WO2022102748A1 - Microscopic examination assistance device, microscopic examination assistance method, automatic dyeing device, automatic dye substance estimation system, program, and recording medium - Google Patents

Microscopic examination assistance device, microscopic examination assistance method, automatic dyeing device, automatic dye substance estimation system, program, and recording medium Download PDF

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Publication number
WO2022102748A1
WO2022102748A1 PCT/JP2021/041744 JP2021041744W WO2022102748A1 WO 2022102748 A1 WO2022102748 A1 WO 2022102748A1 JP 2021041744 W JP2021041744 W JP 2021041744W WO 2022102748 A1 WO2022102748 A1 WO 2022102748A1
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Prior art keywords
information
substance
image
unit
microscopic examination
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PCT/JP2021/041744
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French (fr)
Japanese (ja)
Inventor
悠 平岡
達也 山田
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株式会社GramEye
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Priority to JP2022562205A priority Critical patent/JPWO2022102748A1/ja
Publication of WO2022102748A1 publication Critical patent/WO2022102748A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64—Fluorescence; Phosphorescence
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material

Definitions

  • the present invention relates to a microscopic inspection support device, a microscopic inspection support method, an automatic staining device, an automatic staining substance estimation system, a program, and a recording medium.
  • Patent Document 1 discloses a technique for classifying smear microscopic images and displaying similar images.
  • tests such as smear microscopic examination to detect stained substances (for example, pathogens, cells, etc.) involve a plurality of steps, require the procedure of a clinical laboratory technician, and have a problem that it takes time to obtain results. be. Therefore, in the actual medical field, there is also a problem that the test result is not transmitted to the doctor before prescribing the antibacterial drug and is rarely reflected in the prescription.
  • stained substances for example, pathogens, cells, etc.
  • an object of the present invention is to provide a microscopic inspection support device, a microscopic inspection support method, an automatic staining device, an automatic staining substance estimation system, a program, and a recording medium capable of estimating a staining substance.
  • the microscopic examination support device of the present invention includes image information acquisition unit, recognition estimation unit, count unit, and information output unit.
  • the image information acquisition unit acquires a microscopic image of a stained specimen of a specimen collected from an organism to be inspected, and obtains a microscope image.
  • the recognition estimation unit recognizes the stained substance image in the microscope image, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information.
  • the counting unit counts the image of the dyed substance and generates information on the estimated number of stained substances.
  • the information output unit outputs the dyeing substance estimated type information and the dyeing substance estimated number information. It is a device.
  • the microscopic examination support method of the present invention Including image information acquisition process, recognition estimation process, counting process, and information output process
  • image information acquisition step a microscope image of a stained specimen of a specimen collected from an organism to be inspected is acquired.
  • the recognition estimation step recognizes the stained substance image in the microscope image, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information.
  • the counting step the stained substance images are counted to generate the estimated number of stained substances, and the information is generated.
  • the information output step outputs the dyeing substance estimated type information and the dyeing substance estimated number information. , The way.
  • the automatic dyeing apparatus of the present invention Includes holding section, moving section, staining reagent supply section, and control section.
  • the holding portion can hold the slide glass and can hold the slide glass.
  • the slide glass is smeared with a sample collected from the organism to be inspected.
  • the moving portion can be connected to the holding portion to move the holding portion.
  • the staining reagent supply unit includes a plurality of reagent dropping units.
  • the plurality of reagent dropping portions are arranged side by side according to the dyeing step. Each of the reagent dropping parts of the plurality of reagent dropping parts can drop one kind of reagent according to the dyeing step.
  • the holding portion is arranged below the reagent dropping portion. By controlling the moving unit, the control unit moves the holding unit so as to be located below the reagent dropping unit capable of dropping the reagent that needs to be supplied to the slide glass according to the dyeing step. Let, It is a device.
  • the dyeing substance can be estimated. Therefore, for example, it is possible to support an inspection such as a smear inspection (also referred to as a smear inspection), and the result of the inspection can be obtained more quickly.
  • a smear inspection also referred to as a smear inspection
  • FIG. 1 is a block diagram showing an example of the configuration of the microscopic examination support device of the first embodiment.
  • FIG. 2 is a block diagram showing an example of the hardware configuration of the microscopic examination support device of the first embodiment.
  • FIG. 3 is a flowchart showing an example of processing in the microscopic examination support method of the first embodiment.
  • FIG. 4 is a schematic diagram showing an example of control by the microscope control unit.
  • FIG. 5 is a schematic diagram showing another example of control by the microscope control unit.
  • FIG. 6 is a block diagram showing an example of the configuration of the automatic dyeing apparatus of the second embodiment.
  • FIG. 7 is a schematic diagram showing an example of processing of the control unit during the dyeing process.
  • FIG. 1 is a block diagram showing an example of the configuration of the microscopic examination support device of the first embodiment.
  • FIG. 2 is a block diagram showing an example of the hardware configuration of the microscopic examination support device of the first embodiment.
  • FIG. 3 is a flowchart showing an example of
  • FIG. 8 is a block diagram showing an example of the configuration of the automatic staining substance estimation system of the third embodiment.
  • FIG. 9 is a schematic view showing an example in which the slide glass moves from the lower part of the reagent dropping portion of the automatic dyeing device to the lower part of the objective lens of the microscope device.
  • FIG. 10 is a schematic view showing an example in which the slide glass moves from the sample fixing device to the lower part of the objective lens of the microscope device through the lower part of the reagent dropping portion of the automatic staining device.
  • FIG. 11 is a block diagram showing an example of the configuration of the microscopic examination support device including the related information acquisition unit in the first embodiment.
  • FIG. 12 is a schematic diagram showing an example of information displayed on the display.
  • FIG. 13 is a block diagram showing an example of the configuration of an automatic dyeing substance estimation system including a shading recognition device in the third embodiment.
  • the image acquisition unit acquires a plurality of microscopic images of the stained specimen, and obtains a plurality of microscopic images.
  • the recognition estimation unit recognizes the stained substance image in the plurality of microscope images, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information. May be good.
  • the image acquisition unit acquires the microscope image obtained by capturing the stained specimen at a plurality of magnifications.
  • the recognition estimation unit recognizes the stain substance image in the microscope image of each magnification of the microscope image having a plurality of magnifications, estimates the type of the stain substance from the stain substance image, and obtains the stain substance estimation type information. It may be in the form of generating.
  • the recognition estimation unit calculates the probability of the estimated type of the dyeing substance and generates the estimated type probability information.
  • the information output unit may be in an embodiment in which the estimated type probability information is associated with the dyeing substance estimated type information and output.
  • the recognition estimation unit generates dyeing substance list information listing a plurality of estimated dyeing substances according to the magnitude of the probability.
  • the information output unit may be in the form of outputting the dyeing substance list information.
  • the staining substance may be at least one of a pathogen, a non-pathogen, and cells derived from the organism to be inspected.
  • the recognition estimation unit When the staining substance contains cells derived from the organism to be inspected, the recognition estimation unit generates Geckler classification information based on the staining substance estimation type information and the staining substance estimated number information.
  • the information output unit may be in the form of outputting the Geckler classification information.
  • the microscopic examination support device of the present invention is, for example, In addition, including the related information acquisition department,
  • the related information acquisition unit acquires related information regarding the stained specimen, and obtains the related information.
  • the recognition estimation unit may be in an embodiment of generating the staining substance estimation type information with reference to the related information.
  • the related information may be at least one of information about the sample target organism, information about the sample, and information about the environment.
  • the microscopic examination support device of the present invention is, for example, In addition, it includes a recommended information generator.
  • the recommended information unit generates recommended information based on the stained substance estimated type information.
  • the information output unit may be in the form of outputting the recommended information.
  • the recommended information may be in the form of at least one of the recommended test information and the recommended treatment information.
  • the microscopic examination support device of the present invention is, for example, In addition, including the medical record information acquisition department,
  • the medical record information acquisition unit acquires the medical record information of the organism to be inspected, and obtains the medical record information.
  • the recommended information generation unit may generate the recommended treatment information based on the medical record information.
  • the microscopic examination support device of the present invention is, for example, Including medical record information acquisition department
  • the medical record information acquisition unit acquires the medical record information of the organism to be inspected, and obtains the medical record information.
  • the recognition estimation unit calculates the probability of developing a disease using the medical record information and generates estimated onset probability information.
  • the information output unit may be in a mode of outputting the estimated onset probability information in association with the dyeing substance estimated type information.
  • the microscopic examination support device of the present invention is, for example, In addition, including the infected organ estimation department, the infected organ estimation unit estimates the organ from which the sample is collected as an infected organ and generates estimated infected organ information.
  • the information output unit may be in the form of outputting the estimated infected organ information.
  • the microscopic examination support device of the present invention is, for example, In addition, it includes an image switching judgment unit.
  • the image switching determination unit determines when the microscope image is acquired and when the microscope image is not acquired in the image acquisition unit.
  • the recognition estimation unit and the counting unit switch from the acquisition of the microscope image to the non-acquisition of the microscope image, and then generate the stained substance estimated type information and the stained substance estimated number information, respectively. It may be an embodiment.
  • the microscopic examination support device of the present invention is, for example, Further, it includes at least one of a staining device control unit, a microscope control unit, and a sample fixing device control unit.
  • the staining device control unit controls a staining device that automatically stains the sample and prepares the stained sample.
  • the microscope control unit controls a microscope that captures a microscope image of the stained specimen.
  • the sample fixing device control unit may be in an embodiment of controlling a sample fixing device that performs a fixing process on a sample smeared on a slide glass.
  • the microscope control unit determines whether or not the image is appropriate for each microscope image, and if it is determined that the image is not appropriate, the holding unit is moved in the longitudinal direction of the slide glass, and if it is determined that the image is appropriate, the holding unit is moved.
  • the movement of the holding portion may be controlled so as to move the holding portion in the lateral direction of the slide glass.
  • the microscope control unit acquires the shading data of the entire slide glass, analyzes the shading data to identify a position having a density within a preset range, and starts the visual field search from the position. It may be an aspect of controlling the microscope.
  • the dyeing device control unit can specify the decolorization time in the decolorization step, which is one step of the dyeing step, for each sample, and controls the dyeing device so that the decolorization step is performed at the designated decolorization time. It may be an embodiment.
  • the microscopic examination support device of the present invention is, for example, In addition, it includes a priority setting section.
  • the priority setting unit can set an arbitrary priority for each sample.
  • At least one of the staining device control unit, the microscope control unit, and the sample fixing device control unit is such that the staining device, the microscope, and the sample fixing device are processed in descending order of priority. It may be an aspect of controlling.
  • the image acquisition step a plurality of microscopic images of the stained specimen are acquired, and the image acquisition step is performed.
  • the recognition estimation step is an embodiment in which the stain substance image is recognized in the plurality of microscope images, and the type of the stain substance is estimated from the stain substance image to generate the stain substance estimation type information. May be good.
  • the image acquisition step the microscope image obtained by capturing the stained specimen at a plurality of magnifications is acquired.
  • the recognition estimation step the stain substance image is recognized in the microscope image of each magnification of the microscope image having a plurality of magnifications, and the type of the stain substance is estimated from the stain substance image to obtain the stain substance estimation type information. It may be in the form of generating.
  • the recognition estimation step calculates the estimated probability of the type of dyeing substance and generates the estimated type probability information.
  • the information output step may be in an embodiment in which the estimated type probability information is associated with the dyeing substance estimated type information and output.
  • the staining substance may be at least one of a pathogen, a non-pathogen, and cells derived from the organism to be inspected.
  • the recognition estimation step When the staining substance contains cells derived from the organism to be inspected, the recognition estimation step generates Geckler classification information based on the stained substance estimated type information and the stained substance estimated number information.
  • the information output step may be in the form of outputting the Geckler classification information.
  • the microscopic examination support method of the present invention is, for example, In addition, it includes a related information acquisition process.
  • the related information acquisition step acquires related information regarding the stained specimen, and obtains the related information.
  • the recognition estimation step may be in an embodiment of generating the staining substance estimation type information with reference to the related information.
  • the related information may be at least one of information about the sample target organism, information about the sample, and information about the environment.
  • the microscopic examination support method of the present invention is, for example, In addition, it includes a recommended information generation process.
  • the recommended information generation step generates recommended information based on the stained substance estimated type information.
  • the information output step may be in the form of outputting the recommended information.
  • the recommended information may be in the form of at least one of the recommended test information and the recommended treatment information.
  • the microscopic examination support method of the present invention is, for example, In addition, it includes a medical record information acquisition process.
  • the medical record information acquisition step the medical record information of the organism to be inspected is acquired, and the medical record information is acquired.
  • the medical record information includes the cell estimation type information and the cell estimation number information.
  • the recommended information generation step may be in the form of generating the recommended information based on the medical record information.
  • the microscopic examination support method of the present invention is, for example, In addition, it includes a medical record information acquisition process.
  • the medical record information acquisition step the medical record information of the organism to be inspected is acquired, and the medical record information is acquired.
  • the medical record information includes the cell estimation type information and the cell estimation number information.
  • the recognition estimation step uses the medical record information to calculate the probability of developing a disease and generate estimated onset probability information.
  • the information output step may be in an embodiment in which the estimated onset probability information is associated with the dyeing substance estimated type information and output.
  • the microscopic examination support method of the present invention is, for example, In addition, it includes an infected organ estimation process.
  • the infected organ estimation step using the stained substance image recognized by the recognition estimation step, the organ from which the sample is collected is estimated as an infected organ to generate estimated infected organ information.
  • the information output step may be in the form of outputting the estimated infected organ information.
  • the microscopic examination support method of the present invention is, for example, In addition, it includes an image switching judgment process.
  • image switching determination step in the image acquisition step, it is determined when the microscope image is acquired and when the microscope image is not acquired.
  • the recognition estimation step and the counting step are switched from the acquisition of the microscope image to the non-acquisition of the microscope image, and then the generation of the staining substance estimation type information and the staining substance estimation number information is performed, respectively. May be.
  • the microscopic examination support method of the present invention is, for example, Further, it comprises at least one of a staining device control step, a microscope control step, and a sample fixation device control step.
  • the staining device control step controls a staining device that automatically stains the sample to prepare a stained sample.
  • the microscope control step controls a microscope that captures a microscopic image of the stained specimen.
  • the sample fixing device control step may be an embodiment in which the sample fixing device that performs the fixing process on the sample smeared on the slide glass is controlled.
  • the microscope control step determines whether or not the image is appropriate for each microscope image, and if it is determined that the image is not appropriate, the holding portion is moved in the longitudinal direction of the slide glass, and if it is determined that the image is appropriate.
  • the movement of the holding portion may be controlled so as to move the holding portion in the lateral direction of the slide glass.
  • the shading data of the entire slide glass is acquired, the shading data is analyzed to identify a position having a density within a preset range, and the visual field search is started from the position. It may be an aspect of controlling the microscope.
  • the decolorization time in the decolorization step which is one step of the dyeing step, can be specified for each sample, and the dyeing device is controlled so that the decolorization step is performed at the designated decolorization time. It may be an embodiment.
  • the microscopic examination support method of the present invention is, for example, In addition, it includes a priority setting process.
  • the priority setting step any priority can be set for each sample.
  • At least one of the staining device control step, the microscope control step, and the sample fixing device control step is such that the staining device, the microscope, and the sample fixing device are processed in descending order of priority. It may be an aspect of controlling.
  • the program of the present invention is a program for causing a computer to execute each step of the method of the present invention as a procedure.
  • the recording medium of the present invention is a computer-readable recording medium on which the program of the present invention is recorded.
  • the control unit controls the moving unit after the decolorizing liquid is dropped onto the slide glass by the reagent dropping unit, so that the slide is centered on at least one of the longitudinal direction and the lateral direction of the slide glass.
  • the holding portion may be driven so that the glass is tilted.
  • the control unit has at least one of the longitudinal direction and the lateral direction of the slide glass as an axis, and the lateral direction and the longitudinal direction other than the axis.
  • the holding portion may be driven in at least one of clockwise and counterclockwise so that the inclination of each end portion of the slide glass in the direction becomes a degree predetermined from the reference.
  • the automatic staining substance estimation system of the present invention includes an automatic dyeing device, a microscopic device, and a microscopic inspection support device, and the microscopic inspection support device is the microscopic inspection support device of the present invention.
  • the automatic dyeing apparatus may be an embodiment of the automatic dyeing apparatus of the present invention.
  • the microscopic examination support device includes a display unit and includes a display unit.
  • the display unit may be in an embodiment in which the information output by the information output unit can be displayed.
  • the display unit may be capable of displaying microscope images captured at different focal points for the same field of view.
  • the automated stain estimation system of the present invention is, for example, In addition, including user terminals,
  • the user terminal can display the information output by the information output unit.
  • Arbitrary information may be added to the information output by the information output unit in a situation where it can be shared with other user terminals.
  • the automated stain estimation system of the present invention is, for example, Further, the embodiment may include a sample fixing device.
  • the automated stain estimation system of the present invention is, for example, In the microscopic examination support device
  • the information output unit may also output report information according to the information to be output.
  • the "dyeing substance” is a substance dyed by a dyeing treatment.
  • Specific examples thereof include pathogens, non-pathogens (for example, indigenous bacteria, etc.), cells derived from the organism to be inspected, substances derived from the organism to be inspected (for example, fibrin, crystals, etc.), and the like. It is not limited to these.
  • the pathogen is a substance exhibiting pathogenicity, and includes, for example, organisms such as protozoa, bacteria, viruses, and fungi.
  • the non-pathogenic substance is a substance that does not show pathogenicity, and for example, an example of the pathogen can be incorporated.
  • the dyeing process is not particularly limited. Examples of the dyeing treatment include known dyeing treatments such as Gram stain, Thirneilzen stain, ink stain, Giemsa stain, and Grocott stain. By the staining treatment, a stained specimen described later is prepared.
  • FIG. 1 is a block diagram showing an example of the configuration of the microscopic examination support device 100 of the present embodiment.
  • the present apparatus 100 includes an image information acquisition unit 101, a recognition estimation unit 102, a counting unit 103, and an information output unit 104. Further, the apparatus 100 has an arbitrary configuration, further, a related information acquisition unit 105, a recommended information generation unit 106, a chart information acquisition unit 107, an infected organ estimation unit 108, an image switching determination unit 109, a staining device control unit 110, and the like.
  • the microscope control unit 111, the priority setting unit 112, the sample fixing device control unit 113, the display unit 114, and the like may be included.
  • Reference numeral 109 can be said to be, for example, the inspection support processing unit 100A.
  • the respective parts are connected to each other by, for example, an internal bus.
  • the device 100 may be, for example, one device including the above-mentioned parts, or may be a device in which the above-mentioned parts can be connected via a communication network. Further, the present device 100 can be connected to an external device described later via the communication network.
  • the communication network is not particularly limited, and a known network can be used, and may be wired or wireless, for example.
  • the communication line network includes, for example, an internet line, WWW (World Wide Web), a telephone line, a LAN (Local Area Network), a SAN (Storage Area Network), a DTN (Delay Orient Network), and an LPWA (L). L5G (local 5G), etc. can be mentioned.
  • wireless communication examples include Wi-Fi (registered trademark), Bluetooth (registered trademark), local 5G, LPWA and the like.
  • the wireless communication may be a form in which each device directly communicates (Ad Hoc communication), an infrastructure (infrastructure communication), an indirect communication via an access point, or the like.
  • the apparatus 100 may be incorporated in the server as a system, for example. Further, the apparatus 100 may be, for example, a personal computer (PC, for example, a desktop type, a notebook type), a smartphone, a tablet terminal, a wearable terminal, or the like in which the program of the present invention is installed. Further, all or a part of each part of the apparatus 100 may be realized on the cloud.
  • the present device 100 is in the form of cloud computing, edge computing, or the like, for example, such that at least one of the above parts is on a server (cloud) and the other parts are on a terminal. You may.
  • FIG. 2 illustrates a block diagram of the hardware configuration of the present device 100.
  • the apparatus 100 may include, for example, a central processing unit (CPU, GPU, etc.) 1, a memory 2, a bus 3, a storage device 4, an input device 5, an output device 6, a communication device 7, and the like. It should be noted that these are examples, and the hardware configuration of the present device 100 is not limited to this as long as the processing of each part can be executed. Further, the number of the central processing unit 1 and the like included in the present apparatus 100 is not limited to the example of FIG. 2, and for example, a plurality of central processing units 1 may be included in the present apparatus 100. Each part of the hardware configuration of the present apparatus 100 is connected to each other via the bus 3 by each interface (I / F).
  • I / F interface
  • the central processing unit 1 is responsible for overall control of the device 100.
  • the program of the present invention and other programs are executed by the central processing unit 1, and various information is read and written. Then, the central processing unit 1 can execute the processing of each part of the apparatus 100.
  • Bus 3 can also be connected to, for example, an external device.
  • the external device include an external storage device (external database, etc.), an external input device, an external output device, and the like.
  • the device 100 can be connected to an external network (the communication network) by, for example, a communication device 7 connected to the bus 3, and can also be connected to another device via the external network.
  • the memory 2 may be, for example, a main memory (main storage device).
  • main memory main storage device
  • the memory 2 reads various operation programs such as the program of the present invention stored in the storage device 4 described later, and the central processing unit 1 reads the various operation programs from the memory 2. Receive the data and run the program.
  • the main memory is, for example, a RAM (random access memory).
  • the memory 2 may be, for example, a ROM (read-only memory).
  • the storage device 4 is also referred to as a so-called auxiliary storage device with respect to the main memory (main storage device), for example.
  • the storage device 4 stores an operation program including the program of the present invention.
  • the storage device 4 may be, for example, a combination of a recording medium and a drive for reading and writing to the recording medium.
  • the recording medium is not particularly limited, and may be an internal type or an external type, and examples thereof include HD (hard disk), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, and memory card. Be done.
  • the storage device 104 may be, for example, a hard disk drive (HDD) in which a recording medium and a drive are integrated, and a solid state drive (SSD).
  • HDD hard disk drive
  • SSD solid state drive
  • the memory 2 and the storage device 4 perform log information, information acquired from an external database (not shown) or an external device, information generated by each process of the device 100, and each process of the device 100. It is also possible to store various information such as information used at the time of execution. It should be noted that at least a part of the information may be stored in an external server other than the memory 2 and the storage device 4, or may be distributed and stored in a plurality of terminals by using blockchain technology or the like. ..
  • the device 100 may further include, for example, an input device 5 and an output device 6.
  • the input device 5 is, for example, a device for inputting characters, numbers, the position of an object displayed on the screen, an image, a sound, and the like, and specifically, a digitizer (touch panel, etc.), a keyboard, a mouse, a scanner, and an image pickup. Devices, microphones, sensors and the like can be mentioned.
  • Examples of the output device 6 include a display device (LED display, liquid crystal display), a printer, a speaker, and the like.
  • the display unit 114 may display various information using, for example, the display device of the output device 6.
  • the present device 100 can be applied to, for example, an inspection using a microscope image taken by a microscope.
  • the examination is not particularly limited, and is, for example, a smear inspection (inspection relating to staining such as Gram stain, Thirneilzen staining, fungal staining, Giemsa staining, etc.), pathological specimen inspection, and the like.
  • the microscopic examination support method of the present embodiment is carried out as follows, for example, by using the microscopic examination support device 100 of FIG.
  • the microscopic examination support method of the present embodiment is not limited to the use of the microscopic examination support device 100 of FIG.
  • the image information acquisition step can be executed by, for example, the image information acquisition unit 101
  • the recognition estimation step can be executed by, for example, the recognition estimation unit 102
  • the counting process can be executed by, for example, the counting unit 103.
  • the information output step can be executed by, for example, the information output unit 104
  • the related information acquisition step can be executed by, for example, the related information acquisition unit 105
  • the recommended information generation step can be executed by, for example, the recommended information generation unit 106.
  • the chart information acquisition step can be executed, for example, by the chart information acquisition unit 107
  • the infected organ estimation step can be executed by, for example, the infected organ estimation unit 108
  • the image switching determination step can be executed, for example, by image switching.
  • the staining device control step can be executed by, for example, the staining device control unit 110
  • the microscope control step can be executed by, for example, the microscope control unit 111
  • the priority setting step can be executed, for example, by the microscope control unit 111.
  • the sample fixing device control step can be executed by, for example, the sample fixing device control unit 113.
  • the image information acquisition unit 101 acquires a microscopic image of a stained specimen of a specimen collected from an organism to be inspected (S101).
  • the organism to be inspected is not particularly limited, and may be, for example, a human or a non-human organism.
  • the microscope image refers to an image captured by a microscope.
  • the recognition estimation unit 102 recognizes the stained substance image in the microscope image, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information (S102A).
  • the dyed substance image means an image to which the dyed substance is transferred. That is, it can be said that the recognition estimation unit 102 recognizes the staining substance in the microscope image.
  • the recognition estimation unit 102 may be able to estimate the types of the plurality of dyeing substances, for example.
  • the dyeing substance estimation type information may indicate, for example, a plurality of types of the dyeing substance.
  • the recognition estimation unit 102 may estimate morphological characteristics such as gram-positive streptococcus, gram-negative streptococcus, and yeast-like fungus, or organisms such as Enterobacteriaceae , Pseudomonas , and Streptococcus . It may be estimated by the family name and genus name in the classification, or by the species name in the biological classification such as Streptococcus agalactiae , Escherichia coli , Pseudomonas aeruginosa and the like.
  • the counting unit 103 counts the stained substance images and generates information on the estimated number of stained substances (S103). More specifically, the number of the dyed substances recognized by the recognition estimation unit 102 in the stained substance image is counted.
  • the information on the estimated number of dyed substances is information indicating the number of the dyed substances. The counting may be performed for each type of the dyeing substance estimated by the recognition estimation unit 102.
  • the information output unit 104 outputs the stain substance estimated type information and the stain substance estimated number information (S104), and ends (END).
  • the method of output by the information output unit 104 is not particularly limited, and for example, the output device 6 may be used for output, or the communication device 7 may be used for output to an external device.
  • the type of the dyeing substance can be automatically estimated, and the count can also be automated. Therefore, according to the present embodiment, it is possible to support an inspection such as a smear microscopic examination. Specifically, the automation can reduce the time required for inspection and the human cost. In addition, the burden on the inspection engineer can be reduced. Further, according to the present embodiment, it is possible to present the information to the medical staff by outputting the information on the estimated type of the dyeing substance and the information on the estimated number of the dyeing substances.
  • the image information acquisition unit 101 may acquire a plurality of microscope images of the stained specimen in the step S101, for example.
  • the recognition estimation unit 102 recognizes the stain image in the plurality of microscope images, estimates the type of the stain substance from the stain image, and estimates the stain substance type. Information may be generated.
  • the recognition estimation unit 102 may generate the stain substance estimation type information for each of the microscope images, or the stain substance estimation type information (the said for a plurality of microscope images) for one stain sample. Staining substance estimation type information) summarizing the estimation results may be generated.
  • the plurality of microscope images may be images captured in different fields of view, or may be images captured at different focal points for one field of view. By acquiring a plurality of microscope images in this way, it is possible to improve the accuracy of the processing of the recognition estimation unit 102 and, by extension, the inspection.
  • the image information acquisition unit 101 may acquire, for example, the microscope image obtained by capturing the stained specimen at a plurality of magnifications in the step S101.
  • the recognition estimation unit 102 recognizes the stain substance image in the microscope image of each magnification of the microscope image having a plurality of magnifications, and the type of the stain substance from the stain substance image. May generate the estimated type information of the staining substance.
  • the recognition estimation unit 102 may generate the stain substance estimation type information for each microscope image of each magnification, or one stain substance estimation type information (of each magnification) for one stain sample. (Staining substance estimation type information) that summarizes the estimation results for the microscope image may be generated.
  • the accuracy of the processing of the recognition estimation unit 102 and, by extension, the inspection can be improved by taking the microscope image taken at a plurality of magnifications.
  • the recognition estimation unit 102 may calculate the estimated probability of the type of the dyeing substance and generate the estimated type probability information.
  • the probability of the type of the dyeing substance means "the certainty that the dyeing substance is the type".
  • the recognition estimation unit 102 may calculate the estimated probability of the type of dyeing substance by machine learning, for example.
  • the estimated type probability information may be, for example, "Pseudomonas 90%” or the like, and may be associated with the type of the dyeing substance to express the probability numerically (percentage or the like), or may be a character (for example,).
  • the information output unit 104 may output the estimated type probability information in association with the stained substance estimated type information in the step S104, for example.
  • the estimated type probability information linked to the estimated type information of the stained substance a format in which the name of the stained substance and the probability are combined, such as "Streptococcus pneumoniae 95%” and "Mycoplasma 80%".
  • this is an example and is not limited to this. In this way, by generating the estimated type probability information, it is possible to further support the inspection, and a person (for example, a medical worker) who has acquired the estimated type probability information can easily determine the type of the dyeing substance and its probability. It is possible to grasp.
  • the test information includes, for example, information on various tests such as CRP (C-reactive protein) indicating the degree of inflammation, white blood cell count, body temperature, respiratory function, urine volume, and ⁇ -D glucan.
  • the text information includes, for example, information on the presence / absence of cough, the presence / absence of dyspnea, the presence / absence of lower back pain, X-ray findings, severity, infected organs, drug processing function, and the like.
  • the inspection information and the text information may be acquired by, for example, the medical record information acquisition unit 107 described later.
  • the recognition estimation unit 102 calculates the weight of the parameter for each type of the dyeing substance using the inspection information and each information included in the text information as parameters, and uses the weight of the parameter to calculate the weight according to a specific calculation formula. Calculate the probability.
  • the specific calculation formula is not particularly limited and can be set arbitrarily.
  • the recognition estimation unit 102 calculates the probability by using each information generated by the present apparatus 100 such as the stain substance estimation type information and the stain substance estimated number information, in addition to the inspection information and the text information, for example. You may.
  • the recognition estimation unit 102 may generate a dyeing substance list information listing a plurality of estimated dyeing substances according to the magnitude of the probability of the estimated type of the dyeing substance. ..
  • the stain substance list information may also serve as, for example, the estimated type probability information associated with the stain substance estimated type information.
  • the dyeing substance list information may be those in which the types of the dyeing substances are arranged in descending order of the probability, or may be those in which the types of the dyeing substances are arranged in the order of the smaller probability.
  • the information output unit 104 may output the dyeing substance list information in the step S104, for example.
  • the dyeing substance list information by generating the dyeing substance list information, it is possible to further support the inspection, and a person (for example, a medical worker) who has acquired the dyeing substance list information can easily determine the type of the dyeing substance and its probability. It is possible to grasp.
  • the staining substance is, for example, at least one of a pathogen, a non-pathogen, and cells derived from the organism to be inspected.
  • the cells derived from the test target organism are, for example, epithelial cells and leukocyte cells in a sputum sample, phagocytic leukocyte cells and the like.
  • the recognition estimation unit 102 When the staining substance includes cells derived from the organism to be inspected, the recognition estimation unit 102, for example, after the step S103, has Geckler classification information based on the staining substance estimation type information and the staining substance estimated number information. May be generated. The generation of the Geckler classification information may be performed, for example, before the step S104 or after the step S104. Then, the information output unit 104 may output, for example, the Geckler classification information.
  • the Geckler classification information is information indicating to which group of the Geckler classification the sample of the organism to be inspected belongs.
  • the recognition estimation unit 102 estimates at least leukocytes and squamous epithelial cells from the stained substance image, and the counting unit 13 at least determines the number of the leukocytes and the number of the squamous epithelial cells. Count. By generating the Geckler classification information in this way, the sample can be evaluated.
  • the apparatus 100 may further include, for example, the related information acquisition unit 105.
  • FIG. 11 shows an example of the configuration of the present apparatus 100 including the related information acquisition unit 105.
  • the related information acquisition unit 105 acquires, for example, related information regarding the stained specimen before the step S102A (S105).
  • the step S105 is an arbitrary step and may not be executed.
  • the related information is, for example, at least one of information about the sample target organism, information about the sample, and information about the environment. More specifically, for example, the age of the sample target organism (human or the like), the disease name, the biological state of the sample target organism, the medication history, the location of the medical institution, the antibiogram in the medical institution, and the like.
  • the apparatus 100 may further include, for example, the recommended information generation unit 106.
  • the recommended information generation unit 106 may generate recommended information based on the dyeing substance estimation type information, for example, after the step S102A (S106).
  • the step S106 is an arbitrary step and may not be executed.
  • the recommended information is, for example, at least one of recommended test information and recommended treatment information.
  • the recommended test information is, for example, information on additional tests for identifying bacterial species such as culture. More specifically, for example, when a fungal-like object is confirmed by Gram stain of sputum, recommended test information is generated that recommends culturing in a selective medium that selectively grows fungi.
  • the recommended treatment information is, for example, information on the type of antibiotic to be prescribed, the treatment policy, and the like.
  • the recommended information generation unit 106 may generate the recommended information by referring to the related information, for example. Then, the information output unit 104 may output the recommended information, for example (S104). For example, when the recommended test information is generated, the information output unit 104 may notify a medical worker such as a test technician that the recommended test information has been generated. By generating the recommended information in this way, it is possible to support medical professionals such as laboratory technicians.
  • the recommended treatment information since the staining substance can be estimated in more detail and accurately, the recommended treatment information also has more detailed and accurate contents, and the selection of the therapeutic agent by the medical staff And can more support the decision of treatment policy.
  • the present device 100 may further include, for example, a medical record information acquisition unit 107.
  • the medical record information acquisition unit 107 acquires, for example, the medical record information of the organism to be inspected before the step S102B or the step S106 described later (S107).
  • the step S107 is an arbitrary step and may not be executed.
  • the chart information may include, for example, the above-mentioned test information and the text information, and more specifically, as a result of the test, body temperature, leukocyte count, C-reactive protein value, X-ray finding, severity, and the like.
  • There is information about the living body of the sample target organism such as an infected organ and a drug processing function.
  • the result of the inspection may be, for example, the dyeing substance estimated type information and the dyeing substance estimated number information.
  • the medical record information acquisition unit 107 may acquire the medical record information from an external device via the communication network, or may acquire the medical record information input via the input device 5.
  • the recommended information generation unit 106 may generate the recommended treatment information based on the medical record information, for example, in the step S106.
  • a narrow-range antibacterial drug is selected, it becomes possible to suppress the outbreak of drug-resistant bacteria and the drug price.
  • the present invention by generating the recommended treatment information using the medical record information, it is possible to support the selection of a narrow-range antibacterial drug and the like, and more appropriate and effective treatment becomes possible.
  • the recognition estimation unit 102 may generate the estimated onset probability information by calculating the probability of developing a disease by using at least the medical record information, for example (S102B). In addition to the chart information, the recognition estimation unit 102 may calculate the probability by using each information generated by the present apparatus 100 such as the dyeing substance estimation type information and the dyeing substance estimated number information. As the method for calculating the probability, for example, a known method may be used, or a method described later may be used. The recognition estimation unit 102 may calculate the probability of developing a disease by machine learning, for example.
  • the estimated onset probability information may be, for example, expressing the probability numerically (percentage or the like) in association with the type of the disease, characters (for example, "high probability", “low probability”, etc.). ), Symbols, and other numbers may be used to express the probability.
  • the information output unit 104 may output the estimated onset probability information in association with the stained substance estimated type information in, for example, in the step S104.
  • the estimated type probability information linked to the estimated type information of the stained substance the name and probability of the stained substance such as "bacterial pneumonia 95%” and "atypical pneumonia 80%" are used. There are combined formats, but this is an example and is not limited to this.
  • the estimated onset probability information is output in association with the estimated onset probability information, for example, it is possible to support a medical worker.
  • the recognition estimation unit 102 calculates the weight of the parameter for each type of disease by using, for example, each information included in the test information and the text information as a parameter, and uses the weight of the parameter to calculate the probability by a specific calculation formula. Is calculated.
  • the specific calculation formula is not particularly limited and can be set arbitrarily.
  • the apparatus 100 may further include, for example, an infected organ estimation unit 108.
  • the infected organ estimation unit 108 estimates that the organ from which the sample is collected is an infected organ by analysis using the staining substance image recognized by the recognition estimation unit 102, and estimates the infected organ. Information may be generated (S108). Further, the infected organ estimation unit 108 may estimate the organ from which the sample was collected, for example, by analyzing the image of the stained substance.
  • the infected organ means an organ infected with the staining substance (particularly, at least one of a pathogen and a non-pathogen).
  • the information output unit 104 outputs, for example, the estimated infected organ information in the step S104.
  • the information output unit 104 outputs, for example, the estimated infected organ information in the step S104.
  • the infected organ estimation unit 108 uses the organ from which the sample was collected as an infected organ. May be estimated.
  • (1) At least one of the pathogen and the non-pathogen, and both leukocytes
  • the cause of the disease is not limited to the pathogen, and for example, indigenous bacteria may be the cause of the disease.
  • the present device 100 may further include, for example, an image switching determination unit 109.
  • the image switching determination unit 109 determines when the microscope image is acquired and when the microscope image is not acquired (S109). Then, the recognition estimation unit 102 and the counting unit 103 switch from the acquisition of the microscope image to the non-acquisition of the microscope image, and then generate the stained substance estimated type information and the stained substance estimated number information, respectively. You may.
  • the apparatus 100 may further include, for example, at least one of the staining apparatus control unit 110, the microscope control unit 111, and the sample fixing device control unit 113.
  • the staining device control unit 110 controls a staining device that automatically stains the sample and prepares the stained sample.
  • the timing of control by the dyeing apparatus control unit 110 is not particularly limited, but is executed, for example, before the step S101.
  • the dyeing device may be, for example, the automatic dyeing device of the present invention.
  • the microscope control unit 111 controls a microscope that captures a microscope image of the stained specimen.
  • the timing of control by the microscope control unit 111 is not particularly limited, but is executed, for example, before the step S101.
  • the image acquisition unit 101 acquires, for example, the microscope image captured by the microscope.
  • the "slide glass” in the present invention may be laminated with a cover glass, if necessary. That is, the “slide glass” in the present invention can be read as "preparation” as needed. For example, if the method of staining the sample is Gram stain, imaging with the microscope may be performed without a cover glass.
  • FIG. 4 An example of control by the microscope control unit 111 will be described with reference to FIG.
  • the sample is often spread on the slide glass 10 in the direction of the arrow from A. Therefore, when observing with a microscope in the longitudinal direction of the slide glass 10, as shown on the right side of FIG. 4, darkly smeared portions of the sample appear at regular intervals.
  • the right side of FIG. 4 is a partially enlarged view of the slide glass 10.
  • the shading means the density of the smear of the sample, and the darker the shading in the figure, the darker the sample is the smeared region.
  • the portion surrounded by the thick frame means the visual field region by the microscope (that is, the microscope image), and the arrow indicates the movement of the visual field region (that is, the slide glass 10). It means the movement of the holding part that holds the.
  • the microscope control unit 111 determines whether or not the microscope image in the visual field region (1) is an appropriate image.
  • the proper image is, for example, an image in which a dyeing substance with good dyeing is reflected or an image in which the dyeing substance is clearly visible.
  • the smear of the sample is too thin, so that the dyeing substance cannot be clearly seen, and it is determined that the image is not appropriate.
  • the microscope control unit 111 determines whether or not the image is appropriate for each of the microscope images, and if it is determined that the image is not appropriate, the microscope control unit 111 moves in the longitudinal direction of the slide glass 10 and determines that the image is appropriate. In this case, the movement of the holding portion is controlled so as to move in the lateral direction of the slide glass 10.
  • the smear of the sample on the slide glass 10 is often spread as shown on the left side of FIG. 4, so when observed with a microscope in the longitudinal direction of the slide glass 10, the right side of FIG. 4 is observed.
  • areas where the sample is heavily smeared appear at regular intervals. Therefore, when an image with an appropriate darkness that is useful for clinical judgment is found, there is a high possibility that an image with an appropriate darkness will also be found on the side in the lateral direction.
  • more efficient visual field search becomes possible.
  • the microscope control unit 111 acquires the shading data of the entire slide glass 10.
  • the shading data is, for example, as shown on the left side of FIG. 5, information indicating the shading of the smear of the sample generated by reading the entire slide glass 10 with the shading recognition device 20.
  • the shade recognition device 20 for example, a known device such as a camera or a sensor can be used.
  • the shade recognition device 20 may be, for example, an input device 5 or an external device.
  • the microscope control unit 111 analyzes the shading data and identifies a position having a density within a preset range. The density can be set arbitrarily.
  • the microscope control unit 111 controls the movement of the holding unit so as to start the visual field search from the position.
  • the sample is smeared on the slide glass by an inspection engineer, but there is a problem that it takes time to search for an appropriate field of view and detect pathogens and the like because shading is formed in the slide glass.
  • the pathogens or cells are often invisible even when the spot where the sample is thinly smeared is observed with a microscope.
  • this aspect since it is possible to grasp the shading of the smear, more efficient visual search can be performed.
  • the dyeing apparatus control unit 110 may be able to specify, for example, the decolorization time in the decolorization step, which is one step of the dyeing step, for each sample.
  • the decolorization time can be specified by inputting the decolorization time by a user (medical personnel or the like).
  • the dyeing step is not particularly limited, and may be a step of a conventionally known dyeing method.
  • a staining method there are Gram stain, which mainly examines the presence or absence and characteristics of bacteria, and Thirneilsen staining, which mainly examines the presence and characteristics of acid-fast bacilli.
  • the dyeing device control unit 110 controls the dyeing device so as to carry out the decolorization step at the designated decolorization time, for example.
  • the dyeing apparatus control unit 110 may be able to specify the time required for steps other than the decolorization step for each sample. Then, the dyeing device control unit 110 may control the dyeing device so as to carry out the step at a designated time, for example. This makes it possible to improve the accuracy of dyeing.
  • pathogens that should be stained with Gram-positive (purple) due to excessive decolorization are stained with Gram-negative (red), and pathogens that should be stained with Gram-negative (red) are stained with Gram-positive (purple).
  • this problem is not limited to Gram stain and can occur. Therefore, incorrect test results may be obtained.
  • factors that determine the degree of decolorization include the decolorization time and the contact between the sample and the decolorizing liquid.
  • the decolorization time is about 5 to 7 seconds for a sample whose smear is watery and thin (for example, blood culture sample or urine), but it takes 10 seconds or more for a sample such as highly viscous sputum. Sometimes.
  • the staining device control unit 110 can specify the decolorization time input by the user for each sample, any sample can be appropriately decolorized.
  • the present device 100 may further include, for example, a priority setting unit 112.
  • the priority setting unit 112 can set an arbitrary priority for each sample. Specifically, the present device 10 sets the priority input by the medical staff to the sample via, for example, the input device 5.
  • the priority is represented by, for example, numbers, letters, symbols, and the like.
  • at least one of the staining device control unit 110, the microscope control unit 111, and the sample fixing device control unit 113 is subjected to processing of the staining device, the microscope, and the sample fixing device in descending order of priority. To control.
  • the processing for the sample is not in the order of setting in various devices but in the order of priority, so that one sample is processed before the other sample set before the one sample.
  • So-called interrupts can occur.
  • the time priority for returning test results differs depending on the type of sample and the clinical department. For example, when a blood culture sample becomes positive for culture, sepsis is suspected, but since sepsis is a very urgent disease, immediate bacterial species (staining substance) estimation and antibacterial drug administration are required. It is also desirable to return the test results as soon as possible for the samples submitted by the emergency department.
  • the priority setting unit 112 since the priority can be set, it is possible to give priority to the sample having the highest priority for processing by the apparatus 100 or the like.
  • FIG. 6 is a schematic view showing an example of the configuration of the automatic dyeing apparatus 200 of the present embodiment.
  • the apparatus 200 includes a holding unit 201, a moving unit 202, a staining reagent supply unit 203, and a control unit 204.
  • the apparatus 200 may further include, as an arbitrary configuration, a waste liquid tank 205, a staining reagent bottle 206, and the like, and conventionally known configurations.
  • the control unit 204 is executed by, for example, a central processing unit 1 which is one of the hardware included in the automatic dyeing device 200.
  • the configuration of other hardware of the automatic dyeing apparatus 200 is not particularly limited, and for example, the hardware configuration described in the first embodiment can be incorporated.
  • the holding portion 201 can hold the slide glass 10. As described above, also in the present embodiment, "slide glass” can be read as "preparation” as needed. On the slide glass 10, for example, after the dyeing step is completed, a cover glass is placed on the slide glass 10 to prepare the slide glass 10.
  • the form of the holding portion 201 is not particularly limited as long as it can hold the slide glass 10.
  • the holding portion 201 is, for example, as shown in FIG. 6, a stage-shaped holding portion 201, which may be capable of mounting and holding the slide glass 10, or a clip-shaped holding portion as described later.
  • the number is 201, and the slide glass 10 may be sandwiched and held. It is assumed that the slide glass 10 is smeared with a sample collected from the organism to be inspected.
  • the holding portion 201 is arranged below the reagent dropping portion 2031 and holds the surface of the slide glass 10 on which the sample is smeared toward the reagent dropping portion 2031.
  • the moving unit 202 is connected to the holding unit 201 and can move the holding unit 201.
  • the form of the moving unit 202 is not particularly limited as long as the holding unit 201 can be moved.
  • the movement may be horizontal movement, vertical movement, or rotational movement.
  • the dyeing reagent supply unit 203 includes a plurality of reagent dropping units 2031. As shown in FIG. 6, the plurality of reagent dropping portions 2031 are arranged side by side according to the dyeing step.
  • the dyeing step is not particularly limited and is, for example, the same as described above.
  • Each reagent dropping section 2031 of the plurality of reagent dropping sections 2031 can drop one type of reagent according to the dyeing step.
  • the reagent is housed in, for example, a stain reagent bottle 206.
  • the staining reagent supply unit 203 supplies the reagent from the staining reagent bottle 206 to the reagent dropping unit 2031, for example.
  • the reagent dropping unit 2031 may, for example, drop the reagent only on or around the sample, or may drop the reagent so as to fill the stage-shaped holding portion 201 with the reagent.
  • control unit 204 may control each unit so that the reagent is dropped after the lapse of time instructed by the dyeing apparatus control unit 110, for example. Further, the control unit 204 may control the time from the dropping of the reagent to the waste liquid tank 205 by controlling the dyeing reagent supply unit 203, for example. Specifically, the control unit 204 drains the reagent dropped on the surface of the slide glass 10 on which the sample is smeared after the lapse of time instructed by the dyeing device control unit 110 into the waste liquid tank 205. Each part may be moved to.
  • FIG. 7 shows an example of the slide glass 10 held by the clip-shaped holding portion 201.
  • the surface of the slide glass 10 facing the reagent dropping portion 2031 is smeared with a sample collected from the organism to be inspected.
  • the control unit 204 controls the moving unit 202 after the decolorizing liquid is dropped on the slide glass 10 by the reagent dropping unit 2031 to axis the longitudinal direction of the slide glass 10.
  • the holding portion 201 is driven so that the slide glass 10 is tilted in the lateral direction. Not limited to the example shown in FIG.
  • control unit 204 may drive the holding unit 201 so that the slide glass 10 is tilted in the longitudinal direction with respect to the lateral direction of the slide glass 10, for example. Further, the control unit 204 may drive the holding unit 201 so that the slide glass 10 is tilted alternately in the longitudinal direction and the lateral direction, for example, with the longitudinal direction and the lateral direction of the slide glass 10 as axes alternately. ..
  • the control unit 204 may use at least one of the longitudinal direction and the lateral direction of the slide glass 10 as an axis. Even if the holding portion 201 is driven to at least one of clockwise and counterclockwise so that the inclination of each end of at least one of the slide glass 10 in the lateral direction and the longitudinal direction becomes a degree predetermined from the above reference. good.
  • the degree is not particularly limited and can be set arbitrarily.
  • the degree is, for example, -10 degrees or more and +10 degrees or less, -5 degrees or more and +5 degrees or less, -3 degrees or more and +3 degrees or less, etc., when the inclination of one end in the reference state is 0 degrees. It is the state of any value in the range of.
  • the driving of the holding unit 201 is executed by the control unit 204 controlling the moving unit 202.
  • the control unit 204 drives the holding unit 201 in specific seconds (for example, 1 to 5 seconds, 1 to 3 seconds, 1 second, etc.) and at specific time intervals (for example, 1 to 5 seconds, 1 second, etc.). It may be repeated a plurality of times in ⁇ 3 seconds, 1 second, etc.). By performing such control, each reagent can be uniformly applied to the sample, and the accuracy of staining can be improved.
  • the decolorization process is a process in which it is difficult to properly decolorize as described above.
  • factors that determine the degree of bleaching include the bleaching time and the contact between the sample and the bleaching solution. Since the control unit 204 can efficiently touch these by the above control, the accuracy of decolorization can be improved.
  • the sample staining process can be performed automatically, it is possible to support inspections such as smear inspection.
  • the sample fixing device 500 is not particularly limited as long as it is a device that performs a fixing process on the sample smeared on the slide glass.
  • the fixing process is not particularly limited, and a conventionally known fixing process can be applied.
  • the fixing treatment includes, for example, a treatment using heat, a treatment using alcohol, and the like.
  • the sample subjected to the fixing treatment is stained by the automatic staining apparatus 200.
  • the sample in a tube or the like is smeared on a slide glass to kill bacteria and viruses, and immobilization is performed. After that, the processes of dyeing, drying, microscopic observation, and medical record entry are continued.
  • alcohol also referred to as alcohol fixation
  • the fixing process can be automated and the burden on the site can be further reduced. Further, by using the sample fixing device 500, the method used for the fixing process can be unified, so that the accuracy of the inspection can be improved.
  • the automatic staining apparatus 200 is not particularly limited as long as it is an apparatus that automatically stains the specimen to prepare a stained specimen, and is, for example, the automatic staining apparatus 200 according to the second embodiment.
  • the stained specimen prepared by the automatic staining device 200 is set in the microscope device 300, and a microscope image is taken. The set may be performed manually, for example.
  • the slide glass 10 may be manually moved from the lower part of the reagent dropping part 2031 of the automatic dyeing device 200 to the lower part of the objective lens 301 of the microscope device 300, but the moving part 202 is moved as shown in FIG. You may go by. If necessary, the cover glass may or may not be laminated on the slide glass 10 before the slide glass 10 is moved to the lower part of the objective lens 301 of the microscope device 300.
  • the laminating may be performed manually, for example.
  • FIG. 9 is a schematic view showing an example in which the slide glass 10 moves from the lower part of the reagent dropping portion 2031 of the automatic dyeing device 200 to the lower part of the objective lens 301 of the microscope device 300. As shown in FIG.
  • the sample is smeared on the slide glass 10 by the inspection engineer, and the slide glass 10 is set on the holding unit 201, whereby the staining process, the imaging with a microscope, and the imaging are performed.
  • the estimation of the dyeing substance can be performed fully automatically. As a result, it is possible to significantly reduce the labor required for Gram stain, Ziehl-Neelsen stain, and the like.
  • the slide glass 10 may be manually moved from the sample fixing device 500 to the lower part of the reagent dropping section 2031 of the automatic staining device 200, but it may also be moved by moving the moving section 202 as shown in FIG. good.
  • FIG. 10 is a schematic view showing an example in which the slide glass 10 moves from the sample fixing device 500 to the lower part of the objective lens 301 of the microscope device 300 through the lower part of the reagent dropping portion 2031 of the automatic staining device 200.
  • the moving unit 202 may be movable to, for example, the lower part of the sample fixing device 500.
  • the moving unit 202 may move in this way under the control of, for example, the control unit 204.
  • the moving unit 202 may be movable from the sample fixing device 500 to the lower part of the objective lens 301 of the microscope device 300, passing through the lower part of the reagent dropping part 2031 of the automatic staining device 200, for example.
  • a series of steps from fixing process, staining process, imaging with a microscope, and estimation of the stained substance can be performed fully automatically, and the labor can be further reduced.
  • the microscope device 300 (also simply referred to as a microscope 300) is not particularly limited as long as it can capture a microscope image of the stained specimen, and may be, for example, a known device.
  • the microscope image taken by the microscope device 300 is acquired by the microscope inspection support device 100.
  • the microscopic examination support device 100 may include, for example, a display unit 114 that displays information output by the information output unit 104.
  • the display unit 114 may be able to display microscope images captured at different focal points for the same field of view, for example, by a user's operation.
  • the microscopic images taken at the different focal points are included, for example, in the stained substance estimation type information.
  • the user's operation is not particularly limited, and is, for example, an operation such as moving a mouse wheel. This enables three-dimensional observation.
  • This aspect is particularly useful for confirming, for example, a capsule formation image of Streptococcus pneumoniae.
  • the capsule formation image of Streptococcus pneumoniae is difficult to confirm on a flat surface, and can be confirmed by intentionally shifting the focus.
  • the various processes performed by the display unit 114 can be said to be, for example, a display process.
  • the display unit 114 may attach identification information to each slide glass 10 and display the identification information.
  • the identification information is not particularly limited, and may be, for example, numbers, letters, symbols, and combinations thereof.
  • FIG. 12 shows an example of the identification information and the like displayed on the display by the processing of the display unit 114.
  • the display unit 114 has, for example, the identification information of the slide glass 10 (indicated as a unique number for each slide glass 10) and the inserted state of the slide glass 10 (whether or not it is held by the holding unit 201). Or) may be displayed in association with each other.
  • the inserted state is displayed as "inserted”, and if the slide glass 10 is removed from the holding portion 201, for example, the inserted state is "removed”. Is displayed.
  • the terms "inserted” and “removed” are examples, and the present invention is not limited thereto.
  • the display unit 114 displays, for example, the time taken for each step of the dyeing process set by the dyeing device control unit 110 based on the input to the user in association with the identification information. You may. Further, the display unit 114 may display the priority set by the priority setting unit 112 based on the input to the user in association with the identification information, for example, as shown in FIG. In FIG. 12, the priorities are displayed as “ ⁇ ”, “ ⁇ ”, and “ ⁇ ” in descending order of priority.
  • the display unit 114 may display, for example, each information generated by the microscopic examination support device 100 in a table format as shown in FIG. 12, but this is an example and is not limited thereto.
  • the user terminal 400 is a terminal of a user such as a medical worker. Specifically, there are personal computers (PCs, for example, desktop type, notebook type), smartphones, tablet terminals, wearable terminals and the like.
  • the user terminal 400 is not particularly limited as long as it can display the information output by the information output unit 104 and can add arbitrary information to the information output by the information output unit.
  • the information output by the information output unit 104 may be, for example, in a situation where it can be shared by a plurality of user terminals 400.
  • the situation that can be shared by a plurality of user terminals 400 is, for example, a situation in which the automatic staining substance estimation system 1000 is stored in a server, a database, or the like inside or outside the system 1000.
  • the Gram stain and the chart input place, and the work called culture determination, which is a post-staining step in the microbial identification test, are carried out at different places. Even if each work is performed in different places in this way, by performing the addition to the information under the situation, the information and the information can be added to the plurality of user terminals 400. It is possible to share the contents that have been made.
  • the information output unit 104 may output the report information in association with the information according to the information to be output, for example.
  • the notification information is information that means, for example, that an infectious disease is suspected or that a specific response is required. For example, when the stained substance estimated type information is generated and an infectious disease is suspected, when the recommended test information is generated and the need for the additional test (test other than routine test) is high, the stained substance estimated type information is generated.
  • the notification information is output when it is determined that an urgent response is necessary based on the content of the information on the estimated number of stained substances.
  • the stained substance estimation type information indicating that a gram-positive staphylococcus was estimated is generated, it is suspected that a resistant bacterium called MRSA is ineffective, and a strong antibacterial drug different from the routine is administered. You will need it.
  • the stained substance estimation type information indicating that leukocytes or phagocytic leukocytes were estimated is generated, it means that an inflammatory reaction is occurring at the place where the sample was collected, and many of these objects are present. If found, it will need to be treated as an infectious disease. When such a sample can be confirmed, the medical worker can promptly respond by outputting the notification information in association with information such as information on the estimated type of dyeing substance.
  • a specific process associated with the notification information is executed in the output destination device and device. For example, if the output destination is a speaker, an alarm sounds, if the output destination is a monitor, notification information is displayed on the monitor, or if the output destination is a lamp, the lamp blinks. ..
  • the automatic dyeing substance estimation system 1000 may further include, for example, a shade recognition device 20.
  • the microscopic examination support device 100 can communicate with the light and shade recognition device 20.
  • the shading recognition device 20 is a device capable of recognizing the shading of an object, and the above description can be incorporated.
  • the automatic staining substance estimation system 1000 may use the shading recognition device 20 and the sample fixing device 500 in combination.
  • the stained specimen prepared by the staining device 200 is subjected to the shade recognition device 20.
  • the microscope control unit 111 acquires the shade data generated by the shade recognition device 20, and then the stained specimen is set in the microscope device 300.
  • the moving unit 202 may be movable to, for example, a position where the light and shade can be recognized by the light and shade recognition device 20.
  • the program of the present embodiment is a program for causing a computer to execute each step of the method of the present invention as a procedure.
  • "procedure” may be read as "processing”.
  • the program of the present embodiment may be recorded on a computer-readable recording medium, for example.
  • the recording medium is, for example, a non-transitory computer-readable storage medium.
  • the recording medium is not particularly limited, and examples thereof include a read-only memory (ROM), a hard disk (HD), and an optical disk.
  • the present invention it is possible to support inspections such as smear inspection.
  • the present invention is useful in estimating dyeing substances.

Abstract

Provided is a microscopic examination assistance device which can estimate a dye substance.　The present invention is a microscopic examination assistance device (100), wherein: an image information acquisition unit (101) acquires a microscopic image of a dye sample of a specimen collected from a subject organism; a recognition estimation unit (102) recognizes a dye substance image in the microscopic image, estimates types of dye substances from the dye substance image, and generates dye substance estimation type information; a counting unit (103) performs counting on the dye substance image and generates dye substance estimation number information; and an information output unit (104) outputs the dye substance estimation type information and the dye substance estimation number information.

Description

顕微鏡検査支援装置、顕微鏡検査支援方法、自動染色装置、自動染色物質推定システム、プログラム、及び記録媒体Microscopic inspection support device, microscopic inspection support method, automatic staining device, automatic staining substance estimation system, program, and recording medium
　本発明は、顕微鏡検査支援装置、顕微鏡検査支援方法、自動染色装置、自動染色物質推定システム、プログラム、及び記録媒体に関する。 The present invention relates to a microscopic inspection support device, a microscopic inspection support method, an automatic staining device, an automatic staining substance estimation system, a program, and a recording medium.
　感染症治療における抗菌薬の決定には塗抹鏡検検査が有用とされている。例えば、特許文献1には、塗抹鏡検画像を分類し、類似した画像を表示する技術が開示されている。 It is said that smear examination is useful for determining antibacterial drugs in the treatment of infectious diseases. For example, Patent Document 1 discloses a technique for classifying smear microscopic images and displaying similar images.
特開２０１８－５４４７２号公報Japanese Unexamined Patent Publication No. 2018-54472
　しかし、染色物質（例えば、病原体や細胞等）を検出する塗抹鏡検検査等の検査は、複数の工程を含み、臨床検査技師の手技を必要とし、結果が得られるまで時間がかかるという問題がある。そのため、実際の医療現場では、検査の結果が、抗菌薬処方の前に医師に伝わり、処方に反映されることが少ないという問題もある。 However, tests such as smear microscopic examination to detect stained substances (for example, pathogens, cells, etc.) involve a plurality of steps, require the procedure of a clinical laboratory technician, and have a problem that it takes time to obtain results. be. Therefore, in the actual medical field, there is also a problem that the test result is not transmitted to the doctor before prescribing the antibacterial drug and is rarely reflected in the prescription.
　そこで、本発明は、染色物質を推定可能な顕微鏡検査支援装置、顕微鏡検査支援方法、自動染色装置、自動染色物質推定システム、プログラム、及び記録媒体を提供することを目的とする。 Therefore, an object of the present invention is to provide a microscopic inspection support device, a microscopic inspection support method, an automatic staining device, an automatic staining substance estimation system, a program, and a recording medium capable of estimating a staining substance.
　前記目的を達成するために、本発明の顕微鏡検査支援装置は、
画像情報取得部、認識推定部、カウント部、及び、情報出力部を含み、
前記画像情報取得部は、検査対象生物から採取された検体の染色標本の顕微鏡画像を取得し、
前記認識推定部は、前記顕微鏡画像において、染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成し、
前記カウント部は、前記染色物質画像をカウントして染色物質推定個数情報を生成し、
前記情報出力部は、前記染色物質推定種類情報及び前記染色物質推定個数情報を出力する、
装置である。 In order to achieve the above object, the microscopic examination support device of the present invention is used.
Includes image information acquisition unit, recognition estimation unit, count unit, and information output unit.
The image information acquisition unit acquires a microscopic image of a stained specimen of a specimen collected from an organism to be inspected, and obtains a microscope image.
The recognition estimation unit recognizes the stained substance image in the microscope image, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information.
The counting unit counts the image of the dyed substance and generates information on the estimated number of stained substances.
The information output unit outputs the dyeing substance estimated type information and the dyeing substance estimated number information.
It is a device.
本発明の顕微鏡検査支援方法は、
画像情報取得工程、認識推定工程、カウント工程、及び、情報出力工程を含み、
前記画像情報取得工程は、検査対象生物から採取された検体の染色標本の顕微鏡画像を取得し、
前記認識推定工程は、前記顕微鏡画像において、染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成し、
前記カウント工程は、前記染色物質画像をカウントして染色物質推定個数情報を生成し、
前記情報出力工程は、前記染色物質推定種類情報及び前記染色物質推定個数情報を出力する、
、方法である。 The microscopic examination support method of the present invention
Including image information acquisition process, recognition estimation process, counting process, and information output process
In the image information acquisition step, a microscope image of a stained specimen of a specimen collected from an organism to be inspected is acquired.
The recognition estimation step recognizes the stained substance image in the microscope image, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information.
In the counting step, the stained substance images are counted to generate the estimated number of stained substances, and the information is generated.
The information output step outputs the dyeing substance estimated type information and the dyeing substance estimated number information.
, The way.
本発明の自動染色装置は、
保持部、移動部、染色試薬供給部、及び、制御部を含み、
前記保持部は、スライドガラスを保持可能であり、
前記スライドガラスには、検査対象生物から採取された検体が塗抹されており、
前記移動部は、前記保持部に連結して前記保持部を移動可能であり、
前記染色試薬供給部は、複数の試薬滴下部を含み、
複数の前記試薬滴下部は、染色工程に応じて並んで配置され、
複数の前記試薬滴下部の各前記試薬滴下部は、前記染色工程に応じて一種類の試薬を滴下可能であり、
前記保持部は、前記試薬滴下部の下方に配置され、
前記制御部は、前記移動部を制御することにより、前記保持部を、前記染色工程に応じて前記スライドガラスに供給が必要な試薬を滴下可能な前記試薬滴下部の下方に位置するように移動させる、
装置である。 The automatic dyeing apparatus of the present invention
Includes holding section, moving section, staining reagent supply section, and control section.
The holding portion can hold the slide glass and can hold the slide glass.
The slide glass is smeared with a sample collected from the organism to be inspected.
The moving portion can be connected to the holding portion to move the holding portion.
The staining reagent supply unit includes a plurality of reagent dropping units.
The plurality of reagent dropping portions are arranged side by side according to the dyeing step.
Each of the reagent dropping parts of the plurality of reagent dropping parts can drop one kind of reagent according to the dyeing step.
The holding portion is arranged below the reagent dropping portion.
By controlling the moving unit, the control unit moves the holding unit so as to be located below the reagent dropping unit capable of dropping the reagent that needs to be supplied to the slide glass according to the dyeing step. Let,
It is a device.
　本発明によれば、染色物質を推定可能である。このため、例えば、塗抹鏡検検査（塗抹鏡検ともいう）等の検査を支援可能であり、検査の結果をより早く得ることができる。 According to the present invention, the dyeing substance can be estimated. Therefore, for example, it is possible to support an inspection such as a smear inspection (also referred to as a smear inspection), and the result of the inspection can be obtained more quickly.
図１は、実施形態１の顕微鏡検査支援装置の構成の一例を示すブロック図である。FIG. 1 is a block diagram showing an example of the configuration of the microscopic examination support device of the first embodiment. 図２は、実施形態１の顕微鏡検査支援装置のハードウエア構成の一例を示すブロック図である。FIG. 2 is a block diagram showing an example of the hardware configuration of the microscopic examination support device of the first embodiment. 図３は、実施形態１の顕微鏡検査支援方法における処理の一例を示すフローチャートである。FIG. 3 is a flowchart showing an example of processing in the microscopic examination support method of the first embodiment. 図４は、顕微鏡制御部による制御の一例を示す模式図である。FIG. 4 is a schematic diagram showing an example of control by the microscope control unit. 図５は、顕微鏡制御部による制御のその他の例を示す模式図である。FIG. 5 is a schematic diagram showing another example of control by the microscope control unit. 図６は、実施形態２の自動染色装置の構成の一例を示すブロック図である。FIG. 6 is a block diagram showing an example of the configuration of the automatic dyeing apparatus of the second embodiment. 図７は、染色工程中における制御部の処理の一例を示す模式図である。FIG. 7 is a schematic diagram showing an example of processing of the control unit during the dyeing process. 図８は、実施形態３の自動染色物質推定システムの構成の一例を示すブロック図である。FIG. 8 is a block diagram showing an example of the configuration of the automatic staining substance estimation system of the third embodiment. 図９は、スライドガラスが自動染色装置の試薬滴下部の下部から顕微鏡装置の対物レンズの下部へ移動する一例を示す模式図である。FIG. 9 is a schematic view showing an example in which the slide glass moves from the lower part of the reagent dropping portion of the automatic dyeing device to the lower part of the objective lens of the microscope device. 図１０は、スライドガラスが検体固定装置から自動染色装置の試薬滴下部の下部を通過して顕微鏡装置の対物レンズの下部へ移動する一例を示す模式図である。FIG. 10 is a schematic view showing an example in which the slide glass moves from the sample fixing device to the lower part of the objective lens of the microscope device through the lower part of the reagent dropping portion of the automatic staining device. 図１１は、実施形態１において、関連情報取得部を含む顕微鏡検査支援装置の構成の一例を示すブロック図である。FIG. 11 is a block diagram showing an example of the configuration of the microscopic examination support device including the related information acquisition unit in the first embodiment. 図１２は、ディスプレイに表示された情報の一例を示す模式図である。FIG. 12 is a schematic diagram showing an example of information displayed on the display. 図１３は、実施形態３において、濃淡認識装置を含む自動染色物質推定システムの構成の一例を示すブロック図である。FIG. 13 is a block diagram showing an example of the configuration of an automatic dyeing substance estimation system including a shading recognition device in the third embodiment.
　本発明の顕微鏡検査支援装置において、例えば、
前記画像取得部は、前記染色標本の複数の顕微鏡画像を取得し、
前記認識推定部は、複数の前記顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The image acquisition unit acquires a plurality of microscopic images of the stained specimen, and obtains a plurality of microscopic images.
The recognition estimation unit recognizes the stained substance image in the plurality of microscope images, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information. May be good.
　本発明の顕微鏡検査支援装置において、例えば、
前記画像取得部は、前記染色標本を複数の倍率で撮像した前記顕微鏡画像を取得し、
前記認識推定部は、複数の倍率の前記顕微鏡画像の各倍率の顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The image acquisition unit acquires the microscope image obtained by capturing the stained specimen at a plurality of magnifications.
The recognition estimation unit recognizes the stain substance image in the microscope image of each magnification of the microscope image having a plurality of magnifications, estimates the type of the stain substance from the stain substance image, and obtains the stain substance estimation type information. It may be in the form of generating.
　本発明の顕微鏡検査支援装置において、例えば、
前記認識推定部は、推定された染色物質の種類の確率を算出して推定種類確率情報を生成し、
前記情報出力部は、前記推定種類確率情報を前記染色物質推定種類情報と紐づけて出力する、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The recognition estimation unit calculates the probability of the estimated type of the dyeing substance and generates the estimated type probability information.
The information output unit may be in an embodiment in which the estimated type probability information is associated with the dyeing substance estimated type information and output.
　本発明の顕微鏡検査支援装置において、例えば、
前記認識推定部は、前記確率の大きさに応じて、推定された複数の染色物質をリスト化した染色物質リスト情報を生成し、
前記情報出力部は、前記染色物質リスト情報を出力する、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The recognition estimation unit generates dyeing substance list information listing a plurality of estimated dyeing substances according to the magnitude of the probability.
The information output unit may be in the form of outputting the dyeing substance list information.
　本発明の顕微鏡検査支援装置において、例えば、
前記染色物質が、病原体、非病原体、及び前記検査対象生物由来の細胞の少なくとも一つである、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The staining substance may be at least one of a pathogen, a non-pathogen, and cells derived from the organism to be inspected.
　本発明の顕微鏡検査支援装置において、例えば、
前記染色物質として、前記検査対象生物由来の細胞を含む場合、
前記認識推定部は、前記染色物質推定種類情報及び前記染色物質推定個数情報に基づき、Geckler分類情報を生成し、
前記情報出力部は、前記Geckler分類情報を出力する、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
When the staining substance contains cells derived from the organism to be inspected,
The recognition estimation unit generates Geckler classification information based on the staining substance estimation type information and the staining substance estimated number information.
The information output unit may be in the form of outputting the Geckler classification information.
　本発明の顕微鏡検査支援装置は、例えば、
さらに、関連情報取得部を含み、
前記関連情報取得部は、前記染色標本に関する関連情報を取得し、
前記認識推定部は、前記関連情報を参照して前記染色物質推定種類情報を生成する、という態様であってもよい。 The microscopic examination support device of the present invention is, for example,
In addition, including the related information acquisition department,
The related information acquisition unit acquires related information regarding the stained specimen, and obtains the related information.
The recognition estimation unit may be in an embodiment of generating the staining substance estimation type information with reference to the related information.
　本発明の顕微鏡検査支援装置において、例えば、
前記関連情報は、前記検体対象生物に関する情報、前記検体に関する情報、及び、環境に関する情報の少なくとも一つである、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The related information may be at least one of information about the sample target organism, information about the sample, and information about the environment.
　本発明の顕微鏡検査支援装置は、例えば、
さらに、推奨情報生成部を含み、
前記推奨情報部は、前記染色物質推定種類情報に基づき、推奨情報を生成し、
前記情報出力部は、前記推奨情報を出力する、という態様であってもよい。 The microscopic examination support device of the present invention is, for example,
In addition, it includes a recommended information generator.
The recommended information unit generates recommended information based on the stained substance estimated type information.
The information output unit may be in the form of outputting the recommended information.
　本発明の顕微鏡検査支援装置において、例えば、
前記推奨情報は、推奨検査情報、及び、推奨治療情報の少なくとも一方の情報である、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The recommended information may be in the form of at least one of the recommended test information and the recommended treatment information.
　本発明の顕微鏡検査支援装置は、例えば、
さらに、カルテ情報取得部を含み、
前記カルテ情報取得部は、前記検査対象生物のカルテ情報を取得し、
前記推奨情報生成部は、前記カルテ情報に基づき、前記推奨治療情報を生成する、という態様であってもよい。 The microscopic examination support device of the present invention is, for example,
In addition, including the medical record information acquisition department,
The medical record information acquisition unit acquires the medical record information of the organism to be inspected, and obtains the medical record information.
The recommended information generation unit may generate the recommended treatment information based on the medical record information.
　本発明の顕微鏡検査支援装置は、例えば、
カルテ情報取得部を含み、
前記カルテ情報取得部は、前記検査対象生物のカルテ情報を取得し、
前記認識推定部は、前記カルテ情報を用いて、疾患を発症する確率を算出して推定発症確率情報を生成し、
前記情報出力部は、前記推定発症確率情報を前記染色物質推定種類情報と紐づけて出力する、という態様であってもよい。 The microscopic examination support device of the present invention is, for example,
Including medical record information acquisition department
The medical record information acquisition unit acquires the medical record information of the organism to be inspected, and obtains the medical record information.
The recognition estimation unit calculates the probability of developing a disease using the medical record information and generates estimated onset probability information.
The information output unit may be in a mode of outputting the estimated onset probability information in association with the dyeing substance estimated type information.
　本発明の顕微鏡検査支援装置は、例えば、
さらに、感染臓器推定部を含み、
前記感染臓器推定部は、前記認識推定部により認識された前記染色物質画像を用いて、前記検体を採取した臓器を感染臓器と推定して推定感染臓器情報を生成し、
前記情報出力部は、前記推定感染臓器情報を出力する、という態様であってもよい。 The microscopic examination support device of the present invention is, for example,
In addition, including the infected organ estimation department,
Using the stained substance image recognized by the recognition estimation unit, the infected organ estimation unit estimates the organ from which the sample is collected as an infected organ and generates estimated infected organ information.
The information output unit may be in the form of outputting the estimated infected organ information.
　本発明の顕微鏡検査支援装置は、例えば、
さらに、画像切替判断部を含み、
前記画像切替判断部は、前記画像取得部において、前記顕微鏡画像の取得時及び前記顕微鏡画像の非取得時を判断し、
前記認識推定部及び前記カウント部は、前記顕微鏡画像の取得時から前記顕微鏡画像の非取得時に切り替わった後、それぞれ、前記染色物質推定種類情報及び前記染色物質推定個数情報の生成を実施する、という態様であってもよい。 The microscopic examination support device of the present invention is, for example,
In addition, it includes an image switching judgment unit.
The image switching determination unit determines when the microscope image is acquired and when the microscope image is not acquired in the image acquisition unit.
The recognition estimation unit and the counting unit switch from the acquisition of the microscope image to the non-acquisition of the microscope image, and then generate the stained substance estimated type information and the stained substance estimated number information, respectively. It may be an embodiment.
　本発明の顕微鏡検査支援装置は、例えば、
さらに、染色装置制御部、顕微鏡制御部、及び検体固定装置制御部の少なくとも一つを含み、
前記染色装置制御部は、前記検体を自動染色して染色標本を調製する染色装置を制御し、
前記顕微鏡制御部は、前記染色標本の顕微鏡画像を撮像する顕微鏡を制御し、
前記検体固定装置制御部は、スライドガラス上に塗抹された検体に対して固定処理を実施する検体固定装置を制御する、という態様であってもよい。 The microscopic examination support device of the present invention is, for example,
Further, it includes at least one of a staining device control unit, a microscope control unit, and a sample fixing device control unit.
The staining device control unit controls a staining device that automatically stains the sample and prepares the stained sample.
The microscope control unit controls a microscope that captures a microscope image of the stained specimen.
The sample fixing device control unit may be in an embodiment of controlling a sample fixing device that performs a fixing process on a sample smeared on a slide glass.
　本発明の顕微鏡検査支援装置において、例えば、
前記顕微鏡制御部は、前記顕微鏡画像毎に適正画像か否かを判定し、適正画像でないと判定した場合は、スライドガラスの長手方向に保持部を移動し、適正画像であると判定した場合は、スライドガラスの短手方向に保持部を移動するように、前記保持部の移動を制御する、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The microscope control unit determines whether or not the image is appropriate for each microscope image, and if it is determined that the image is not appropriate, the holding unit is moved in the longitudinal direction of the slide glass, and if it is determined that the image is appropriate, the holding unit is moved. , The movement of the holding portion may be controlled so as to move the holding portion in the lateral direction of the slide glass.
　本発明の顕微鏡検査支援装置において、例えば、
前記顕微鏡制御部は、前記スライドガラス全体の濃淡データを取得し、前記濃淡データを解析して予め設定した範囲内の濃さを有する位置を特定し、前記位置から視野探索を開始するように前記顕微鏡を制御する、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The microscope control unit acquires the shading data of the entire slide glass, analyzes the shading data to identify a position having a density within a preset range, and starts the visual field search from the position. It may be an aspect of controlling the microscope.
　本発明の顕微鏡検査支援装置において、例えば、
前記染色装置制御部は、染色工程の一工程である脱色工程における脱色時間を前記検体毎に指定可能であり、指定された前記脱色時間で脱色工程を実施するように染色装置を制御する、という態様であってもよい。 In the microscopic examination support device of the present invention, for example,
The dyeing device control unit can specify the decolorization time in the decolorization step, which is one step of the dyeing step, for each sample, and controls the dyeing device so that the decolorization step is performed at the designated decolorization time. It may be an embodiment.
　本発明の顕微鏡検査支援装置は、例えば、
さらに、優先度設定部を含み、
前記優先度設定部は、前記検体毎に任意の優先度を設定可能であり、
前記染色装置制御部、前記顕微鏡制御部、及び前記検体固定装置制御部の少なくとも一つは、前記優先度の高い順に、前記染色装置、前記顕微鏡、及び検体固定装置の処理が実施されるように制御する、という態様であってもよい。 The microscopic examination support device of the present invention is, for example,
In addition, it includes a priority setting section.
The priority setting unit can set an arbitrary priority for each sample.
At least one of the staining device control unit, the microscope control unit, and the sample fixing device control unit is such that the staining device, the microscope, and the sample fixing device are processed in descending order of priority. It may be an aspect of controlling.
　本発明の顕微鏡検査支援方法において、例えば、
前記画像取得工程は、前記染色標本の複数の顕微鏡画像を取得し、
前記認識推定工程は、複数の前記顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
In the image acquisition step, a plurality of microscopic images of the stained specimen are acquired, and the image acquisition step is performed.
The recognition estimation step is an embodiment in which the stain substance image is recognized in the plurality of microscope images, and the type of the stain substance is estimated from the stain substance image to generate the stain substance estimation type information. May be good.
　本発明の顕微鏡検査支援方法において、例えば、
前記画像取得工程は、前記染色標本を複数の倍率で撮像した前記顕微鏡画像を取得し、
前記認識推定工程は、複数の倍率の前記顕微鏡画像の各倍率の顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
In the image acquisition step, the microscope image obtained by capturing the stained specimen at a plurality of magnifications is acquired.
In the recognition estimation step, the stain substance image is recognized in the microscope image of each magnification of the microscope image having a plurality of magnifications, and the type of the stain substance is estimated from the stain substance image to obtain the stain substance estimation type information. It may be in the form of generating.
　本発明の顕微鏡検査支援方法において、例えば、
前記認識推定工程は、推定された染色物質の種類の確率を算出して推定種類確率情報を生成し、
前記情報出力工程は、前記推定種類確率情報を前記染色物質推定種類情報と紐づけて出力する、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
The recognition estimation step calculates the estimated probability of the type of dyeing substance and generates the estimated type probability information.
The information output step may be in an embodiment in which the estimated type probability information is associated with the dyeing substance estimated type information and output.
　本発明の顕微鏡検査支援方法において、例えば、
前記認識推定工程は、前記確率の大きさに応じて、推定された複数の染色物質をリスト化した染色物質リスト情報を生成し、
前記情報出力工程は、前記染色物質リスト情報を出力する、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
The recognition estimation step generates dyeing substance list information listing a plurality of estimated dyeing substances according to the magnitude of the probability.
The information output step may be in the form of outputting the dyeing substance list information.
　本発明の顕微鏡検査支援方法において、例えば、
前記染色物質が、病原体、非病原体、及び前記検査対象生物由来の細胞の少なくとも一つである、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
The staining substance may be at least one of a pathogen, a non-pathogen, and cells derived from the organism to be inspected.
　本発明の顕微鏡検査支援方法において、例えば、
前記染色物質として、前記検査対象生物由来の細胞を含む場合、
前記認識推定工程は、前記染色物質推定種類情報及び前記染色物質推定個数情報に基づき、Geckler分類情報を生成し、
前記情報出力工程は、前記Geckler分類情報を出力する、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
When the staining substance contains cells derived from the organism to be inspected,
The recognition estimation step generates Geckler classification information based on the stained substance estimated type information and the stained substance estimated number information.
The information output step may be in the form of outputting the Geckler classification information.
　本発明の顕微鏡検査支援方法は、例えば、
さらに、関連情報取得工程を含み、
前記関連情報取得工程は、前記染色標本に関する関連情報を取得し、
前記認識推定工程は、前記関連情報を参照して前記染色物質推定種類情報を生成する、という態様であってもよい。 The microscopic examination support method of the present invention is, for example,
In addition, it includes a related information acquisition process.
The related information acquisition step acquires related information regarding the stained specimen, and obtains the related information.
The recognition estimation step may be in an embodiment of generating the staining substance estimation type information with reference to the related information.
　本発明の顕微鏡検査支援方法において、例えば、
前記関連情報は、前記検体対象生物に関する情報、前記検体に関する情報、及び、環境に関する情報の少なくとも一つである、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
The related information may be at least one of information about the sample target organism, information about the sample, and information about the environment.
　本発明の顕微鏡検査支援方法は、例えば、
さらに、推奨情報生成工程を含み、
前記推奨情報生成工程は、前記染色物質推定種類情報に基づき、推奨情報を生成し、
前記情報出力工程は、前記推奨情報を出力する、という態様であってもよい。 The microscopic examination support method of the present invention is, for example,
In addition, it includes a recommended information generation process.
The recommended information generation step generates recommended information based on the stained substance estimated type information.
The information output step may be in the form of outputting the recommended information.
　本発明の顕微鏡検査支援方法において、例えば、
前記推奨情報は、推奨検査情報、及び、推奨治療情報の少なくとも一方の情報である、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
The recommended information may be in the form of at least one of the recommended test information and the recommended treatment information.
　本発明の顕微鏡検査支援方法は、例えば、
さらに、カルテ情報取得工程を含み、
前記カルテ情報取得工程は、前記検査対象生物のカルテ情報を取得し、
　前記カルテ情報は、前記細胞推定種類情報及び前記細胞推定個数情報を含み、
前記推奨情報生成工程は、前記カルテ情報に基づき、前記推奨情報を生成する、という態様であってもよい。 The microscopic examination support method of the present invention is, for example,
In addition, it includes a medical record information acquisition process.
In the medical record information acquisition step, the medical record information of the organism to be inspected is acquired, and the medical record information is acquired.
The medical record information includes the cell estimation type information and the cell estimation number information.
The recommended information generation step may be in the form of generating the recommended information based on the medical record information.
　本発明の顕微鏡検査支援方法は、例えば、
さらに、カルテ情報取得工程を含み、
前記カルテ情報取得工程は、前記検査対象生物のカルテ情報を取得し、
　前記カルテ情報は、前記細胞推定種類情報及び前記細胞推定個数情報を含み、
前記認識推定工程は、前記カルテ情報を用いて、疾患を発症する確率を算出して推定発症確率情報を生成し、
前記情報出力工程は、前記推定発症確率情報を前記染色物質推定種類情報と紐づけて出力する、という態様であってもよい。 The microscopic examination support method of the present invention is, for example,
In addition, it includes a medical record information acquisition process.
In the medical record information acquisition step, the medical record information of the organism to be inspected is acquired, and the medical record information is acquired.
The medical record information includes the cell estimation type information and the cell estimation number information.
The recognition estimation step uses the medical record information to calculate the probability of developing a disease and generate estimated onset probability information.
The information output step may be in an embodiment in which the estimated onset probability information is associated with the dyeing substance estimated type information and output.
　本発明の顕微鏡検査支援方法は、例えば、
さらに、感染臓器推定工程を含み、
前記感染臓器推定工程は、前記認識推定工程により認識された前記染色物質画像を用いて、前記検体を採取した臓器を感染臓器と推定して推定感染臓器情報を生成し、
前記情報出力工程は、前記推定感染臓器情報を出力する、という態様であってもよい。 The microscopic examination support method of the present invention is, for example,
In addition, it includes an infected organ estimation process.
In the infected organ estimation step, using the stained substance image recognized by the recognition estimation step, the organ from which the sample is collected is estimated as an infected organ to generate estimated infected organ information.
The information output step may be in the form of outputting the estimated infected organ information.
　本発明の顕微鏡検査支援方法は、例えば、
さらに、画像切替判断工程を含み、
前記画像切替判断工程は、前記画像取得工程において、前記顕微鏡画像の取得時及び前記顕微鏡画像の非取得時を判断し、
前記認識推定工程及び前記カウント工程は、前記顕微鏡画像の取得時から顕微鏡画像の非取得時に切り替わった後、それぞれ、前記染色物質推定種類情報及び前記染色物質推定個数情報の生成を実施する、という態様であってもよい。 The microscopic examination support method of the present invention is, for example,
In addition, it includes an image switching judgment process.
In the image switching determination step, in the image acquisition step, it is determined when the microscope image is acquired and when the microscope image is not acquired.
The recognition estimation step and the counting step are switched from the acquisition of the microscope image to the non-acquisition of the microscope image, and then the generation of the staining substance estimation type information and the staining substance estimation number information is performed, respectively. May be.
　本発明の顕微鏡検査支援方法は、例えば、
さらに、染色装置制御工程、顕微鏡制御工程、及び検体固定装置制御工程の少なくとも一つを含み、
前記染色装置制御工程は、前記検体を自動染色して染色標本を調製する染色装置を制御し、
前記顕微鏡制御工程は、前記染色標本の顕微鏡画像を撮像する顕微鏡を制御し、
前記検体固定装置制御工程は、スライドガラス上に塗抹された検体に対して固定処理を実施する検体固定装置を制御する、という態様であってもよい。 The microscopic examination support method of the present invention is, for example,
Further, it comprises at least one of a staining device control step, a microscope control step, and a sample fixation device control step.
The staining device control step controls a staining device that automatically stains the sample to prepare a stained sample.
The microscope control step controls a microscope that captures a microscopic image of the stained specimen.
The sample fixing device control step may be an embodiment in which the sample fixing device that performs the fixing process on the sample smeared on the slide glass is controlled.
　本発明の顕微鏡検査支援方法において、例えば、
前記顕微鏡制御工程は、前記顕微鏡画像毎に適正画像か否かを判定し、適正画像でないと判定した場合は、スライドガラスの長手方向に保持部を移動し、適正画像であると判定した場合は、スライドガラスの短手方向に保持部を移動するように、前記保持部の移動を制御する、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
The microscope control step determines whether or not the image is appropriate for each microscope image, and if it is determined that the image is not appropriate, the holding portion is moved in the longitudinal direction of the slide glass, and if it is determined that the image is appropriate. , The movement of the holding portion may be controlled so as to move the holding portion in the lateral direction of the slide glass.
　本発明の顕微鏡検査支援方法において、例えば、
前記顕微鏡制御工程は、前記スライドガラス全体の濃淡データを取得し、前記濃淡データを解析して予め設定した範囲内の濃さを有する位置を特定し、前記位置から視野探索を開始するように前記顕微鏡を制御する、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
In the microscope control step, the shading data of the entire slide glass is acquired, the shading data is analyzed to identify a position having a density within a preset range, and the visual field search is started from the position. It may be an aspect of controlling the microscope.
　本発明の顕微鏡検査支援方法において、例えば、
前記染色装置制御工程は、染色工程の一工程である脱色工程における脱色時間を前記検体毎に指定可能であり、指定された前記脱色時間で脱色工程を実施するように染色装置を制御する、という態様であってもよい。 In the microscopic examination support method of the present invention, for example,
In the dyeing device control step, the decolorization time in the decolorization step, which is one step of the dyeing step, can be specified for each sample, and the dyeing device is controlled so that the decolorization step is performed at the designated decolorization time. It may be an embodiment.
　本発明の顕微鏡検査支援方法は、例えば、
さらに、優先度設定工程を含み、
前記優先度設定工程は、前記検体毎に任意の優先度を設定可能であり、
前記染色装置制御工程、前記顕微鏡制御工程、及び前記検体固定装置制御工程の少なくとも一つは、前記優先度の高い順に、前記染色装置、前記顕微鏡、及び検体固定装置の処理が実施されるように制御する、という態様であってもよい。 The microscopic examination support method of the present invention is, for example,
In addition, it includes a priority setting process.
In the priority setting step, any priority can be set for each sample.
At least one of the staining device control step, the microscope control step, and the sample fixing device control step is such that the staining device, the microscope, and the sample fixing device are processed in descending order of priority. It may be an aspect of controlling.
　本発明のプログラムは、本発明の方法の各工程を、手順として、コンピュータに実行させるためのプログラムである。 The program of the present invention is a program for causing a computer to execute each step of the method of the present invention as a procedure.
　本発明の記録媒体は、本発明のプログラムを記録しているコンピュータ読み取り可能な記録媒体である。 The recording medium of the present invention is a computer-readable recording medium on which the program of the present invention is recorded.
　本発明の自動染色装置において、例えば、
前記制御部は、前記試薬滴下部により脱色液が前記スライドガラスに滴下された後に、前記移動部を制御することにより、前記スライドガラスの長手方向及び短手方向の少なくとも一方を軸として、前記スライドガラスが傾くように前記保持部を駆動させる、という態様であってもよい。 In the automatic dyeing apparatus of the present invention, for example,
The control unit controls the moving unit after the decolorizing liquid is dropped onto the slide glass by the reagent dropping unit, so that the slide is centered on at least one of the longitudinal direction and the lateral direction of the slide glass. The holding portion may be driven so that the glass is tilted.
　本発明の自動染色装置において、例えば、
前記制御部は、前記脱色液の滴下前の前記スライドガラスの保持状態を基準としたとき、前記スライドガラスの長手方向及び短手方向の少なくとも一方を軸として、前記軸ではない短手方向及び長手方向の前記スライドガラスの各端部の傾きが前記基準から予め規定した度合いになるように前記保持部を時計回り及び反時計回りの少なくとも一方に駆動させる、という態様であってもよい。 In the automatic dyeing apparatus of the present invention, for example,
When the holding state of the slide glass before dropping the decolorizing liquid is used as a reference, the control unit has at least one of the longitudinal direction and the lateral direction of the slide glass as an axis, and the lateral direction and the longitudinal direction other than the axis. The holding portion may be driven in at least one of clockwise and counterclockwise so that the inclination of each end portion of the slide glass in the direction becomes a degree predetermined from the reference.
　本発明の自動染色物質推定システムは、自動染色装置、顕微鏡装置、及び、顕微鏡検査支援装置を含み、前記顕微鏡検査支援装置は、本発明の顕微鏡検査支援装置である。 The automatic staining substance estimation system of the present invention includes an automatic dyeing device, a microscopic device, and a microscopic inspection support device, and the microscopic inspection support device is the microscopic inspection support device of the present invention.
　本発明の自動染色物質推定システムにおいて、例えば、
前記自動染色装置は、本発明の自動染色装置である、という態様であってもよい。 In the automated staining substance estimation system of the present invention, for example,
The automatic dyeing apparatus may be an embodiment of the automatic dyeing apparatus of the present invention.
　本発明の自動染色物質推定システムにおいて、例えば、
前記顕微鏡検査支援装置は、表示部を含み、
前記表示部は、前記情報出力部が出力する情報を表示可能である、という態様であってもよい。 In the automated staining substance estimation system of the present invention, for example,
The microscopic examination support device includes a display unit and includes a display unit.
The display unit may be in an embodiment in which the information output by the information output unit can be displayed.
　本発明の自動染色物質推定システムにおいて、例えば、
前記表示部は、同一の視野に対して異なる焦点で撮像された顕微鏡画像を表示可能である、という態様であってもよい。 In the automated staining substance estimation system of the present invention, for example,
The display unit may be capable of displaying microscope images captured at different focal points for the same field of view.
　本発明の自動染色物質推定システムは、例えば、
さらに、ユーザ端末を含み、
前記ユーザ端末は、前記情報出力部が出力する情報を表示可能であり、
他のユーザ端末と共有可能な状況下にある前記情報出力部が出力する情報に対して、任意の情報を追記可能である、という態様であってもよい。 The automated stain estimation system of the present invention is, for example,
In addition, including user terminals,
The user terminal can display the information output by the information output unit.
Arbitrary information may be added to the information output by the information output unit in a situation where it can be shared with other user terminals.
　本発明の自動染色物質推定システムは、例えば、
さらに、検体固定装置を含む、という態様であってもよい。 The automated stain estimation system of the present invention is, for example,
Further, the embodiment may include a sample fixing device.
　本発明の自動染色物質推定システムは、例えば、
前記顕微鏡検査支援装置において、
前記情報出力部は、出力する情報に応じて、通報情報も出力する、という態様であってもよい。 The automated stain estimation system of the present invention is, for example,
In the microscopic examination support device
The information output unit may also output report information according to the information to be output.
　本発明において、「染色物質」は、染色処理によって染色された物質である。具体的には、例えば、病原体、非病原体（例えば、常在菌等）、検査対象生物由来の細胞、検査対象生物由来の物質（例えば、フィブリン、結晶等）等が挙げられるが、本発明はこれらに限定されるものではない。前記病原体は、病原性を示す物質であり、例えば、原生動物、細菌、ウイルス、真菌等の生物がある。前記非病原体は、病原性を示さない物質であり、例えば、前記病原体の例示を援用可能である。前記染色処理は、特に制限されない。前記染色処理としては、例えば、グラム染色、チールニールゼン染色、墨汁染色、ギムザ染色、グロコット染色等の公知の染色処理が挙げられる。前記染色処理によって、後述の染色標本が作製される。 In the present invention, the "dyeing substance" is a substance dyed by a dyeing treatment. Specific examples thereof include pathogens, non-pathogens (for example, indigenous bacteria, etc.), cells derived from the organism to be inspected, substances derived from the organism to be inspected (for example, fibrin, crystals, etc.), and the like. It is not limited to these. The pathogen is a substance exhibiting pathogenicity, and includes, for example, organisms such as protozoa, bacteria, viruses, and fungi. The non-pathogenic substance is a substance that does not show pathogenicity, and for example, an example of the pathogen can be incorporated. The dyeing process is not particularly limited. Examples of the dyeing treatment include known dyeing treatments such as Gram stain, Thirneilzen stain, ink stain, Giemsa stain, and Grocott stain. By the staining treatment, a stained specimen described later is prepared.
　次に、本発明の実施形態について図を用いて説明する。本発明は、以下の実施形態には限定されない。以下の各図において、同一部分には、同一符号を付している。また、各実施形態の説明は、特に言及がない限り、互いの説明を援用でき、各実施形態の構成は、特に言及がない限り、組合せ可能である。 Next, an embodiment of the present invention will be described with reference to the drawings. The present invention is not limited to the following embodiments. In each of the following figures, the same parts are designated by the same reference numerals. Further, the explanations of the respective embodiments can be referred to each other unless otherwise specified, and the configurations of the respective embodiments can be combined unless otherwise specified.
［実施形態１］
　図１は、本実施形態の顕微鏡検査支援装置１００の構成の一例を示すブロック図である。図１に示すように、本装置１００は、画像情報取得部１０１、認識推定部１０２、カウント部１０３、及び、情報出力部１０４を含む。また、本装置１００は、任意の構成として、さらに、関連情報取得部１０５、推奨情報生成部１０６、カルテ情報取得部１０７、感染臓器推定部１０８、画像切替判断部１０９、染色装置制御部１１０、顕微鏡制御部１１１、優先度設定部１１２、検体固定装置制御部１１３、表示部１１４等を含んでもよい。画像情報取得部１０１、認識推定部１０２、カウント部１０３、情報出力部１０４、関連情報取得部１０５、推奨情報生成部１０６、カルテ情報取得部１０７、感染臓器推定部１０８、及び、画像切替判断部１０９は、例えば、検査支援処理部１００Ａともいえる。前記各部は、例えば、内部バスにより相互に接続されている。 [Embodiment 1]
FIG. 1 is a block diagram showing an example of the configuration of the microscopic examination support device 100 of the present embodiment. As shown in FIG. 1, the present apparatus 100 includes an image information acquisition unit 101, a recognition estimation unit 102, a counting unit 103, and an information output unit 104. Further, the apparatus 100 has an arbitrary configuration, further, a related information acquisition unit 105, a recommended information generation unit 106, a chart information acquisition unit 107, an infected organ estimation unit 108, an image switching determination unit 109, a staining device control unit 110, and the like. The microscope control unit 111, the priority setting unit 112, the sample fixing device control unit 113, the display unit 114, and the like may be included. Image information acquisition unit 101, recognition estimation unit 102, counting unit 103, information output unit 104, related information acquisition unit 105, recommended information generation unit 106, chart information acquisition unit 107, infected organ estimation unit 108, and image switching determination unit. Reference numeral 109 can be said to be, for example, the inspection support processing unit 100A. The respective parts are connected to each other by, for example, an internal bus.
　本装置１００は、例えば、前記各部を含む１つの装置でもよいし、前記各部が、通信回線網を介して接続可能な装置でもよい。また、本装置１００は、前記通信回線網を介して、後述する外部装置と接続可能である。前記通信回線網は、特に制限されず、公知のネットワークを使用でき、例えば、有線でも無線でもよい。前記通信回線網は、例えば、インターネット回線、ＷＷＷ（Ｗｏｒｌｄ　Ｗｉｄｅ　Ｗｅｂ）、電話回線、ＬＡＮ（Ｌｏｃａｌ　Ａｒｅａ　Ｎｅｔｗｏｒｋ）、ＳＡＮ（Ｓｔｏｒａｇｅ　Ａｒｅａ　Ｎｅｔｗｏｒｋ）、ＤＴＮ（Ｄｅｌａｙ　Ｔｏｌｅｒａｎｔ　Ｎｅｔｗｏｒｋｉｎｇ）、ＬＰＷＡ（Ｌｏｗ　Ｐｏｗｅｒ　Ｗｉｄｅ　Ａｒｅａ）、Ｌ５Ｇ（ローカル５Ｇ）、等があげられる。無線通信としては、例えば、Ｗｉ－Ｆｉ（登録商標）、Ｂｌｕｅｔｏｏｔｈ（登録商標）、ローカル５Ｇ、ＬＰＷＡ等が挙げられる。前記無線通信としては、各装置が直接通信する形態（Ａｄ　Ｈｏｃ通信）、インフラストラクチャ（infrastructure通信）、アクセスポイントを介した間接通信等であってもよい。本装置１００は、例えば、システムとしてサーバに組み込まれていてもよい。また、本装置１００は、例えば、本発明のプログラムがインストールされたパーソナルコンピュータ（ＰＣ、例えば、デスクトップ型、ノート型）、スマートフォン、タブレット端末、ウエアラブル端末等であってもよい。さらに、本装置１００の各部の全部又は一部が、クラウド上で実現されてもよい。具体的に、本装置１００は、例えば、前記各部のうち少なくとも一つがサーバ（クラウド）上にあり、その他の前記各部が端末上にあるような、クラウドコンピューティングやエッジコンピューティング等の形態であってもよい。 The device 100 may be, for example, one device including the above-mentioned parts, or may be a device in which the above-mentioned parts can be connected via a communication network. Further, the present device 100 can be connected to an external device described later via the communication network. The communication network is not particularly limited, and a known network can be used, and may be wired or wireless, for example. The communication line network includes, for example, an internet line, WWW (World Wide Web), a telephone line, a LAN (Local Area Network), a SAN (Storage Area Network), a DTN (Delay Orient Network), and an LPWA (L). L5G (local 5G), etc. can be mentioned. Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), local 5G, LPWA and the like. The wireless communication may be a form in which each device directly communicates (Ad Hoc communication), an infrastructure (infrastructure communication), an indirect communication via an access point, or the like. The apparatus 100 may be incorporated in the server as a system, for example. Further, the apparatus 100 may be, for example, a personal computer (PC, for example, a desktop type, a notebook type), a smartphone, a tablet terminal, a wearable terminal, or the like in which the program of the present invention is installed. Further, all or a part of each part of the apparatus 100 may be realized on the cloud. Specifically, the present device 100 is in the form of cloud computing, edge computing, or the like, for example, such that at least one of the above parts is on a server (cloud) and the other parts are on a terminal. You may.
　図２に、本装置１００のハードウエア構成のブロック図を例示する。本装置１００は、例えば、中央処理装置（ＣＰＵ、ＧＰＵ等）１、メモリ２、バス３、記憶装置４、入力装置５、出力装置６、及び通信デバイス７等を含んでもよい。なお、これらは例示であって、本装置１００のハードウエア構成は、前記各部の処理を実行可能であれば、これに限定されない。また、本装置１００に含まれる中央処理装置１等の数も図２の例示に限定されるものではなく、例えば、複数の中央処理装置１が本装置１００に含まれていてもよい。本装置１００のハードウエア構成の各部は、それぞれのインタフェース（Ｉ／Ｆ）により、バス３を介して相互に接続されている。 FIG. 2 illustrates a block diagram of the hardware configuration of the present device 100. The apparatus 100 may include, for example, a central processing unit (CPU, GPU, etc.) 1, a memory 2, a bus 3, a storage device 4, an input device 5, an output device 6, a communication device 7, and the like. It should be noted that these are examples, and the hardware configuration of the present device 100 is not limited to this as long as the processing of each part can be executed. Further, the number of the central processing unit 1 and the like included in the present apparatus 100 is not limited to the example of FIG. 2, and for example, a plurality of central processing units 1 may be included in the present apparatus 100. Each part of the hardware configuration of the present apparatus 100 is connected to each other via the bus 3 by each interface (I / F).
　中央処理装置１は、本装置１００の全体の制御を担う。本装置１００において、中央処理装置１により、例えば、本発明のプログラムやその他のプログラムが実行され、また、各種情報の読み込みや書き込みが行われる。そして、中央処理装置１により、本装置１００の各部の処理が実行され得る。 The central processing unit 1 is responsible for overall control of the device 100. In the present device 100, for example, the program of the present invention and other programs are executed by the central processing unit 1, and various information is read and written. Then, the central processing unit 1 can execute the processing of each part of the apparatus 100.
　バス３は、例えば、外部装置とも接続できる。前記外部装置は、例えば、外部記憶装置（外部データベース等）、外部入力装置、外部出力装置、等があげられる。本装置１００は、例えば、バス３に接続された通信デバイス７により、外部ネットワーク（前記通信回線網）に接続でき、外部ネットワークを介して、他の装置と接続することもできる。 Bus 3 can also be connected to, for example, an external device. Examples of the external device include an external storage device (external database, etc.), an external input device, an external output device, and the like. The device 100 can be connected to an external network (the communication network) by, for example, a communication device 7 connected to the bus 3, and can also be connected to another device via the external network.
　メモリ２は、例えば、メインメモリ（主記憶装置）が挙げられる。中央処理装置１が処理を行う際には、例えば、後述する記憶装置４に記憶されている本発明のプログラム等の種々の動作プログラムを、メモリ２が読み込み、中央処理装置１は、メモリ２からデータを受け取って、プログラムを実行する。前記メインメモリは、例えば、ＲＡＭ（ランダムアクセスメモリ）である。また、メモリ２は、例えば、ＲＯＭ（読み出し専用メモリ）であってもよい。 The memory 2 may be, for example, a main memory (main storage device). When the central processing unit 1 performs processing, the memory 2 reads various operation programs such as the program of the present invention stored in the storage device 4 described later, and the central processing unit 1 reads the various operation programs from the memory 2. Receive the data and run the program. The main memory is, for example, a RAM (random access memory). Further, the memory 2 may be, for example, a ROM (read-only memory).
　記憶装置４は、例えば、前記メインメモリ（主記憶装置）に対して、いわゆる補助記憶装置ともいう。前述のように、記憶装置４には、本発明のプログラムを含む動作プログラムが格納されている。記憶装置４は、例えば、記録媒体と、記録媒体に読み書きするドライブとの組合せであってもよい。前記記録媒体は、特に制限されず、例えば、内蔵型でも外付け型でもよく、ＨＤ（ハードディスク）、ＣＤ－ＲＯＭ、ＣＤ－Ｒ、ＣＤ－ＲＷ、ＭＯ、ＤＶＤ、フラッシュメモリー、メモリーカード等が挙げられる。記憶装置１０４は、例えば、記録媒体とドライブとが一体化されたハードディスクドライブ（ＨＤＤ）、及びソリッドステートドライブ（ＳＳＤ）であってもよい。 The storage device 4 is also referred to as a so-called auxiliary storage device with respect to the main memory (main storage device), for example. As described above, the storage device 4 stores an operation program including the program of the present invention. The storage device 4 may be, for example, a combination of a recording medium and a drive for reading and writing to the recording medium. The recording medium is not particularly limited, and may be an internal type or an external type, and examples thereof include HD (hard disk), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, and memory card. Be done. The storage device 104 may be, for example, a hard disk drive (HDD) in which a recording medium and a drive are integrated, and a solid state drive (SSD).
　本装置１００において、メモリ２及び記憶装置４は、ログ情報、外部データベース（図示せず）や外部の装置から取得した情報、本装置１００の各処理によって生じた情報、本装置１００が各処理を実行する際に用いる情報等の種々の情報を記憶することも可能である。なお、少なくとも一部の情報は、例えば、メモリ２及び記憶装置４以外の外部サーバに記憶されていてもよいし、複数の端末にブロックチェーン技術等を用いて分散して記憶されていてもよい。 In the device 100, the memory 2 and the storage device 4 perform log information, information acquired from an external database (not shown) or an external device, information generated by each process of the device 100, and each process of the device 100. It is also possible to store various information such as information used at the time of execution. It should be noted that at least a part of the information may be stored in an external server other than the memory 2 and the storage device 4, or may be distributed and stored in a plurality of terminals by using blockchain technology or the like. ..
　本装置１００は、例えば、さらに、入力装置５、及び出力装置６を含んでもよい。入力装置５は、例えば、文字、数字、画面上に表示された物の位置、画像、音等を入力する装置であり、具体的には、デジタイザ（タッチパネル等）、キーボード、マウス、スキャナ、撮像装置、マイク、センサ等が挙げられる。出力装置６は、例えば、表示装置（ＬＥＤディスプレイ、液晶ディスプレイ）、プリンター、スピーカー等が挙げられる。表示部１１４は、例えば、出力装置６の表示装置を用いて各種情報を表示してもよい。 The device 100 may further include, for example, an input device 5 and an output device 6. The input device 5 is, for example, a device for inputting characters, numbers, the position of an object displayed on the screen, an image, a sound, and the like, and specifically, a digitizer (touch panel, etc.), a keyboard, a mouse, a scanner, and an image pickup. Devices, microphones, sensors and the like can be mentioned. Examples of the output device 6 include a display device (LED display, liquid crystal display), a printer, a speaker, and the like. The display unit 114 may display various information using, for example, the display device of the output device 6.
　本装置１００は、例えば、顕微鏡が撮像した顕微鏡画像を用いた検査に適用可能である。前記検査は、特に制限されず、例えば、塗抹鏡検検査（グラム染色、チールニールゼン染色、真菌染色、ギムザ染色等の染色に関する検査）、病理標本検査等である。 The present device 100 can be applied to, for example, an inspection using a microscope image taken by a microscope. The examination is not particularly limited, and is, for example, a smear inspection (inspection relating to staining such as Gram stain, Thirneilzen staining, fungal staining, Giemsa staining, etc.), pathological specimen inspection, and the like.
　つぎに、本実施形態の顕微鏡検査支援方法の一例を、図３のフローチャートに基づき説明する。本実施形態の顕微鏡検査支援方法は、例えば、図１の顕微鏡検査支援装置１００を用いて、次のように実施する。なお、本実施形態の顕微鏡検査支援方法は、図１の顕微鏡検査支援装置１００の使用には限定されない。 Next, an example of the microscopic examination support method of the present embodiment will be described based on the flowchart of FIG. The microscopic examination support method of the present embodiment is carried out as follows, for example, by using the microscopic examination support device 100 of FIG. The microscopic examination support method of the present embodiment is not limited to the use of the microscopic examination support device 100 of FIG.
　以下において、前記画像情報取得工程は、例えば、画像情報取得部１０１により実行でき、前記認識推定工程は、例えば、認識推定部１０２により実行でき、前記カウント工程は、例えば、カウント部１０３により実行でき、前記情報出力工程は、例えば、情報出力部１０４により実行でき、前記関連情報取得工程は、例えば、関連情報取得部１０５により実行でき、前記推奨情報生成工程は、例えば、推奨情報生成部１０６により実行でき、前記カルテ情報取得工程は、例えば、カルテ情報取得部１０７により実行でき、前記感染臓器推定工程は、例えば、感染臓器推定部１０８により実行でき、前記画像切替判断工程は、例えば、画像切替判断部１０９により実行でき、前記染色装置制御工程は、例えば、染色装置制御部１１０により実行でき、前記顕微鏡制御工程は、例えば、顕微鏡制御部１１１により実行でき、前記優先度設定工程は、例えば、優先度設定部１１２により実行でき、前記検体固定装置制御工程は、例えば、検体固定装置制御部１１３により実行できるものとする。 In the following, the image information acquisition step can be executed by, for example, the image information acquisition unit 101, the recognition estimation step can be executed by, for example, the recognition estimation unit 102, and the counting process can be executed by, for example, the counting unit 103. The information output step can be executed by, for example, the information output unit 104, the related information acquisition step can be executed by, for example, the related information acquisition unit 105, and the recommended information generation step can be executed by, for example, the recommended information generation unit 106. The chart information acquisition step can be executed, for example, by the chart information acquisition unit 107, the infected organ estimation step can be executed by, for example, the infected organ estimation unit 108, and the image switching determination step can be executed, for example, by image switching. It can be executed by the determination unit 109, the staining device control step can be executed by, for example, the staining device control unit 110, the microscope control step can be executed by, for example, the microscope control unit 111, and the priority setting step can be executed, for example, by the microscope control unit 111. It can be executed by the priority setting unit 112, and the sample fixing device control step can be executed by, for example, the sample fixing device control unit 113.
　まず、画像情報取得部１０１により、検査対象生物から採取された検体の染色標本の顕微鏡画像を取得する（Ｓ１０１）。前記検査対象生物は、特に制限されず、例えば、ヒトでもよいし、ヒト以外の生物であってもよい。前記顕微鏡画像は、顕微鏡により撮像された画像をいう。 First, the image information acquisition unit 101 acquires a microscopic image of a stained specimen of a specimen collected from an organism to be inspected (S101). The organism to be inspected is not particularly limited, and may be, for example, a human or a non-human organism. The microscope image refers to an image captured by a microscope.
　次に、認識推定部１０２により、前記顕微鏡画像において、染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する（Ｓ１０２Ａ）。前記染色物質画像とは、染色物質が移っている画像をいう。すなわち、認識推定部１０２は、前記顕微鏡画像内の染色物質を認識するともいえる。認識推定部１０２は、例えば、複数の前記染色物質の種類を推定可能であってもよい。この場合、前記染色物質推定種類情報は、例えば、複数の前記染色物質の種類を示すものであってもよい。 Next, the recognition estimation unit 102 recognizes the stained substance image in the microscope image, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information (S102A). The dyed substance image means an image to which the dyed substance is transferred. That is, it can be said that the recognition estimation unit 102 recognizes the staining substance in the microscope image. The recognition estimation unit 102 may be able to estimate the types of the plurality of dyeing substances, for example. In this case, the dyeing substance estimation type information may indicate, for example, a plurality of types of the dyeing substance.
　認識推定部１０２は、例えば、前記推定において、グラム陽性レンサ球菌、グラム陰性短桿菌、酵母状真菌等のように形態的特徴を推定してもよいし、Enterobacteriaceae、Pseudomonas、Streptococcus等のように生物分類における科名及び属名等で推定してもよいし、Streptococcus agalactiae、Escherichia coli、Pseudomonas aeruginosa等のように生物分類における種名で推定してもよい。 In the estimation, the recognition estimation unit 102 may estimate morphological characteristics such as gram-positive streptococcus, gram-negative streptococcus, and yeast-like fungus, or organisms such as Enterobacteriaceae , Pseudomonas , and Streptococcus . It may be estimated by the family name and genus name in the classification, or by the species name in the biological classification such as Streptococcus agalactiae , Escherichia coli , Pseudomonas aeruginosa and the like.
　次に、カウント部１０３により、前記染色物質画像をカウントして染色物質推定個数情報を生成する（Ｓ１０３）。より具体的には、前記染色物質画像内において認識推定部１０２により認識した前記染色物質の数をカウントする。前記染色物質推定個数情報は、前記染色物質の数を示す情報である。前記カウントは、認識推定部１０２により推定された前記染色物質の種類毎に行ってもよい。 Next, the counting unit 103 counts the stained substance images and generates information on the estimated number of stained substances (S103). More specifically, the number of the dyed substances recognized by the recognition estimation unit 102 in the stained substance image is counted. The information on the estimated number of dyed substances is information indicating the number of the dyed substances. The counting may be performed for each type of the dyeing substance estimated by the recognition estimation unit 102.
　そして、情報出力部１０４により、前記染色物質推定種類情報及び前記染色物質推定個数情報を出力して（Ｓ１０４）、終了する（ＥＮＤ）。情報出力部１０４による出力の手法は、特に制限されず、例えば、出力装置６を用いて出力してもよいし、通信デバイス７を用いて外部の装置に出力してもよい。 Then, the information output unit 104 outputs the stain substance estimated type information and the stain substance estimated number information (S104), and ends (END). The method of output by the information output unit 104 is not particularly limited, and for example, the output device 6 may be used for output, or the communication device 7 may be used for output to an external device.
　本実施形態によれば、前記染色物質の種類を自動で推定可能であり、また、前記カウントも自動化できる。このため、本実施形態によれば、塗抹鏡検検査等の検査を支援可能である。具体的に、前記自動化により、検査にかかる時間及び人的コストを削減可能である。また、検査技師の負担を軽減することもできる。さらに、本実施形態によれば、前記染色物質推定種類情報及び前記染色物質推定個数情報を出力することで、医療従事者にこれらの情報を提示可能である。 According to this embodiment, the type of the dyeing substance can be automatically estimated, and the count can also be automated. Therefore, according to the present embodiment, it is possible to support an inspection such as a smear microscopic examination. Specifically, the automation can reduce the time required for inspection and the human cost. In addition, the burden on the inspection engineer can be reduced. Further, according to the present embodiment, it is possible to present the information to the medical staff by outputting the information on the estimated type of the dyeing substance and the information on the estimated number of the dyeing substances.
　画像情報取得部１０１は、例えば、前記工程Ｓ１０１において、前記染色標本の複数の顕微鏡画像を取得してもよい。この場合、認識推定部１０２は、例えば、前記工程Ｓ１０２Ａにおいて、複数の前記顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成してもよい。認識推定部１０２は、例えば、前記顕微鏡画像毎に前記染色物質推定種類情報を生成してもよいし、１つの前記染色標本に対して１つの前記染色物質推定種類情報（複数の顕微鏡画像に対する前記推定の結果をまとめた染色物質推定種類情報）を生成してもよい。前記複数の顕微鏡画像とは、それぞれ異なった視野で撮像された画像でもよいし、１つの視野に対して異なる焦点で撮像された画像であってもよい。このように、複数の顕微鏡画像を取得することで、認識推定部１０２の処理、ひいては、検査の精度を向上可能である。 The image information acquisition unit 101 may acquire a plurality of microscope images of the stained specimen in the step S101, for example. In this case, for example, in the step S102A, the recognition estimation unit 102 recognizes the stain image in the plurality of microscope images, estimates the type of the stain substance from the stain image, and estimates the stain substance type. Information may be generated. For example, the recognition estimation unit 102 may generate the stain substance estimation type information for each of the microscope images, or the stain substance estimation type information (the said for a plurality of microscope images) for one stain sample. Staining substance estimation type information) summarizing the estimation results may be generated. The plurality of microscope images may be images captured in different fields of view, or may be images captured at different focal points for one field of view. By acquiring a plurality of microscope images in this way, it is possible to improve the accuracy of the processing of the recognition estimation unit 102 and, by extension, the inspection.
　画像情報取得部１０１は、例えば、前記工程Ｓ１０１において、前記染色標本を複数の倍率で撮像した前記顕微鏡画像を取得してもよい。この場合、認識推定部１０２は、例えば、前記工程Ｓ１０２Ａにおいて、複数の倍率の前記顕微鏡画像の各倍率の顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成してもよい。認識推定部１０２は、例えば、各倍率の前記顕微鏡画像毎に前記染色物質推定種類情報を生成してもよいし、１つの前記染色標本に対して１つの前記染色物質推定種類情報（各倍率の前記顕微鏡画像に対する前記推定の結果をまとめた染色物質推定種類情報）を生成してもよい。このように、複数の倍率で撮像した前記顕微鏡画像することで、認識推定部１０２の処理、ひいては、検査の精度を向上可能である。 The image information acquisition unit 101 may acquire, for example, the microscope image obtained by capturing the stained specimen at a plurality of magnifications in the step S101. In this case, for example, in the step S102A, the recognition estimation unit 102 recognizes the stain substance image in the microscope image of each magnification of the microscope image having a plurality of magnifications, and the type of the stain substance from the stain substance image. May generate the estimated type information of the staining substance. For example, the recognition estimation unit 102 may generate the stain substance estimation type information for each microscope image of each magnification, or one stain substance estimation type information (of each magnification) for one stain sample. (Staining substance estimation type information) that summarizes the estimation results for the microscope image may be generated. As described above, the accuracy of the processing of the recognition estimation unit 102 and, by extension, the inspection can be improved by taking the microscope image taken at a plurality of magnifications.
　認識推定部１０２は、例えば、前記工程Ｓ１０２Ａにおいて、推定された染色物質の種類の確率を算出して推定種類確率情報を生成してもよい。前記染色物質の種類の確率とは、「前記染色物質がその種類である確からしさ」を意味する。前記確率を算出する手法は、例えば、公知の手法を用いてもよいし、後述する手法を用いてもよい。認識推定部１０２は、例えば、機械学習により、推定された染色物質の種類の確率を算出してもよい。前記推定種類確率情報は、例えば、「Pseudomonas 90%」等のように、前記染色物質の種類と紐づけて前記確率を数値（パーセント等）で表現するものであってもよいし、文字（例えば、「高確率」、「低確率」等）や記号等の数字以外で前記確率を表現するものであってもよい。前記推定種類確率情報が生成された場合、情報出力部１０４は、例えば、前記工程Ｓ１０４において、前記推定種類確率情報を前記染色物質推定種類情報と紐づけて出力してもよい。具体的に、前記染色物質推定種類情報に紐づいた前記推定種類確率情報の一例として、「肺炎球菌　９５％」、「マイコプラズマ　８０％」等のように、染色物質名と確率とを組み合わせた形式があるが、これは例示であって、これに限定されない。このように、前記推定種類確率情報を生成することで、検査をより支援可能であり、前記推定種類確率情報を取得した者（例えば、医療従事者）が前記染色物質の種類及びその確率を容易に把握可能である。 For example, in the step S102A, the recognition estimation unit 102 may calculate the estimated probability of the type of the dyeing substance and generate the estimated type probability information. The probability of the type of the dyeing substance means "the certainty that the dyeing substance is the type". As the method for calculating the probability, for example, a known method may be used, or a method described later may be used. The recognition estimation unit 102 may calculate the estimated probability of the type of dyeing substance by machine learning, for example. The estimated type probability information may be, for example, "Pseudomonas 90%" or the like, and may be associated with the type of the dyeing substance to express the probability numerically (percentage or the like), or may be a character (for example,). , "High probability", "Low probability", etc.) and numbers other than symbols may be used to express the probability. When the estimated type probability information is generated, the information output unit 104 may output the estimated type probability information in association with the stained substance estimated type information in the step S104, for example. Specifically, as an example of the estimated type probability information linked to the estimated type information of the stained substance, a format in which the name of the stained substance and the probability are combined, such as "Streptococcus pneumoniae 95%" and "Mycoplasma 80%". However, this is an example and is not limited to this. In this way, by generating the estimated type probability information, it is possible to further support the inspection, and a person (for example, a medical worker) who has acquired the estimated type probability information can easily determine the type of the dyeing substance and its probability. It is possible to grasp.
　推定された染色物質の種類の確率を算出する手法の一例について説明する。なお、以下の説明は例示であって、前記手法が以下の説明に限定されるものではない。前記確率の算出には、例えば、数値化されている検査情報と、カルテに記載されたテキスト情報とを用いる。前記検査情報には、例えば、炎症の程度を示すＣＲＰ（Ｃ反応性たんぱく質）、白血球数、体温、呼吸機能、尿量、β－Ｄグルカン等の各種検査に関する情報がある。前記テキスト情報には、例えば、咳の有無、呼吸困難感の有無、腰部痛の有無、レントゲンの所見、重症度、感染臓器、薬剤処理機能等に関する情報がある。前記検査情報及び前記テキスト情報は、例えば、後述のカルテ情報取得部１０７により取得してもよい。認識推定部１０２は、例えば、前記検査情報及び前記テキスト情報に含まれる各情報をパラメータとして、前記パラメータの重みを染色物質の種類毎に算出し、前記パラメータの重み用いて特定の計算式により前記確率を算出する。前記特定の計算式は、特に制限されず、任意に設定可能である。認識推定部１０２は、例えば、前記検査情報及び前記テキスト情報以外に、前記染色物質推定種類情報や前記染色物質推定個数情報等の本装置１００により生成された各情報を用いて前記確率を算出してもよい。 An example of a method for calculating the probability of the estimated type of dyeing substance will be explained. The following description is an example, and the method is not limited to the following description. For the calculation of the probability, for example, the digitized inspection information and the text information described in the medical record are used. The test information includes, for example, information on various tests such as CRP (C-reactive protein) indicating the degree of inflammation, white blood cell count, body temperature, respiratory function, urine volume, and β-D glucan. The text information includes, for example, information on the presence / absence of cough, the presence / absence of dyspnea, the presence / absence of lower back pain, X-ray findings, severity, infected organs, drug processing function, and the like. The inspection information and the text information may be acquired by, for example, the medical record information acquisition unit 107 described later. For example, the recognition estimation unit 102 calculates the weight of the parameter for each type of the dyeing substance using the inspection information and each information included in the text information as parameters, and uses the weight of the parameter to calculate the weight according to a specific calculation formula. Calculate the probability. The specific calculation formula is not particularly limited and can be set arbitrarily. The recognition estimation unit 102 calculates the probability by using each information generated by the present apparatus 100 such as the stain substance estimation type information and the stain substance estimated number information, in addition to the inspection information and the text information, for example. You may.
　認識推定部１０２は、例えば、前記工程Ｓ１０２Ａにおいて、推定された染色物質の種類の確率の大きさに応じて、推定された複数の染色物質をリスト化した染色物質リスト情報を生成してもよい。前記染色物質リスト情報が、例えば、前記染色物質推定種類情報に紐づけられた前記推定種類確率情報を兼ねてもよい。前記染色物質リスト情報は、前記確率の大きい順に前記染色物質の種類を並べたものであってもよいし、前記確率の小さい順に前記染色物質の種類を並べたものであってもよい。情報出力部１０４は、例えば、前記工程Ｓ１０４において、前記染色物質リスト情報を出力してもよい。このように、前記染色物質リスト情報を生成することで、検査をより支援可能であり、前記染色物質リスト情報を取得した者（例えば、医療従事者）が前記染色物質の種類及びその確率を容易に把握可能である。 For example, in the step S102A, the recognition estimation unit 102 may generate a dyeing substance list information listing a plurality of estimated dyeing substances according to the magnitude of the probability of the estimated type of the dyeing substance. .. The stain substance list information may also serve as, for example, the estimated type probability information associated with the stain substance estimated type information. The dyeing substance list information may be those in which the types of the dyeing substances are arranged in descending order of the probability, or may be those in which the types of the dyeing substances are arranged in the order of the smaller probability. The information output unit 104 may output the dyeing substance list information in the step S104, for example. In this way, by generating the dyeing substance list information, it is possible to further support the inspection, and a person (for example, a medical worker) who has acquired the dyeing substance list information can easily determine the type of the dyeing substance and its probability. It is possible to grasp.
　前記染色物質は、例えば、病原体、非病原体、及び前記検査対象生物由来の細胞の少なくとも一つである。前記検査対象生物がヒトである場合、前記検査対象生物に由来する細胞は、例えば、喀痰検体における上皮細胞や白血球細胞、貪食をした白血球細胞等である。 The staining substance is, for example, at least one of a pathogen, a non-pathogen, and cells derived from the organism to be inspected. When the test target organism is a human, the cells derived from the test target organism are, for example, epithelial cells and leukocyte cells in a sputum sample, phagocytic leukocyte cells and the like.
　前記染色物質として、前記検査対象生物由来の細胞を含む場合、認識推定部１０２は、例えば、前記工程Ｓ１０３の後において、前記染色物質推定種類情報及び前記染色物質推定個数情報に基づき、Geckler分類情報を生成してもよい。前記Geckler分類情報の生成は、例えば、前記工程Ｓ１０４の前に実行されてもよいし、前記工程Ｓ１０４の後に実行されてもよい。そして、情報出力部１０４は、例えば、前記Geckler分類情報を出力してもよい。ここで、前記Geckler分類情報とは、前記検査対象生物の検体がGeckler分類のどのグループに属するかを示す情報である。つまり、本態様の場合、認識推定部１０２は、少なくとも、前記染色物質画像から白血球と扁平上皮細胞とを推定し、カウント部１３は、少なくとも、前記白血球の数と前記扁平上皮細胞の数とをカウントする。このように、Geckler分類情報を生成することで、前記検体を評価可能である。 When the staining substance includes cells derived from the organism to be inspected, the recognition estimation unit 102, for example, after the step S103, has Geckler classification information based on the staining substance estimation type information and the staining substance estimated number information. May be generated. The generation of the Geckler classification information may be performed, for example, before the step S104 or after the step S104. Then, the information output unit 104 may output, for example, the Geckler classification information. Here, the Geckler classification information is information indicating to which group of the Geckler classification the sample of the organism to be inspected belongs. That is, in the case of this embodiment, the recognition estimation unit 102 estimates at least leukocytes and squamous epithelial cells from the stained substance image, and the counting unit 13 at least determines the number of the leukocytes and the number of the squamous epithelial cells. Count. By generating the Geckler classification information in this way, the sample can be evaluated.
　前述したように、本装置１００は、例えば、さらに、関連情報取得部１０５を含んでもよい。関連情報取得部１０５を含む本装置１００の構成の一例を図１１に示す。関連情報取得部１０５は、例えば、前記工程Ｓ１０２Ａの前に、前記染色標本に関する関連情報を取得する（Ｓ１０５）。前記工程Ｓ１０５は、任意の工程であって、実行されなくともよい。前記関連情報は、例えば、前記検体対象生物に関する情報、前記検体に関する情報、及び、環境に関する情報の少なくとも一つである。より具体的には、例えば、前記検体対象生物（ヒト等）の年齢、疾患名、前記検体対象生物の生体状態、投薬歴、医療機関の所在地や医療機関内のアンチバイオグラム等である。本態様の場合、認識推定部１０２は、例えば、前記工程Ｓ１０２Ａにおいて、前記関連情報を参照して前記染色物質推定種類情報を生成してもよい。一般的に、前記検体対象生物の年齢や、基礎疾患等によって疾患（例えば、肺炎等）の原因となり得る物質（病原体等）が異なる。例として、高齢者の肺炎は、口腔内細菌が原因となることが多い。このように、前記関連情報を加味することで、認識推定部１０２による推定の精度を向上可能である。 As described above, the apparatus 100 may further include, for example, the related information acquisition unit 105. FIG. 11 shows an example of the configuration of the present apparatus 100 including the related information acquisition unit 105. The related information acquisition unit 105 acquires, for example, related information regarding the stained specimen before the step S102A (S105). The step S105 is an arbitrary step and may not be executed. The related information is, for example, at least one of information about the sample target organism, information about the sample, and information about the environment. More specifically, for example, the age of the sample target organism (human or the like), the disease name, the biological state of the sample target organism, the medication history, the location of the medical institution, the antibiogram in the medical institution, and the like. In the case of this embodiment, the recognition estimation unit 102 may generate the dyeing substance estimation type information with reference to the related information in the step S102A, for example. In general, substances (pathogens, etc.) that can cause diseases (for example, pneumonia, etc.) differ depending on the age of the sample target organism, the underlying disease, and the like. As an example, pneumonia in the elderly is often caused by oral bacteria. In this way, by adding the related information, it is possible to improve the accuracy of estimation by the recognition estimation unit 102.
　医療分野において、検査の結果から病原体等の疾患と要因となっている物の種類を絞る必要があった。そこで、特許文献１のように、特定の装置を用いて病原菌の種類の絞り込みを精度高くする取り組みがなされてきた。しかしながら、これまでは形態的特徴のみから分類を試みていたため、治療薬の選択等に決定的な情報を得られるまでの絞り込みには至っていなかった。これに対し、本発明は、前記関連情報を取得することで、より詳細および正確に染色物質を推定可能である。このため、医療従事者は、前記推定の結果（前記染色物質推定種類情報）を治療薬の選択等に有効活用できる。 In the medical field, it was necessary to narrow down the types of diseases and factors such as pathogens from the test results. Therefore, as in Patent Document 1, efforts have been made to improve the accuracy of narrowing down the types of pathogens by using a specific device. However, since we have tried to classify only by morphological characteristics, we have not been able to narrow down until we can obtain definitive information on the selection of therapeutic agents. On the other hand, in the present invention, the dyeing substance can be estimated in more detail and accurately by acquiring the related information. Therefore, the medical staff can effectively utilize the estimation result (the stain substance estimation type information) for the selection of the therapeutic agent and the like.
　前述したように、本装置１００は、例えば、さらに、推奨情報生成部１０６を含んでもよい。推奨情報生成部１０６は、例えば、前記工程Ｓ１０２Ａの後に、前記染色物質推定種類情報に基づき、推奨情報を生成してもよい（Ｓ１０６）。前記工程Ｓ１０６は、任意の工程であって、実行されなくともよい。前記推奨情報は、例えば、推奨検査情報、及び、推奨治療情報の少なくとも一方の情報である。前記推奨検査情報は、例えば、培養をはじめとした菌種を特定するための追加検査等に関する情報である。より具体的には、例えば、喀痰のグラム染色にて真菌のような物体が確認できた時に真菌を選択的に生やす選択培地にて培養することを推奨する推奨検査情報が生成される。前記推奨治療情報は、例えば、処方すべき抗生物質の種類、治療方針等に関する情報である。推奨情報生成部１０６は、例えば、前記関連情報を参照して前記推奨情報を生成してもよい。そして、情報出力部１０４は、例えば、前記推奨情報を出力してもよい（Ｓ１０４）。情報出力部１０４は、例えば、前記推奨検査情報が生成された場合は、前記推奨検査情報が生成されたことを検査技師等の医療従事者に通知してもよい。このように、前記推奨情報を生成することで、検査技師等の医療従事者を支援可能である。特に、前述したように、本発明によれば、より詳細および正確に染色物質を推定可能であるから、前記推奨治療情報も、より詳細且つ正確な内容になり、医療従事者による治療薬の選択や治療方針の決定をより支援することができる。 As described above, the apparatus 100 may further include, for example, the recommended information generation unit 106. The recommended information generation unit 106 may generate recommended information based on the dyeing substance estimation type information, for example, after the step S102A (S106). The step S106 is an arbitrary step and may not be executed. The recommended information is, for example, at least one of recommended test information and recommended treatment information. The recommended test information is, for example, information on additional tests for identifying bacterial species such as culture. More specifically, for example, when a fungal-like object is confirmed by Gram stain of sputum, recommended test information is generated that recommends culturing in a selective medium that selectively grows fungi. The recommended treatment information is, for example, information on the type of antibiotic to be prescribed, the treatment policy, and the like. The recommended information generation unit 106 may generate the recommended information by referring to the related information, for example. Then, the information output unit 104 may output the recommended information, for example (S104). For example, when the recommended test information is generated, the information output unit 104 may notify a medical worker such as a test technician that the recommended test information has been generated. By generating the recommended information in this way, it is possible to support medical professionals such as laboratory technicians. In particular, as described above, according to the present invention, since the staining substance can be estimated in more detail and accurately, the recommended treatment information also has more detailed and accurate contents, and the selection of the therapeutic agent by the medical staff And can more support the decision of treatment policy.
　前述したように、本装置１００は、例えば、さらに、カルテ情報取得部１０７を含んでもよい。カルテ情報取得部１０７は、例えば、後述の工程Ｓ１０２Ｂまたは前記工程Ｓ１０６の前に、前記検査対象生物のカルテ情報を取得する（Ｓ１０７）。前記工程Ｓ１０７は、任意の工程であって、実行されなくともよい。前記カルテ情報は、例えば、前述した前記検査情報及び前記テキスト情報を含んでもよく、より具体的には、検査の結果、体温、白血球数、Ｃ反応性たんぱく質の数値、レントゲンの所見、重症度、感染臓器、薬剤処理機能等の前記検体対象生物の生体に関する情報等がある。前記検査の結果は、例えば、前記染色物質推定種類情報及び前記染色物質推定個数情報であってもよい。カルテ情報取得部１０７は、例えば、前記通信回線網を介して外部の装置から前記カルテ情報を取得してもよいし、入力装置５を介して入力された前記カルテ情報を取得してもよい。前記カルテ情報を取得した場合、推奨情報生成部１０６は、例えば、前記工程Ｓ１０６において、前記カルテ情報に基づき、前記推奨治療情報を生成してもよい。臨床現場では、各種要因を総合的に判断し、感染症を抑えることができ、かつ可能な限り狭域な抗菌薬を選択する必要がある。時には、いくつかの情報なしで判断する必要もある。狭域な抗菌薬が選択されると、薬剤耐性菌の発生や薬価を抑えることが可能になる。本発明は、前記カルテ情報を用いて前記推奨治療情報を生成することで、狭域な抗菌薬の選択等を支援することができ、より適切かつ効果的な治療が可能になる。 As described above, the present device 100 may further include, for example, a medical record information acquisition unit 107. The medical record information acquisition unit 107 acquires, for example, the medical record information of the organism to be inspected before the step S102B or the step S106 described later (S107). The step S107 is an arbitrary step and may not be executed. The chart information may include, for example, the above-mentioned test information and the text information, and more specifically, as a result of the test, body temperature, leukocyte count, C-reactive protein value, X-ray finding, severity, and the like. There is information about the living body of the sample target organism such as an infected organ and a drug processing function. The result of the inspection may be, for example, the dyeing substance estimated type information and the dyeing substance estimated number information. The medical record information acquisition unit 107 may acquire the medical record information from an external device via the communication network, or may acquire the medical record information input via the input device 5. When the medical record information is acquired, the recommended information generation unit 106 may generate the recommended treatment information based on the medical record information, for example, in the step S106. In clinical practice, it is necessary to comprehensively judge various factors and select an antibacterial drug that can suppress infectious diseases and is as narrow as possible. Sometimes it is necessary to make a judgment without some information. When a narrow-range antibacterial drug is selected, it becomes possible to suppress the outbreak of drug-resistant bacteria and the drug price. According to the present invention, by generating the recommended treatment information using the medical record information, it is possible to support the selection of a narrow-range antibacterial drug and the like, and more appropriate and effective treatment becomes possible.
　前記カルテ情報を取得した場合、認識推定部１０２は、例えば、少なくとも前記カルテ情報を用いて、疾患を発症する確率を算出して推定発症確率情報を生成してもよい（Ｓ１０２Ｂ）。認識推定部１０２は、例えば、前記カルテ情報以外に、前記染色物質推定種類情報や前記染色物質推定個数情報等の本装置１００により生成された各情報を用いて前記確率を算出してもよい。前記確率を算出する手法は、例えば、公知の手法を用いてもよいし、後述する手法を用いてもよい。認識推定部１０２は、例えば、機械学習により、疾患を発症する確率を算出してもよい。前記推定発症確率情報は、例えば、前記疾患の種類と紐づけて前記確率を数値（パーセント等）で表現するものであってもよいし、文字（例えば、「高確率」、「低確率」等）や記号等の数字以外で前記確率を表現するものであってもよい。前記推定発症確率情報が生成された場合、情報出力部１０４は、例えば、前記工程Ｓ１０４において、前記推定発症確率情報を前記染色物質推定種類情報と紐づけて出力してもよい。具体的に、前記染色物質推定種類情報に紐づいた前記推定種類確率情報の一例として、「細菌性肺炎　９５％」、「非定型肺炎　８０％」等のように、染色物質名と確率とを組み合わせた形式があるが、これは例示であって、これに限定されない。一般的に、感染症か否かの判断は難しく、熟練の医師でも感染症か他の炎症か判別が難しいことも多い。これに対して、本発明によれば、前記推定発症確率情報と紐づけて推定発症確率情報が出力されるため、例えば、医療従事者を支援可能である。 When the medical record information is acquired, the recognition estimation unit 102 may generate the estimated onset probability information by calculating the probability of developing a disease by using at least the medical record information, for example (S102B). In addition to the chart information, the recognition estimation unit 102 may calculate the probability by using each information generated by the present apparatus 100 such as the dyeing substance estimation type information and the dyeing substance estimated number information. As the method for calculating the probability, for example, a known method may be used, or a method described later may be used. The recognition estimation unit 102 may calculate the probability of developing a disease by machine learning, for example. The estimated onset probability information may be, for example, expressing the probability numerically (percentage or the like) in association with the type of the disease, characters (for example, "high probability", "low probability", etc.). ), Symbols, and other numbers may be used to express the probability. When the estimated onset probability information is generated, the information output unit 104 may output the estimated onset probability information in association with the stained substance estimated type information in, for example, in the step S104. Specifically, as an example of the estimated type probability information linked to the estimated type information of the stained substance, the name and probability of the stained substance such as "bacterial pneumonia 95%" and "atypical pneumonia 80%" are used. There are combined formats, but this is an example and is not limited to this. In general, it is difficult to determine whether it is an infectious disease, and it is often difficult for even a skilled doctor to determine whether it is an infectious disease or other inflammation. On the other hand, according to the present invention, since the estimated onset probability information is output in association with the estimated onset probability information, for example, it is possible to support a medical worker.
　疾患を発症する確率を算出する手法の一例について説明する。なお、以下の説明は例示であって、前記手法が以下の説明に限定されるものではない。前記確率の算出には、例えば、数値化されている検査情報と、カルテに記載されたテキスト情報とを用いる。前記検査情報及び前記テキスト情報は、前述と同様である。認識推定部１０２は、例えば、前記検査情報及び前記テキスト情報に含まれる各情報をパラメータとして、前記パラメータの重みを疾患の種類毎に算出し、前記パラメータの重み用いて特定の計算式により前記確率を算出する。前記特定の計算式は、特に制限されず、任意に設定可能である。 An example of a method for calculating the probability of developing a disease will be explained. The following description is an example, and the method is not limited to the following description. For the calculation of the probability, for example, the digitized inspection information and the text information described in the medical record are used. The inspection information and the text information are the same as described above. The recognition estimation unit 102 calculates the weight of the parameter for each type of disease by using, for example, each information included in the test information and the text information as a parameter, and uses the weight of the parameter to calculate the probability by a specific calculation formula. Is calculated. The specific calculation formula is not particularly limited and can be set arbitrarily.
　前述したように、本装置１００は、例えば、さらに、感染臓器推定部１０８を含んでもよい。感染臓器推定部１０８は、例えば、前記工程Ｓ１０２Ａの後、認識推定部１０２により認識された前記染色物質画像を用いた解析により、前記検体が採取された臓器を感染臓器と推定して推定感染臓器情報を生成してもよい（Ｓ１０８）。また、感染臓器推定部１０８は、例えば、前記染色物質画像を解析することで、前記検体が採取された臓器を推定してもよい。ここで、感染臓器とは、前記染色物質（特に、病原体及び非病原体の少なくとも一方）に感染している臓器をいう。そして、情報出力部１０４は、例えば、前記工程Ｓ１０４において、前記推定感染臓器情報を出力する。このように、本態様によれば、前記染色物質による感染臓器を推定可能であり、疾患の要因の特定を支援可能である。 As described above, the apparatus 100 may further include, for example, an infected organ estimation unit 108. For example, after the step S102A, the infected organ estimation unit 108 estimates that the organ from which the sample is collected is an infected organ by analysis using the staining substance image recognized by the recognition estimation unit 102, and estimates the infected organ. Information may be generated (S108). Further, the infected organ estimation unit 108 may estimate the organ from which the sample was collected, for example, by analyzing the image of the stained substance. Here, the infected organ means an organ infected with the staining substance (particularly, at least one of a pathogen and a non-pathogen). Then, the information output unit 104 outputs, for example, the estimated infected organ information in the step S104. As described above, according to this aspect, it is possible to estimate the infected organ by the staining substance, and it is possible to support the identification of the cause of the disease.
　感染臓器推定部１０８は、例えば、認識推定部１０２により前記染色物質画像から下記（１）及び（２）の少なくとも一方が認識（観察）された場合に、前記検体が採取された臓器を感染臓器と推定してもよい。
（１）前記病原体及び前記非病原体の少なくとも一方と、白血球との双方
（２）前記病原体 For example, when at least one of the following (1) and (2) is recognized (observed) from the stained substance image by the recognition estimation unit 102, the infected organ estimation unit 108 uses the organ from which the sample was collected as an infected organ. May be estimated.
(1) At least one of the pathogen and the non-pathogen, and both leukocytes (2) The pathogen
　つまり、上記（１）であれば、前記非病原体と白血球との双方が認識された場合に、前記非病原体が疾患の要因である可能性が高いと推定されるため、前記検体が採取された臓器が感染臓器と推定される。上記（２）であれば、前記病原体が認識された場合に、前記病原体が疾患の要因である可能性が高いと推定されるため、前記検体が採取された臓器が感染臓器と推定される。一般的に、疾患の要因となるのは前記病原体に限らず、例えば、常在菌が疾患の要因となることもある。これに対して、本態様によれば、常在菌（前記非病原体）が疾患の要因であっても、前記感染臓器を推定可能であり、感染臓器推定部１０８による推定の精度がより向上する。 That is, in the case of (1) above, when both the non-pathogen and the leukocyte are recognized, it is presumed that the non-pathogen is likely to be the cause of the disease, and therefore the sample was collected. The organ is presumed to be an infected organ. In the case of (2) above, when the pathogen is recognized, it is presumed that the pathogen is likely to be the cause of the disease, and therefore the organ from which the sample is collected is presumed to be an infected organ. In general, the cause of the disease is not limited to the pathogen, and for example, indigenous bacteria may be the cause of the disease. On the other hand, according to this aspect, even if the indigenous bacterium (the non-pathogen) is the cause of the disease, the infected organ can be estimated, and the accuracy of the estimation by the infected organ estimation unit 108 is further improved. ..
　前述したように、本装置１００は、例えば、さらに、画像切替判断部１０９を含んでもよい。画像切替判断部１０９は、例えば、画像取得部１０１による前記工程Ｓ１０１において、前記顕微鏡画像の取得時及び前記顕微鏡画像の非取得時を判断する（Ｓ１０９）。そして、認識推定部１０２及びカウント部１０３は、前記顕微鏡画像の取得時から前記顕微鏡画像の非取得時に切り替わった後、それぞれ、前記染色物質推定種類情報及び前記染色物質推定個数情報の生成を実施してもよい。 As described above, the present device 100 may further include, for example, an image switching determination unit 109. For example, in the step S101 by the image acquisition unit 101, the image switching determination unit 109 determines when the microscope image is acquired and when the microscope image is not acquired (S109). Then, the recognition estimation unit 102 and the counting unit 103 switch from the acquisition of the microscope image to the non-acquisition of the microscope image, and then generate the stained substance estimated type information and the stained substance estimated number information, respectively. You may.
　前述したように、本装置１００は、例えば、さらに、染色装置制御部１１０、顕微鏡制御部１１１、及び検体固定装置制御部１１３の少なくとも一つを含んでもよい。染色装置制御部１１０は、前記検体を自動染色して前記染色標本を調製する染色装置を制御する。染色装置制御部１１０による制御のタイミングは、特に制限されないが、例えば、前記工程Ｓ１０１の前に実行される。前記染色装置は、例えば、本発明の自動染色装置であってもよい。顕微鏡制御部１１１は、前記染色標本の顕微鏡画像を撮像する顕微鏡を制御する。顕微鏡制御部１１１による制御のタイミングは、特に制限されないが、例えば、前記工程Ｓ１０１の前に実行される。画像取得部１０１は、例えば、前記顕微鏡にて撮像された前記顕微鏡画像を取得する。顕微鏡制御部１１１は、例えば、スライドガラスに塗抹された染色標本の一部または全体を高倍率で撮像するように前記顕微鏡を制御してもよい。ここで、高倍率とは対物レンズ40倍や100倍等のことである。顕微鏡制御部１１１は、例えば、１枚のスライドガラスに対して複数の倍率を用いて撮像するように前記顕微鏡を制御してもよい。検体固定装置制御部１１３は、スライドガラス上に塗抹された検体に対して固定処理を実施する検体固定装置を制御する。前記検体固定装置については後述する。 As described above, the apparatus 100 may further include, for example, at least one of the staining apparatus control unit 110, the microscope control unit 111, and the sample fixing device control unit 113. The staining device control unit 110 controls a staining device that automatically stains the sample and prepares the stained sample. The timing of control by the dyeing apparatus control unit 110 is not particularly limited, but is executed, for example, before the step S101. The dyeing device may be, for example, the automatic dyeing device of the present invention. The microscope control unit 111 controls a microscope that captures a microscope image of the stained specimen. The timing of control by the microscope control unit 111 is not particularly limited, but is executed, for example, before the step S101. The image acquisition unit 101 acquires, for example, the microscope image captured by the microscope. The microscope control unit 111 may control the microscope so as to capture a part or the whole of the stained specimen smeared on the slide glass at a high magnification, for example. Here, the high magnification means an objective lens of 40 times, 100 times, or the like. The microscope control unit 111 may control the microscope so as to take an image with a plurality of magnifications for one slide glass, for example. The sample fixing device control unit 113 controls a sample fixing device that performs a fixing process on the sample smeared on the slide glass. The sample fixing device will be described later.
　ここで、本発明における「スライドガラス」には、必要に応じて、カバーガラスが積層されていてもよい。すなわち、本発明における「スライドガラス」は、必要に応じて、「プレパラート」と読み替え可能である。例えば、前記検体に対する染色の手法がグラム染色であれば、カバーガラスなしで、前記顕微鏡による撮像が行われてもよい。 Here, the "slide glass" in the present invention may be laminated with a cover glass, if necessary. That is, the "slide glass" in the present invention can be read as "preparation" as needed. For example, if the method of staining the sample is Gram stain, imaging with the microscope may be performed without a cover glass.
　顕微鏡制御部１１１による制御の一例について図４を用いて説明する。図４の左側に示すように、検体はスライドガラス１０上にＡから矢印の方向に塗り広げられることが多い。そのため、スライドガラス１０の長手方向に顕微鏡で観察していくと、図４右側に示すように、検体が濃く塗抹された部分が一定の間隔で現れる。図４の右側は、スライドガラス１０の一部拡大図である。この一部拡大図において、濃淡は、検体の塗抹の濃さを意味し、図中の濃淡が濃いほど検体が濃く塗抹された領域であることを意味する。また、図４の右側の一部拡大図において、太枠で囲った箇所は、顕微鏡による視野領域（すなわち、前記顕微鏡画像）を意味し、矢印は、前記視野領域の移動（すなわち、スライドガラス１０を保持している保持部の移動）を意味する。まず、顕微鏡制御部１１１は、視野領域（１）の顕微鏡画像に対して、適正画像か否かを判定する。ここで、適正画像とは、例えば、染色良好な染色物質が映った画像や、染色物質がはっきり見えた画像のことである。視野領域（１）では、検体の塗抹が薄すぎるため、染色物質がはっきり見えず、適正画像ではないと判定される。次に、顕微鏡制御部１１１は、前記保持部をスライドガラス１０の長手方向に移動させ、視野領域（２）の顕微鏡画像に対して、適正画像か否かを判定する。視野領域（２）では、検体の塗抹が濃くも薄くもなく、染色物質がはっきり見えるため、適正画像であると判定される。そして、顕微鏡制御部１１１は、前記適正画像であると判定した後に、視野領域（１）から（２）への移動のような前記長手方向の移動から、視野領域（２）～（４）への移動のような短手方向の移動に切り替えるように前記顕微鏡を制御する。このように、顕微鏡制御部１１１は、前記顕微鏡画像毎に適正画像か否かを判定し、適正画像でないと判定した場合は、スライドガラス１０の長手方向に移動し、適正画像であると判定した場合は、スライドガラス１０の短手方向に移動するように、前記保持部の移動を制御する。前述したように、スライドガラス１０上への検体の塗抹は、図４の左側に示すように塗り広げられることが多いため、スライドガラス１０の長手方向に顕微鏡で観察していくと、図４右側に示すように、検体が濃く塗抹された部分が一定の間隔で現れる。そのため、臨床判断の役に立つような適正な濃さの画像を見つけた際、その短手方向側には同じく適正な画像が見つかる可能性が高い。このように、本態様によれば、より効率的な視野探索が可能になる。 An example of control by the microscope control unit 111 will be described with reference to FIG. As shown on the left side of FIG. 4, the sample is often spread on the slide glass 10 in the direction of the arrow from A. Therefore, when observing with a microscope in the longitudinal direction of the slide glass 10, as shown on the right side of FIG. 4, darkly smeared portions of the sample appear at regular intervals. The right side of FIG. 4 is a partially enlarged view of the slide glass 10. In this partially enlarged view, the shading means the density of the smear of the sample, and the darker the shading in the figure, the darker the sample is the smeared region. Further, in the partially enlarged view on the right side of FIG. 4, the portion surrounded by the thick frame means the visual field region by the microscope (that is, the microscope image), and the arrow indicates the movement of the visual field region (that is, the slide glass 10). It means the movement of the holding part that holds the. First, the microscope control unit 111 determines whether or not the microscope image in the visual field region (1) is an appropriate image. Here, the proper image is, for example, an image in which a dyeing substance with good dyeing is reflected or an image in which the dyeing substance is clearly visible. In the visual field region (1), the smear of the sample is too thin, so that the dyeing substance cannot be clearly seen, and it is determined that the image is not appropriate. Next, the microscope control unit 111 moves the holding unit in the longitudinal direction of the slide glass 10 and determines whether or not the image is appropriate for the microscope image in the visual field region (2). In the visual field region (2), the smear of the sample is neither dark nor thin, and the staining substance is clearly visible, so that the image is judged to be appropriate. Then, after determining that the image is appropriate, the microscope control unit 111 moves from the longitudinal movement such as the movement from the visual field region (1) to (2) to the visual field regions (2) to (4). The microscope is controlled to switch to movement in the lateral direction, such as movement of. In this way, the microscope control unit 111 determines whether or not the image is appropriate for each of the microscope images, and if it is determined that the image is not appropriate, the microscope control unit 111 moves in the longitudinal direction of the slide glass 10 and determines that the image is appropriate. In this case, the movement of the holding portion is controlled so as to move in the lateral direction of the slide glass 10. As described above, the smear of the sample on the slide glass 10 is often spread as shown on the left side of FIG. 4, so when observed with a microscope in the longitudinal direction of the slide glass 10, the right side of FIG. 4 is observed. As shown in, areas where the sample is heavily smeared appear at regular intervals. Therefore, when an image with an appropriate darkness that is useful for clinical judgment is found, there is a high possibility that an image with an appropriate darkness will also be found on the side in the lateral direction. As described above, according to this aspect, more efficient visual field search becomes possible.
　顕微鏡制御部１１１による制御のその他の例について図５を用いて説明する。まず、顕微鏡制御部１１１は、スライドガラス１０全体の濃淡データを取得する。前記濃淡データは、例えば、図５左側に示すように、スライドガラス１０全体を濃淡認識装置２０で読み取ることで生成される検体の塗抹の濃淡を示す情報である。濃淡認識装置２０は、例えば、カメラ、センサ等の公知の装置を用いることができる。濃淡認識装置２０は、例えば、入力装置５であってもよいし、外部の装置であってもよい。次に、顕微鏡制御部１１１は、前記濃淡データを解析して予め設定した範囲内の濃さを有する位置を特定する。前記濃さは、任意に設定可能である。そして、顕微鏡制御部１１１は、前記位置から視野探索を開始するように前記保持部の移動を制御する。検体は、検査技師によりスライドガラス上に塗抹されるが、スライドガラス中で濃淡ができてしまうため、適正な視野を探索し、病原菌等を発見するには時間がかかるという問題があった。例えば、病原菌や細胞等の密度が小さい検体が、スライドガラスに塗抹されると、検体の塗抹が薄い箇所を顕微鏡で観察しても病原菌や細胞等が見えない場合が多い。これに対して、本態様によれば、塗抹の濃淡を把握可能であるため、より効率的な視野探索が可能になる。 Another example of control by the microscope control unit 111 will be described with reference to FIG. First, the microscope control unit 111 acquires the shading data of the entire slide glass 10. The shading data is, for example, as shown on the left side of FIG. 5, information indicating the shading of the smear of the sample generated by reading the entire slide glass 10 with the shading recognition device 20. As the shade recognition device 20, for example, a known device such as a camera or a sensor can be used. The shade recognition device 20 may be, for example, an input device 5 or an external device. Next, the microscope control unit 111 analyzes the shading data and identifies a position having a density within a preset range. The density can be set arbitrarily. Then, the microscope control unit 111 controls the movement of the holding unit so as to start the visual field search from the position. The sample is smeared on the slide glass by an inspection engineer, but there is a problem that it takes time to search for an appropriate field of view and detect pathogens and the like because shading is formed in the slide glass. For example, when a sample having a low density of pathogens or cells is smeared on a slide glass, the pathogens or cells are often invisible even when the spot where the sample is thinly smeared is observed with a microscope. On the other hand, according to this aspect, since it is possible to grasp the shading of the smear, more efficient visual search can be performed.
　染色装置制御部１１０は、例えば、染色工程の一工程である脱色工程における脱色時間を前記検体毎に指定可能であってもよい。具体的に、前記脱色時間は、ユーザ（医療関係者等）によって前記脱色時間が入力されることで、指定可能である。前記染色工程は、特に制限されず、従来公知の染色手法の工程であってもよい。具体的に、染色手法として、細菌の有無や特徴を主に調べるグラム染色、抗酸菌の有無や特徴を主に調べるチールニールゼン染色等がある。染色装置制御部１１０は、例えば、指定された前記脱色時間で脱色工程を実施するように染色装置を制御する。染色装置制御部１１０は、例えば、前記脱色工程以外の他の工程にかかる時間も前記検体毎に指定可能であってもよい。そして、染色装置制御部１１０は、例えば、指定された時間でその工程を実施するように前記染色装置を制御してもよい。これにより、染色の精度を向上可能である。 The dyeing apparatus control unit 110 may be able to specify, for example, the decolorization time in the decolorization step, which is one step of the dyeing step, for each sample. Specifically, the decolorization time can be specified by inputting the decolorization time by a user (medical personnel or the like). The dyeing step is not particularly limited, and may be a step of a conventionally known dyeing method. Specifically, as a staining method, there are Gram stain, which mainly examines the presence or absence and characteristics of bacteria, and Thirneilsen staining, which mainly examines the presence and characteristics of acid-fast bacilli. The dyeing device control unit 110 controls the dyeing device so as to carry out the decolorization step at the designated decolorization time, for example. For example, the dyeing apparatus control unit 110 may be able to specify the time required for steps other than the decolorization step for each sample. Then, the dyeing device control unit 110 may control the dyeing device so as to carry out the step at a designated time, for example. This makes it possible to improve the accuracy of dyeing.
　特に、脱色工程において、過度な脱色によりグラム陽性（紫色）に染まるはずの病原体がグラム陰性（赤色）に染まることや、グラム陰性（赤色）に染まるはずの病原体がグラム陽性（紫色）に染まることがあり得る。なお、この問題は、グラム染色に限らず起こり得る問題である。このため、間違った検査結果が出ることがある。一般的に、脱色の程度を決める要素には、脱色時間と検体と脱色液との触れ合わせ方がある。前記脱色時間については、検体が水っぽく塗抹が薄くなる検体（例えば、血液培養検体や尿等の）では５～７秒程度であるが、粘度の高い喀痰等の検体では１０秒以上かけて脱色することもある。このように、検体の種類によって、適切な脱色時間が異なるため、前述したような過度な脱色が起こり得る。これに対して、染色装置制御部１１０は、ユーザが検体毎に入力した脱色時間の指定可能であるため、どんな検体でも適度に脱色することが可能となる。 In particular, in the decolorization process, pathogens that should be stained with Gram-positive (purple) due to excessive decolorization are stained with Gram-negative (red), and pathogens that should be stained with Gram-negative (red) are stained with Gram-positive (purple). There can be. It should be noted that this problem is not limited to Gram stain and can occur. Therefore, incorrect test results may be obtained. In general, factors that determine the degree of decolorization include the decolorization time and the contact between the sample and the decolorizing liquid. The decolorization time is about 5 to 7 seconds for a sample whose smear is watery and thin (for example, blood culture sample or urine), but it takes 10 seconds or more for a sample such as highly viscous sputum. Sometimes. As described above, since the appropriate decolorization time differs depending on the type of sample, excessive decolorization as described above may occur. On the other hand, since the staining device control unit 110 can specify the decolorization time input by the user for each sample, any sample can be appropriately decolorized.
　前述したように、本装置１００は、例えば、さらに、優先度設定部１１２を含んでもよい。優先度設定部１１２は、前記検体毎に任意の優先度を設定可能である。具体的に、本装置１０は、例えば、入力装置５等を介して、医療従事者が入力した優先度を前記検体に設定する。前記優先度は、例えば、数字、文字、記号等で表される。そして、染色装置制御部１１０、顕微鏡制御部１１１、及び検体固定装置制御部１１３の少なくとも一つは、前記優先度の高い順に、前記染色装置、前記顕微鏡、及び前記検体固定装置の処理が実施されるように制御する。これにより、前記検体に対する処理が各種装置へのセット順ではなく、前記優先度順になるため、一方の検体が、前記一方の検体よりも前にセットされた他方の検体よりも先に処理される、いわゆる割り込みが起こり得る。一般的に、検体の種類や診療科によって検査結果を返却する時間的優先度が異なる。例えば、血液培養検体が培養陽性になった時は敗血症を疑うが、敗血症は、とても緊急度の高い疾患であるため、即時の菌種（染色物質）推定と抗菌薬投与が必要になる。また、救急科から提出された検体についても、検査結果を早く返すことが望ましい。これに対し、優先度設定部１１２によれば、優先度を設定可能であるから、優先度の高い検体から優先して本装置１００等の処理に供することができる。 As described above, the present device 100 may further include, for example, a priority setting unit 112. The priority setting unit 112 can set an arbitrary priority for each sample. Specifically, the present device 10 sets the priority input by the medical staff to the sample via, for example, the input device 5. The priority is represented by, for example, numbers, letters, symbols, and the like. Then, at least one of the staining device control unit 110, the microscope control unit 111, and the sample fixing device control unit 113 is subjected to processing of the staining device, the microscope, and the sample fixing device in descending order of priority. To control. As a result, the processing for the sample is not in the order of setting in various devices but in the order of priority, so that one sample is processed before the other sample set before the one sample. , So-called interrupts can occur. Generally, the time priority for returning test results differs depending on the type of sample and the clinical department. For example, when a blood culture sample becomes positive for culture, sepsis is suspected, but since sepsis is a very urgent disease, immediate bacterial species (staining substance) estimation and antibacterial drug administration are required. It is also desirable to return the test results as soon as possible for the samples submitted by the emergency department. On the other hand, according to the priority setting unit 112, since the priority can be set, it is possible to give priority to the sample having the highest priority for processing by the apparatus 100 or the like.
［実施形態２］
　図６は、本実施形態の自動染色装置２００の構成の一例を示す模式図である。図６に示すように、本装置２００は、保持部２０１、移動部２０２、染色試薬供給部２０３、及び、制御部２０４を含む。また、本装置２００は、任意の構成として、さらに、廃液タンク２０５、染色試薬ボトル２０６等や従来公知の構成を含んでもよい。制御部２０４は、例えば、自動染色装置２００が備えるハードウエアの一つである中央処理装置１により実行される。自動染色装置２００のその他のハードウエアの構成は、特に制限されず、例えば、前記実施形態１に記載のハードウエアの構成を援用可能である。 [Embodiment 2]
FIG. 6 is a schematic view showing an example of the configuration of the automatic dyeing apparatus 200 of the present embodiment. As shown in FIG. 6, the apparatus 200 includes a holding unit 201, a moving unit 202, a staining reagent supply unit 203, and a control unit 204. Further, the apparatus 200 may further include, as an arbitrary configuration, a waste liquid tank 205, a staining reagent bottle 206, and the like, and conventionally known configurations. The control unit 204 is executed by, for example, a central processing unit 1 which is one of the hardware included in the automatic dyeing device 200. The configuration of other hardware of the automatic dyeing apparatus 200 is not particularly limited, and for example, the hardware configuration described in the first embodiment can be incorporated.
　保持部２０１は、スライドガラス１０を保持可能である。なお、前述したように、本実施形態においても、必要に応じて、「スライドガラス」を「プレパラート」と読み替え可能である。スライドガラス１０は、例えば、染色工程の終了後に、カバーガラスが載せられ、プレパラートになる。保持部２０１は、スライドガラス１０を保持可能であれば、その形態は、特に制限されない。保持部２０１は、例えば、図６に示すように、ステージ状の保持部２０１であって、スライドガラス１０を載置して保持可能であってもよいし、後述するようにクリップ状の保持部２０１であって、スライドガラス１０を挟み込んで保持可能であってもよい。なお、スライドガラス１０には、検査対象生物から採取された検体が塗抹されているものとする。保持部２０１は、図６に示すように、試薬滴下部２０３１の下方に配置され、スライドガラス１０の前記検体が塗抹されている面を試薬滴下部２０３１に向けて保持する。 The holding portion 201 can hold the slide glass 10. As described above, also in the present embodiment, "slide glass" can be read as "preparation" as needed. On the slide glass 10, for example, after the dyeing step is completed, a cover glass is placed on the slide glass 10 to prepare the slide glass 10. The form of the holding portion 201 is not particularly limited as long as it can hold the slide glass 10. The holding portion 201 is, for example, as shown in FIG. 6, a stage-shaped holding portion 201, which may be capable of mounting and holding the slide glass 10, or a clip-shaped holding portion as described later. The number is 201, and the slide glass 10 may be sandwiched and held. It is assumed that the slide glass 10 is smeared with a sample collected from the organism to be inspected. As shown in FIG. 6, the holding portion 201 is arranged below the reagent dropping portion 2031 and holds the surface of the slide glass 10 on which the sample is smeared toward the reagent dropping portion 2031.
　移動部２０２は、保持部２０１に連結して保持部２０１を移動可能である。移動部２０２は、保持部２０１を移動可能であれば、その形態は、特に制限されない。前記移動は、水平移動でもよいし、垂直移動でもよいし、回転移動でもよい。 The moving unit 202 is connected to the holding unit 201 and can move the holding unit 201. The form of the moving unit 202 is not particularly limited as long as the holding unit 201 can be moved. The movement may be horizontal movement, vertical movement, or rotational movement.
　染色試薬供給部２０３は、複数の試薬滴下部２０３１を含む。複数の試薬滴下部２０３１は、図６に示すように、染色工程に応じて並んで配置されている。前記染色工程は、特に制限されず、例えば、前述と同様である。複数の試薬滴下部２０３１の各試薬滴下部２０３１は、前記染色工程に応じて一種類の試薬を滴下可能である。前記試薬は、例えば、染色試薬ボトル２０６内に収容されている。染色試薬供給部２０３は、例えば、染色試薬ボトル２０６から試薬滴下部２０３１に前記試薬を供給する。試薬滴下部２０３１は、例えば、前記検体又はその周辺のみに前記試薬を滴下してもよいし、ステージ状の保持部２０１を前記試薬で満たすように前記試薬を滴下してもよい。 The dyeing reagent supply unit 203 includes a plurality of reagent dropping units 2031. As shown in FIG. 6, the plurality of reagent dropping portions 2031 are arranged side by side according to the dyeing step. The dyeing step is not particularly limited and is, for example, the same as described above. Each reagent dropping section 2031 of the plurality of reagent dropping sections 2031 can drop one type of reagent according to the dyeing step. The reagent is housed in, for example, a stain reagent bottle 206. The staining reagent supply unit 203 supplies the reagent from the staining reagent bottle 206 to the reagent dropping unit 2031, for example. The reagent dropping unit 2031 may, for example, drop the reagent only on or around the sample, or may drop the reagent so as to fill the stage-shaped holding portion 201 with the reagent.
　制御部２０４は、移動部２０２を制御することにより、保持部２０１を、前記染色工程に応じてスライドガラス１０に供給が必要な試薬を滴下可能な試薬滴下部２０３１の下方に位置するように移動させる。制御部２０４は、前記実施形態１記載の染色装置制御部１１０からの制御に従い、前記移動等の各部の制御を行う。制御部２０４は、例えば、前記実施形態１記載の染色装置制御部１１０からの制御に従い制御されてもよい。制御部２０４は、例えば、染色試薬供給部２０３を制御することにより、試薬滴下部２０３１から試薬を滴下するタイミングを制御してもよい。具体的に、制御部２０４は、例えば、染色装置制御部１１０から指示された時間の経過後に前記試薬を滴下するように前記各部を制御してもよい。また、制御部２０４は、例えば、染色試薬供給部２０３を制御することにより、前記試薬の滴下から廃液タンク２０５へ廃液するまでの時間等を制御してもよい。具体的に、制御部２０４は、例えば、染色装置制御部１１０から指示された時間の経過後にスライドガラス１０の前記検体が塗抹されている面上に滴下された試薬を廃液タンク２０５に廃液するように前記各部を移動させてもよい。 By controlling the moving unit 202, the control unit 204 moves the holding unit 201 so as to be located below the reagent dropping unit 2031 capable of dropping the reagent that needs to be supplied to the slide glass 10 according to the dyeing step. Let me. The control unit 204 controls each unit such as movement in accordance with the control from the dyeing apparatus control unit 110 according to the first embodiment. The control unit 204 may be controlled, for example, according to the control from the dyeing apparatus control unit 110 according to the first embodiment. The control unit 204 may control the timing of dropping the reagent from the reagent dropping unit 2031 by controlling the staining reagent supply unit 203, for example. Specifically, the control unit 204 may control each unit so that the reagent is dropped after the lapse of time instructed by the dyeing apparatus control unit 110, for example. Further, the control unit 204 may control the time from the dropping of the reagent to the waste liquid tank 205 by controlling the dyeing reagent supply unit 203, for example. Specifically, the control unit 204 drains the reagent dropped on the surface of the slide glass 10 on which the sample is smeared after the lapse of time instructed by the dyeing device control unit 110 into the waste liquid tank 205. Each part may be moved to.
　前記染色工程中における制御部２０４の処理の一例について説明する。図７上側の図は、クリップ状の保持部２０１に保持されたスライドガラス１０の一例を示す。図示するように、スライドガラス１０の試薬滴下部２０３１と対向する面には、検査対象生物から採取された検体が塗抹されている。制御部２０４は、図７下側の図に示すように、試薬滴下部２０３１により脱色液がスライドガラス１０に滴下された後に、移動部２０２を制御することにより、スライドガラス１０の長手方向を軸として、スライドガラス１０が短手方向に傾くように保持部２０１を駆動させる。図７に示す例に限らず、制御部２０４は、例えば、スライドガラス１０の短手方向を軸にしてスライドガラス１０が長手方向に傾くように保持部２０１を駆動させてもよい。また、制御部２０４は、例えば、スライドガラス１０の長手方向及び短手方向を交互に軸にしてスライドガラス１０が長手方向及び短手方向の交互に傾くように保持部２０１を駆動させてもよい。 An example of processing of the control unit 204 during the dyeing step will be described. The upper figure of FIG. 7 shows an example of the slide glass 10 held by the clip-shaped holding portion 201. As shown in the figure, the surface of the slide glass 10 facing the reagent dropping portion 2031 is smeared with a sample collected from the organism to be inspected. As shown in the lower figure of FIG. 7, the control unit 204 controls the moving unit 202 after the decolorizing liquid is dropped on the slide glass 10 by the reagent dropping unit 2031 to axis the longitudinal direction of the slide glass 10. The holding portion 201 is driven so that the slide glass 10 is tilted in the lateral direction. Not limited to the example shown in FIG. 7, the control unit 204 may drive the holding unit 201 so that the slide glass 10 is tilted in the longitudinal direction with respect to the lateral direction of the slide glass 10, for example. Further, the control unit 204 may drive the holding unit 201 so that the slide glass 10 is tilted alternately in the longitudinal direction and the lateral direction, for example, with the longitudinal direction and the lateral direction of the slide glass 10 as axes alternately. ..
　具体的に、制御部２０４は、例えば、前記脱色液の滴下前のスライドガラス１０の保持状態を基準としたとき、スライドガラス１０の長手方向及び短手方向の少なくとも一方を軸として、前記軸ではない短手方向及び長手方向の少なくとも一方のスライドガラス１０の各端部の傾きが前記基準から予め規定した度合いになるように保持部２０１を時計回り及び反時計回りの少なくとも一方に駆動させてもよい。前記度合いは、特に制限されず、任意に設定可能である。具体的に、前記度合いは、例えば、前記基準の状態にある一端の傾きを０度としたとき、－１０度以上＋１０度以下、－５度以上＋５度以下、－３度以上＋３度以下等の範囲のうちいずれかの値の状態である。保持部２０１の駆動は、制御部２０４が移動部２０２を制御することにより実行される。制御部２０４は、このような保持部２０１の駆動を、特定の秒間（例えば、１～５秒、１～３秒、１秒等）に、特定の時間毎（例えば、１～５秒、１～３秒、１秒等）で複数回繰り返してもよい。このような制御をすることで、各試薬を前記検体にムラなく供することができ、染色の精度を向上可能である。 Specifically, for example, when the holding state of the slide glass 10 before dropping the decolorizing liquid is used as a reference, the control unit 204 may use at least one of the longitudinal direction and the lateral direction of the slide glass 10 as an axis. Even if the holding portion 201 is driven to at least one of clockwise and counterclockwise so that the inclination of each end of at least one of the slide glass 10 in the lateral direction and the longitudinal direction becomes a degree predetermined from the above reference. good. The degree is not particularly limited and can be set arbitrarily. Specifically, the degree is, for example, -10 degrees or more and +10 degrees or less, -5 degrees or more and +5 degrees or less, -3 degrees or more and +3 degrees or less, etc., when the inclination of one end in the reference state is 0 degrees. It is the state of any value in the range of. The driving of the holding unit 201 is executed by the control unit 204 controlling the moving unit 202. The control unit 204 drives the holding unit 201 in specific seconds (for example, 1 to 5 seconds, 1 to 3 seconds, 1 second, etc.) and at specific time intervals (for example, 1 to 5 seconds, 1 second, etc.). It may be repeated a plurality of times in ~ 3 seconds, 1 second, etc.). By performing such control, each reagent can be uniformly applied to the sample, and the accuracy of staining can be improved.
　特に、脱色工程は、前述したように、適切な脱色させることが難しい工程である。脱色の程度を決める要素には、前述したように、脱色時間と検体と脱色液との触れ合わせ方がある。制御部２０４は、前記制御により、これらを効率的に触れ合わせることが可能であるため、脱色の精度を向上可能である。 In particular, the decolorization process is a process in which it is difficult to properly decolorize as described above. As described above, factors that determine the degree of bleaching include the bleaching time and the contact between the sample and the bleaching solution. Since the control unit 204 can efficiently touch these by the above control, the accuracy of decolorization can be improved.
　本実施形態によれば、検体の染色工程を自動で行えるため、塗抹鏡検検査等の検査を支援可能である。 According to this embodiment, since the sample staining process can be performed automatically, it is possible to support inspections such as smear inspection.
［実施形態３］
　図８は、本実施形態の自動染色物質推定システム１０００の構成の一例を示す模式図である。図８に示すように、自動染色物質推定システム１０００は、自動染色装置２００、顕微鏡装置３００、及び、顕微鏡検査支援装置１００を含む。顕微鏡検査支援装置１００は、前記実施形態１記載の顕微鏡検査支援装置１００である。自動染色物質推定システム１０００は、任意の構成として、例えば、さらに、ユーザ端末４００、検体固定装置５００を含んでもよい。顕微鏡検査支援装置１００は、前記通信回線網を介して、自動染色装置２００、顕微鏡装置３００、ユーザ端末４００、及び検体固定装置５００と通信可能である。自動染色物質推定システム１０００は、自動染色物質推定システム装置１０００ともいえる。なお、図８における各装置及び端末の数は一例であって、複数あってもよい。 [Embodiment 3]
FIG. 8 is a schematic diagram showing an example of the configuration of the automatic staining substance estimation system 1000 of the present embodiment. As shown in FIG. 8, the automatic staining substance estimation system 1000 includes an automatic staining device 200, a microscope device 300, and a microscopy support device 100. The microscopic examination support device 100 is the microscopic examination support device 100 according to the first embodiment. The automatic staining substance estimation system 1000 may further include, for example, a user terminal 400 and a sample fixing device 500 as an arbitrary configuration. The microscopic examination support device 100 can communicate with the automatic staining device 200, the microscope device 300, the user terminal 400, and the sample fixing device 500 via the communication network. The automatic stain substance estimation system 1000 can be said to be an automatic stain substance estimation system device 1000. The number of each device and terminal in FIG. 8 is an example, and may be plural.
　検体固定装置５００は、スライドガラス上に塗抹された検体に対して固定処理を実施する装置であれば、特に制限されない。前記固定処理は、特に制限されず、従来公知の固定処理を適用可能である。前記固定処理として、例えば、熱を用いる処理、アルコールを用いる処理等がある。前記固定処理を施された検体は、自動染色装置２００にて染色される。 The sample fixing device 500 is not particularly limited as long as it is a device that performs a fixing process on the sample smeared on the slide glass. The fixing process is not particularly limited, and a conventionally known fixing process can be applied. The fixing treatment includes, for example, a treatment using heat, a treatment using alcohol, and the like. The sample subjected to the fixing treatment is stained by the automatic staining apparatus 200.
　一般的に、グラム染色等の染色を行うにあたり、チューブなどに入った検体をスライドガラス上に塗抹し、菌やウイルスを殺し、固定処理を実施する。その後、染色・乾燥・顕微鏡観察・カルテ記入という工程が連続する。前記アルコールを用いる処理（アルコール固定ともいう）では、３～５分程度、前記検体をアルコールに浸しておく必要がある。このように、前記固定処理を実施には、手間がかかるという問題がある。これに対し、検体固定装置５００を用いることで、前記固定処理を自動化でき、現場の負担をさらに軽減することができる。また、検体固定装置５００を用いることで、固定処理に用いる方法が統一可能であるから、検査の精度も向上可能である。 Generally, when performing staining such as Gram stain, the sample in a tube or the like is smeared on a slide glass to kill bacteria and viruses, and immobilization is performed. After that, the processes of dyeing, drying, microscopic observation, and medical record entry are continued. In the treatment using alcohol (also referred to as alcohol fixation), it is necessary to soak the sample in alcohol for about 3 to 5 minutes. As described above, there is a problem that it takes time and effort to carry out the fixing process. On the other hand, by using the sample fixing device 500, the fixing process can be automated and the burden on the site can be further reduced. Further, by using the sample fixing device 500, the method used for the fixing process can be unified, so that the accuracy of the inspection can be improved.
　自動染色装置２００は、前記検体を自動染色して染色標本を調製する装置であれば特に制限されず、例えば、前記実施形態２記載の自動染色装置２００である。自動染色装置２００にて調製された前記染色標本は、顕微鏡装置３００にセットされ、顕微鏡画像が撮像される。前記セットは、例えば、人手で行ってもよい。 The automatic staining apparatus 200 is not particularly limited as long as it is an apparatus that automatically stains the specimen to prepare a stained specimen, and is, for example, the automatic staining apparatus 200 according to the second embodiment. The stained specimen prepared by the automatic staining device 200 is set in the microscope device 300, and a microscope image is taken. The set may be performed manually, for example.
　自動染色装置２００の試薬滴下部２０３１の下部から顕微鏡装置３００の対物レンズ３０１の下部へのスライドガラス１０の移動は、人手でやってもよいが、図９に示すように移動部２０２を移動させることで行ってもよい。顕微鏡装置３００の対物レンズ３０１の下部へのスライドガラス１０を移動させる前に、必要に応じて、スライドガラス１０上にカバーガラスを積層してもよいし、積層しなくともよい。前記積層は、例えば、人手で行ってもよい。図９は、スライドガラス１０が自動染色装置２００の試薬滴下部２０３１の下部から顕微鏡装置３００の対物レンズ３０１の下部へ移動する一例を示す模式図である。図９に示すように、保持部２０１に保持されたスライドガラス１０は、移動部２０２により、自動染色装置２００の試薬滴下部２０３１の下部から顕微鏡装置３００の対物レンズ３０１の下部へ移動する。移動部２０２は、例えば、制御部２０４による制御を受けてこのように移動してもよい。すなわち、自動染色物質推定システム１０００において、移動部２０２は、自動染色装置２００下だけではなく、顕微鏡装置３００の対物レンズ３０１の下部まで移動可能であってもよい。顕微鏡装置３００は、対物レンズ３０１の下部に移動してきたスライドガラス１０の顕微鏡画像を撮像して、顕微鏡検査支援装置１００に出力する。このような移動を可能にする移動部２０２によれば、検査技師により検体がスライドガラス１０上に塗抹され、保持部２０１にスライドガラス１０がセットされることで、染色処理、顕微鏡での撮像、染色物質の推定を全自動で行うことができる。これにより、これまでグラム染色やチールネルゼン染色等にかかる手間を大幅に減らすことができる。 The slide glass 10 may be manually moved from the lower part of the reagent dropping part 2031 of the automatic dyeing device 200 to the lower part of the objective lens 301 of the microscope device 300, but the moving part 202 is moved as shown in FIG. You may go by. If necessary, the cover glass may or may not be laminated on the slide glass 10 before the slide glass 10 is moved to the lower part of the objective lens 301 of the microscope device 300. The laminating may be performed manually, for example. FIG. 9 is a schematic view showing an example in which the slide glass 10 moves from the lower part of the reagent dropping portion 2031 of the automatic dyeing device 200 to the lower part of the objective lens 301 of the microscope device 300. As shown in FIG. 9, the slide glass 10 held by the holding portion 201 is moved from the lower portion of the reagent dropping portion 2031 of the automatic dyeing device 200 to the lower portion of the objective lens 301 of the microscope device 300 by the moving portion 202. The moving unit 202 may move in this way under the control of, for example, the control unit 204. That is, in the automatic dyeing substance estimation system 1000, the moving unit 202 may be movable not only under the automatic dyeing device 200 but also to the lower part of the objective lens 301 of the microscope device 300. The microscope device 300 captures a microscope image of the slide glass 10 that has moved to the lower part of the objective lens 301 and outputs it to the microscope inspection support device 100. According to the moving unit 202 that enables such movement, the sample is smeared on the slide glass 10 by the inspection engineer, and the slide glass 10 is set on the holding unit 201, whereby the staining process, the imaging with a microscope, and the imaging are performed. The estimation of the dyeing substance can be performed fully automatically. As a result, it is possible to significantly reduce the labor required for Gram stain, Ziehl-Neelsen stain, and the like.
　検体固定装置５００から自動染色装置２００の試薬滴下部２０３１の下部へのスライドガラス１０の移動は、人手でやってもよいが、図１０に示すように移動部２０２を移動させることで行ってもよい。図１０は、スライドガラス１０が検体固定装置５００から自動染色装置２００の試薬滴下部２０３１の下部を通過して顕微鏡装置３００の対物レンズ３０１の下部へ移動する一例を示す模式図である。図１０に示すように、移動部２０２は、例えば、検体固定装置５００の下部にも移動可能であってもよい。移動部２０２は、例えば、制御部２０４による制御を受けてこのように移動してもよい。このように、移動部２０２は、例えば、検体固定装置５００から自動染色装置２００の試薬滴下部２０３１の下部を通過して顕微鏡装置３００の対物レンズ３０１の下部まで移動可能であってもよい。これにより、固定処理、染色処理、顕微鏡での撮像、染色物質の推定までの一連の流れを全自動で行うことができ、より手間を減らすことができる、 The slide glass 10 may be manually moved from the sample fixing device 500 to the lower part of the reagent dropping section 2031 of the automatic staining device 200, but it may also be moved by moving the moving section 202 as shown in FIG. good. FIG. 10 is a schematic view showing an example in which the slide glass 10 moves from the sample fixing device 500 to the lower part of the objective lens 301 of the microscope device 300 through the lower part of the reagent dropping portion 2031 of the automatic staining device 200. As shown in FIG. 10, the moving unit 202 may be movable to, for example, the lower part of the sample fixing device 500. The moving unit 202 may move in this way under the control of, for example, the control unit 204. In this way, the moving unit 202 may be movable from the sample fixing device 500 to the lower part of the objective lens 301 of the microscope device 300, passing through the lower part of the reagent dropping part 2031 of the automatic staining device 200, for example. As a result, a series of steps from fixing process, staining process, imaging with a microscope, and estimation of the stained substance can be performed fully automatically, and the labor can be further reduced.
　顕微鏡装置３００（単に顕微鏡３００ともいう）は、前記染色標本の顕微鏡画像を撮像可能な装置であれば特に制限されず、例えば、公知の装置であってもよい。顕微鏡装置３００にて撮像された前記顕微鏡画像は、顕微鏡検査支援装置１００に取得される。 The microscope device 300 (also simply referred to as a microscope 300) is not particularly limited as long as it can capture a microscope image of the stained specimen, and may be, for example, a known device. The microscope image taken by the microscope device 300 is acquired by the microscope inspection support device 100.
　顕微鏡検査支援装置１００は、例えば、情報出力部１０４が出力する情報を表示する表示部１１４を含んでもよい。表示部１１４は、例えば、ユーザの操作により、同一の視野に対して異なる焦点で撮像された顕微鏡画像を表示可能であってもよい。前記異なる焦点で撮像された顕微鏡画像は、例えば、前記染色物質推定種類情報に含まれる。前記ユーザの操作は、特に制限されず、例えば、マウスのホイールを動かす等の操作である。これにより、立体的な観察が可能になる。本態様は、例えば、肺炎球菌の莢膜形成像などを確認する場合に特に有用である。肺炎球菌の莢膜形成像は、平面では確認しづらく、ピントをあえてずらすことで確認できるようになる。表示部１１４による各種処理は、例えば、表示工程ともいえる。 The microscopic examination support device 100 may include, for example, a display unit 114 that displays information output by the information output unit 104. The display unit 114 may be able to display microscope images captured at different focal points for the same field of view, for example, by a user's operation. The microscopic images taken at the different focal points are included, for example, in the stained substance estimation type information. The user's operation is not particularly limited, and is, for example, an operation such as moving a mouse wheel. This enables three-dimensional observation. This aspect is particularly useful for confirming, for example, a capsule formation image of Streptococcus pneumoniae. The capsule formation image of Streptococcus pneumoniae is difficult to confirm on a flat surface, and can be confirmed by intentionally shifting the focus. The various processes performed by the display unit 114 can be said to be, for example, a display process.
　表示部１１４は、例えば、保持部２０１にスライドガラス１０が保持されると、スライドガラス１０毎に識別情報を付して、前記識別情報を表示してもよい。前記識別情報は、特に制限されず、例えば、数字、文字、記号、及びこれらの組み合わせ等である。図１２に、表示部１１４の処理により、ディスプレイに表示された識別情報等の一例を示す。図１２に示すように、表示部１１４は、例えば、スライドガラス１０の前記識別情報（スライドガラス１０毎に固有の番号として示す）とスライドガラス１０の挿入状態（保持部２０１に保持されているか否か）とを対応付けて表示してもよい。スライドガラス１０が保持部２０１に保持されていれば、例えば、前記挿入状態が「挿入済」と表示され、スライドガラス１０が保持部２０１から取り外されれば、例えば、前記挿入状態が「抜去済」と表示される。なお、「挿入済」及び「抜去済」との文言は一例であって、本発明は、これに限定されない。 For example, when the slide glass 10 is held by the holding unit 201, the display unit 114 may attach identification information to each slide glass 10 and display the identification information. The identification information is not particularly limited, and may be, for example, numbers, letters, symbols, and combinations thereof. FIG. 12 shows an example of the identification information and the like displayed on the display by the processing of the display unit 114. As shown in FIG. 12, the display unit 114 has, for example, the identification information of the slide glass 10 (indicated as a unique number for each slide glass 10) and the inserted state of the slide glass 10 (whether or not it is held by the holding unit 201). Or) may be displayed in association with each other. If the slide glass 10 is held by the holding portion 201, for example, the inserted state is displayed as "inserted", and if the slide glass 10 is removed from the holding portion 201, for example, the inserted state is "removed". Is displayed. The terms "inserted" and "removed" are examples, and the present invention is not limited thereto.
　また、表示部１１４は、例えば、図１２に示すように、前記識別情報と対応づけて、ユーザに入力に基づいて染色装置制御部１１０により設定された前記染色工程の各工程にかける時間を表示してもよい。さらに、表示部１１４は、例えば、図１２に示すように、前記識別情報と対応づけて、ユーザに入力に基づいて優先度設定部１１２により設定された前記優先度を表示してもよい。図１２において、前記優先度は、優先度の高い順に、「○」、「△」、「×」と表示されている。 Further, as shown in FIG. 12, the display unit 114 displays, for example, the time taken for each step of the dyeing process set by the dyeing device control unit 110 based on the input to the user in association with the identification information. You may. Further, the display unit 114 may display the priority set by the priority setting unit 112 based on the input to the user in association with the identification information, for example, as shown in FIG. In FIG. 12, the priorities are displayed as “◯”, “Δ”, and “×” in descending order of priority.
　表示部１１４は、例えば、図１２に示すようにテーブル形式にて顕微鏡検査支援装置１００により生成される各情報を表示してもよいが、これは例示であって、これに限定されない。 The display unit 114 may display, for example, each information generated by the microscopic examination support device 100 in a table format as shown in FIG. 12, but this is an example and is not limited thereto.
　ユーザ端末４００は、医療従事者等のユーザの端末である。具体的には、パーソナルコンピュータ（ＰＣ、例えば、デスクトップ型、ノート型）、スマートフォン、タブレット端末、ウエアラブル端末等がある。ユーザ端末４００は、情報出力部１０４が出力する情報を表示可能であり、前記情報出力部が出力する情報に対して、任意の情報を追記可能であれば、特に制限されない。情報出力部１０４が出力する情報は、例えば、複数のユーザ端末４００で共有可能な状況下にあってもよい。複数のユーザ端末４００で共有可能な状況下とは、例えば、自動染色物質推定システム１０００内外のサーバ、データベース等に格納されている状況である。微生物検査室においては、グラム染色実施場所とカルテ入力場所、そして、微生物同定検査における染色後の工程である培養判定と呼ばれる作業は、それぞれ別々の場所で実施されている。このように別々の場所でそれぞれの作業が実施されていても、前記状況下にある前記情報に対して、前記追記を行うことで、複数のユーザ端末４００で前記情報及び前記情報に対して追記された内容を共有可能である。 The user terminal 400 is a terminal of a user such as a medical worker. Specifically, there are personal computers (PCs, for example, desktop type, notebook type), smartphones, tablet terminals, wearable terminals and the like. The user terminal 400 is not particularly limited as long as it can display the information output by the information output unit 104 and can add arbitrary information to the information output by the information output unit. The information output by the information output unit 104 may be, for example, in a situation where it can be shared by a plurality of user terminals 400. The situation that can be shared by a plurality of user terminals 400 is, for example, a situation in which the automatic staining substance estimation system 1000 is stored in a server, a database, or the like inside or outside the system 1000. In the microbial laboratory, the Gram stain and the chart input place, and the work called culture determination, which is a post-staining step in the microbial identification test, are carried out at different places. Even if each work is performed in different places in this way, by performing the addition to the information under the situation, the information and the information can be added to the plurality of user terminals 400. It is possible to share the contents that have been made.
　顕微鏡検査支援装置１００において、情報出力部１０４は、例えば、出力する情報に応じて、前記情報と紐づけて通報情報を出力してもよい。前記通報情報は、例えば、感染症が疑われることや特定の対応が必要であること等を意味する情報である。例えば、前記染色物質推定種類情報が生成されて感染症が疑われる場合、前記推奨検査情報が生成されて前記追加検査（ルーチン検査以外の検査）の必要性が高い場合、前記染色物質推定種類情報や前記染色物質推定個数情報の内容により至急な対応が必要と判断された場合等において、前記通報情報が出力される。より具体的には、例えば、グラム陽性ブドウ球菌を推定したことを示す染色物質推定種類情報が生成された場合は、MRSAという薬が効きにくい耐性菌を疑い、ルーチンと異なる強い抗菌薬の投与が必要になる。ほかには、白血球や貪食白血球を推定したことを示す染色物質推定種類情報が生成された場合は、その検体が採取された場所に炎症反応が起こっていることを意味し、これらの物体が多数見つかった場合は、感染症として対応が必要になる。これらのような検体が確認できた際に、染色物質推定種類情報等の情報に紐づけて前記通報情報を出力することで、医療従事者が速やかに対応することができる。前記通報情報が出力されると、出力先の装置及び機器において、前記通報情報と紐づけられた特定の処理が実行される。例えば、前記出力先がスピーカーであれば、アラームが鳴ったり、前記出力先がモニタであれば、通報情報がモニタに表示されたり、前記出力先がランプであれば、前記ランプが点滅したりする。 In the microscopic examination support device 100, the information output unit 104 may output the report information in association with the information according to the information to be output, for example. The notification information is information that means, for example, that an infectious disease is suspected or that a specific response is required. For example, when the stained substance estimated type information is generated and an infectious disease is suspected, when the recommended test information is generated and the need for the additional test (test other than routine test) is high, the stained substance estimated type information is generated. The notification information is output when it is determined that an urgent response is necessary based on the content of the information on the estimated number of stained substances. More specifically, for example, when the stained substance estimation type information indicating that a gram-positive staphylococcus was estimated is generated, it is suspected that a resistant bacterium called MRSA is ineffective, and a strong antibacterial drug different from the routine is administered. You will need it. In addition, if the stained substance estimation type information indicating that leukocytes or phagocytic leukocytes were estimated is generated, it means that an inflammatory reaction is occurring at the place where the sample was collected, and many of these objects are present. If found, it will need to be treated as an infectious disease. When such a sample can be confirmed, the medical worker can promptly respond by outputting the notification information in association with information such as information on the estimated type of dyeing substance. When the notification information is output, a specific process associated with the notification information is executed in the output destination device and device. For example, if the output destination is a speaker, an alarm sounds, if the output destination is a monitor, notification information is displayed on the monitor, or if the output destination is a lamp, the lamp blinks. ..
　自動染色物質推定システム１０００は、図１３に示すように、例えば、さらに、濃淡認識装置２０を含んでもよい。顕微鏡検査支援装置１００は、濃淡認識装置２０と通信可能である。濃淡認識装置２０は、対象物の濃淡を認識可能な装置であり、前述に記載を援用可能である。図示していないが、自動染色物質推定システム１０００は、濃淡認識装置２０と検体固定装置５００とを併用してもよい。染色装置２００にて調製された前記染色標本は、濃淡認識装置２０に供される。そして、濃淡認識装置２０が生成した前記濃淡データを顕微鏡制御部１１１が取得して、その後、前記染色標本が、顕微鏡装置３００にセットされる。移動部２０２は、例えば、濃淡認識装置２０による濃淡認識可能位置にも移動可能であってもよい。 As shown in FIG. 13, the automatic dyeing substance estimation system 1000 may further include, for example, a shade recognition device 20. The microscopic examination support device 100 can communicate with the light and shade recognition device 20. The shading recognition device 20 is a device capable of recognizing the shading of an object, and the above description can be incorporated. Although not shown, the automatic staining substance estimation system 1000 may use the shading recognition device 20 and the sample fixing device 500 in combination. The stained specimen prepared by the staining device 200 is subjected to the shade recognition device 20. Then, the microscope control unit 111 acquires the shade data generated by the shade recognition device 20, and then the stained specimen is set in the microscope device 300. The moving unit 202 may be movable to, for example, a position where the light and shade can be recognized by the light and shade recognition device 20.
［実施形態４］
　本実施形態のプログラムは、本発明の方法の各工程を、手順として、コンピュータに実行させるためのプログラムである。本発明において、「手順」は、「処理」と読み替えてもよい。また、本実施形態のプログラムは、例えば、コンピュータ読み取り可能な記録媒体に記録されていてもよい。前記記録媒体は、例えば、非一時的なコンピュータ可読記録媒体（non-transitory computer-readable storage medium）である。前記記録媒体としては、特に限定されず、例えば、読み出し専用メモリ（ＲＯＭ）、ハードディスク（ＨＤ）、光ディスク等が挙げられる。 [Embodiment 4]
The program of the present embodiment is a program for causing a computer to execute each step of the method of the present invention as a procedure. In the present invention, "procedure" may be read as "processing". Further, the program of the present embodiment may be recorded on a computer-readable recording medium, for example. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples thereof include a read-only memory (ROM), a hard disk (HD), and an optical disk.
　以上、実施形態を参照して本発明を説明したが、本発明は、上記実施形態に限定されるものではない。本発明の構成や詳細には、本発明のスコープ内で当業者が理解しうる様々な変更をできる。 Although the present invention has been described above with reference to the embodiments, the present invention is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the structure and details of the present invention within the scope of the present invention.
　この出願は、２０２０年１１月１２日に出願された日本出願特願２０２０－１９９８９３を基礎とする優先権を主張し、その開示の全てをここに取り込む。 This application claims priority based on Japanese application Japanese Patent Application No. 2020-199893 filed on November 12, 2020, and incorporates all of its disclosures here.
　本発明によれば、塗抹鏡検検査等の検査を支援可能である。特に、本発明は、染色物質を推定する場合において有用である。 According to the present invention, it is possible to support inspections such as smear inspection. In particular, the present invention is useful in estimating dyeing substances.
１　　　　中央処理装置
２　　　　メモリ
３　　　　バス
４　　　　記憶装置
５　　　　入力装置
６　　　　出力装置
７　　　　通信デバイス
１０　　　スライドガラス
２０　　　濃淡認識装置
１００　　顕微鏡検査支援装置
１００Ａ　検査支援処理部
１０１　　画像情報取得部
１０２　　認識推定部
１０３　　カウント部
１０４　　情報出力部
１０５　　関連情報取得部
１０６　　推奨情報生成部
１０７　　カルテ情報取得部
１０８　　感染臓器推定部
１０９　　画像切替判断部
１１０　　染色装置制御部
１１１　　顕微鏡制御部
１１２　　優先度設定部
１１３　　検体固定装置制御部
２００　　自動染色装置
２０１　　保持部
２０２　　移動部
２０３　　染色試薬供給部
２０３１　試薬滴下部
２０４　　制御部
２０５　　廃液タンク
２０６　　染色試薬ボトル
３００　　顕微鏡装置
３０１　　対物レンズ
４００　　ユーザ端末
５００　　検体固定装置 1 Central processing device 2 Memory 3 Bus 4 Storage device 5 Input device 6 Output device 7 Communication device 10 Slide glass 20 Shading recognition device 100 Microscope inspection support device 100A Inspection support processing unit 101 Image information acquisition unit 102 Recognition estimation unit 103 Counting unit 104 Information output unit 105 Related information acquisition unit 106 Recommended information generation unit 107 Carte information acquisition unit 108 Infected organ estimation unit 109 Image switching judgment unit 110 Staining device control unit 111 Microscope control unit 112 Priority setting unit 113 Specimen fixing device control unit 200 Automatic Staining device 201 Holding unit 202 Moving unit 203 Staining reagent supply unit 2031 Reagent dripping unit 204 Control unit 205 Waste liquid tank 206 Staining reagent bottle 300 Microscope device 301 Objective lens 400 User terminal 500 Specimen fixing device

Claims (52)

  1. 画像情報取得部、認識推定部、カウント部、及び、情報出力部を含み、
    前記画像情報取得部は、検査対象生物から採取された検体の染色標本の顕微鏡画像を取得し、
    前記認識推定部は、前記顕微鏡画像において、染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成し、
    前記カウント部は、前記染色物質画像をカウントして染色物質推定個数情報を生成し、
    前記情報出力部は、前記染色物質推定種類情報及び前記染色物質推定個数情報を出力する、
    顕微鏡検査支援装置。     Includes image information acquisition unit, recognition estimation unit, count unit, and information output unit.
    The image information acquisition unit acquires a microscopic image of a stained specimen of a specimen collected from an organism to be inspected, and obtains a microscope image.
    The recognition estimation unit recognizes the stained substance image in the microscope image, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information.
    The counting unit counts the image of the dyed substance and generates information on the estimated number of stained substances.
    The information output unit outputs the dyeing substance estimated type information and the dyeing substance estimated number information.
    Microscopic examination support device.
  2. 前記画像取得部は、前記染色標本の複数の顕微鏡画像を取得し、
    前記認識推定部は、複数の前記顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する、
    請求項１記載の顕微鏡検査支援装置。     The image acquisition unit acquires a plurality of microscopic images of the stained specimen, and obtains a plurality of microscopic images.
    The recognition estimation unit recognizes the stain image in the plurality of microscope images, estimates the type of the stain substance from the stain image, and generates the stain substance estimation type information.
    The microscopic examination support device according to claim 1.
  3. 前記画像取得部は、前記染色標本を複数の倍率で撮像した前記顕微鏡画像を取得し、
    前記認識推定部は、複数の倍率の前記顕微鏡画像の各倍率の顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する、
    請求項１又は２記載の顕微鏡検査支援装置。     The image acquisition unit acquires the microscope image obtained by capturing the stained specimen at a plurality of magnifications.
    The recognition estimation unit recognizes the stain image in the microscope image of each magnification of the microscope image having a plurality of magnifications, estimates the type of the stain substance from the stain image, and obtains the stain substance estimation type information. Generate,
    The microscopic examination support device according to claim 1 or 2.
  4. 前記認識推定部は、推定された染色物質の種類の確率を算出して推定種類確率情報を生成し、
    前記情報出力部は、前記推定種類確率情報を前記染色物質推定種類情報と紐づけて出力する、
    請求項１から３のいずれか一項に記載の顕微鏡検査支援装置。     The recognition estimation unit calculates the probability of the estimated type of the dyeing substance and generates the estimated type probability information.
    The information output unit outputs the estimated type probability information in association with the stained substance estimated type information.
    The microscopic examination support device according to any one of claims 1 to 3.
  5. 前記認識推定部は、前記確率の大きさに応じて、推定された複数の染色物質をリスト化した染色物質リスト情報を生成し、
    前記情報出力部は、前記染色物質リスト情報を出力する、
    請求項４記載の顕微鏡検査支援装置。     The recognition estimation unit generates dyeing substance list information listing a plurality of estimated dyeing substances according to the magnitude of the probability.
    The information output unit outputs the dyeing substance list information.
    The microscopic examination support device according to claim 4.
  6. 前記染色物質は、病原体、非病原体、及び前記検査対象生物由来の細胞の少なくとも一つである、請求項１から５のいずれか一項に記載の顕微鏡検査支援装置。 The microscopic examination support device according to any one of claims 1 to 5, wherein the staining substance is at least one of a pathogen, a non-pathogen, and a cell derived from the organism to be inspected.
  7. 前記染色物質として、前記検査対象生物由来の細胞を含む場合、
    前記認識推定部は、前記染色物質推定種類情報及び前記染色物質推定個数情報に基づき、Geckler分類情報を生成し、
    前記情報出力部は、前記Geckler分類情報を出力する、
    請求項６記載の顕微鏡検査支援装置。     When the staining substance contains cells derived from the organism to be inspected,
    The recognition estimation unit generates Geckler classification information based on the staining substance estimation type information and the staining substance estimated number information.
    The information output unit outputs the Geckler classification information.
    The microscopic examination support device according to claim 6.
  8. さらに、関連情報取得部を含み、
    前記関連情報取得部は、前記染色標本に関する関連情報を取得し、
    前記認識推定部は、前記関連情報を参照して前記染色物質推定種類情報を生成する、
    請求項１から７のいずれか一項に記載の顕微鏡検査支援装置。     In addition, including the related information acquisition department,
    The related information acquisition unit acquires related information regarding the stained specimen, and obtains the related information.
    The recognition estimation unit generates the staining substance estimation type information with reference to the related information.
    The microscopic examination support device according to any one of claims 1 to 7.
  9. 前記関連情報は、前記検体対象生物に関する情報、前記検体に関する情報、及び、環境に関する情報の少なくとも一つである、
    請求項８記載の顕微鏡検査支援装置。     The related information is at least one of information about the sample target organism, information about the sample, and information about the environment.
    The microscopic examination support device according to claim 8.
  10. さらに、推奨情報生成部を含み、
    前記推奨情報部は、前記染色物質推定種類情報に基づき、推奨情報を生成し、
    前記情報出力部は、前記推奨情報を出力する、
    請求項１から９のいずれか一項に記載の顕微鏡検査支援装置。     In addition, it includes a recommended information generator.
    The recommended information unit generates recommended information based on the stained substance estimated type information.
    The information output unit outputs the recommended information.
    The microscopic examination support device according to any one of claims 1 to 9.
  11. 前記推奨情報は、推奨検査情報、及び、推奨治療情報の少なくとも一方の情報である、
    請求項１０記載の顕微鏡検査支援装置。     The recommended information is at least one of the recommended test information and the recommended treatment information.
    The microscopic examination support device according to claim 10.
  12. さらに、カルテ情報取得部を含み、
    前記カルテ情報取得部は、前記検査対象生物のカルテ情報を取得し、
    前記推奨情報生成部は、前記カルテ情報に基づき、前記推奨治療情報を生成する、
    請求項１１記載の顕微鏡検査支援装置。     In addition, including the medical record information acquisition department,
    The medical record information acquisition unit acquires the medical record information of the organism to be inspected, and obtains the medical record information.
    The recommended information generation unit generates the recommended treatment information based on the medical record information.
    The microscopic examination support device according to claim 11.
  13. さらに、カルテ情報取得部を含み、
    前記カルテ情報取得部は、前記検査対象生物のカルテ情報を取得し、
    前記認識推定部は、前記カルテ情報を用いて、疾患を発症する確率を算出して推定発症確率情報を生成し、
    前記情報出力部は、前記推定発症確率情報を前記染色物質推定種類情報と紐づけて出力する、
    請求項１から１２のいずれか一項に記載の顕微鏡検査支援装置。     In addition, including the medical record information acquisition department,
    The medical record information acquisition unit acquires the medical record information of the organism to be inspected, and obtains the medical record information.
    The recognition estimation unit calculates the probability of developing a disease using the medical record information and generates estimated onset probability information.
    The information output unit outputs the estimated onset probability information in association with the dyeing substance estimated type information.
    The microscopic examination support device according to any one of claims 1 to 12.
  14. さらに、感染臓器推定部を含み、
    前記感染臓器推定部は、前記認識推定部により認識された前記染色物質画像を用いて、前記検体を採取した臓器を感染臓器と推定して推定感染臓器情報を生成し、
    前記情報出力部は、前記推定感染臓器情報を出力する、
    請求項１から１３のいずれか一項に記載の顕微鏡検査支援装置。     In addition, including the infected organ estimation department,
    Using the stained substance image recognized by the recognition estimation unit, the infected organ estimation unit estimates the organ from which the sample is collected as an infected organ and generates estimated infected organ information.
    The information output unit outputs the estimated infected organ information.
    The microscopic examination support device according to any one of claims 1 to 13.
  15. さらに、画像切替判断部を含み、
    前記画像切替判断部は、前記画像取得部において、前記顕微鏡画像の取得時及び前記顕微鏡画像の非取得時を判断し、
    前記認識推定部及び前記カウント部は、前記顕微鏡画像の取得時から前記顕微鏡画像の非取得時に切り替わった後、それぞれ、前記染色物質推定種類情報及び前記染色物質推定個数情報の生成を実施する、
    請求項１から１４のいずれか一項の記載の顕微鏡検査支援装置。     In addition, it includes an image switching judgment unit.
    The image switching determination unit determines when the microscope image is acquired and when the microscope image is not acquired in the image acquisition unit.
    The recognition estimation unit and the counting unit switch from the acquisition of the microscope image to the non-acquisition of the microscope image, and then generate the stained substance estimated type information and the stained substance estimated number information, respectively.
    The microscopic examination support device according to any one of claims 1 to 14.
  16. さらに、染色装置制御部、顕微鏡制御部、及び検体固定装置制御部の少なくとも一つを含み、
    前記染色装置制御部は、前記検体を自動染色して染色標本を調製する染色装置を制御し、
    前記顕微鏡制御部は、前記染色標本の顕微鏡画像を撮像する顕微鏡を制御し、
    前記検体固定装置制御部は、スライドガラス上に塗抹された検体に対して固定処理を実施する検体固定装置を制御する、
    請求項１から１５のいずれか一項に記載の顕微鏡検査支援装置。     Further, it includes at least one of a staining device control unit, a microscope control unit, and a sample fixing device control unit.
    The staining device control unit controls a staining device that automatically stains the sample and prepares the stained sample.
    The microscope control unit controls a microscope that captures a microscope image of the stained specimen.
    The sample fixing device control unit controls a sample fixing device that performs a fixing process on a sample smeared on a slide glass.
    The microscopic examination support device according to any one of claims 1 to 15.
  17. 前記顕微鏡制御部は、前記顕微鏡画像毎に適正画像か否かを判定し、適正画像でないと判定した場合は、スライドガラスの長手方向に保持部を移動し、適正画像であると判定した場合は、スライドガラスの短手方向に保持部を移動するように、前記保持部の移動を制御する、
    請求項１６記載の顕微鏡検査支援装置。     The microscope control unit determines whether or not the image is appropriate for each microscope image, and if it is determined that the image is not appropriate, the holding unit is moved in the longitudinal direction of the slide glass, and if it is determined that the image is appropriate, the holding unit is moved. , Control the movement of the holding portion so as to move the holding portion in the lateral direction of the slide glass.
    The microscopic examination support device according to claim 16.
  18. 前記顕微鏡制御部は、前記スライドガラス全体の濃淡データを取得し、前記濃淡データを解析して予め設定した範囲内の濃さを有する位置を特定し、前記位置から視野探索を開始するように前記顕微鏡を制御する、
    請求項１６又は１７記載の顕微鏡検査支援装置。     The microscope control unit acquires the shading data of the entire slide glass, analyzes the shading data to identify a position having a density within a preset range, and starts the visual field search from the position. Control the microscope,
    The microscopic examination support device according to claim 16 or 17.
  19. 前記染色装置制御部は、染色工程の一工程である脱色工程における脱色時間を前記検体毎に指定可能であり、指定された前記脱色時間で脱色工程を実施するように染色装置を制御する、
    請求項１６から１８のいずれか一項に記載の顕微鏡検査支援装置。     The dyeing device control unit can specify the decolorization time in the decolorization step, which is one step of the dyeing step, for each sample, and controls the dyeing device so that the decolorization step is performed at the designated decolorization time.
    The microscopic examination support device according to any one of claims 16 to 18.
  20. さらに、優先度設定部を含み、
    前記優先度設定部は、前記検体毎に任意の優先度を設定可能であり、
    前記染色装置制御部、前記顕微鏡制御部、及び前記検体固定装置制御部の少なくとも一つは、前記優先度の高い順に、前記染色装置、前記顕微鏡、及び検体固定装置の処理が実施されるように制御する、
    請求項１６から１９のいずれか一項に記載の顕微鏡検査支援装置。     In addition, it includes a priority setting section.
    The priority setting unit can set an arbitrary priority for each sample.
    At least one of the staining device control unit, the microscope control unit, and the sample fixing device control unit is such that the staining device, the microscope, and the sample fixing device are processed in descending order of priority. Control,
    The microscopic examination support device according to any one of claims 16 to 19.
  21. 画像情報取得工程、認識推定工程、カウント工程、及び、情報出力工程を含み、
    前記画像情報取得工程は、検査対象生物から採取された検体の染色標本の顕微鏡画像を取得し、
    前記認識推定工程は、前記顕微鏡画像において、染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成し、
    前記カウント工程は、前記染色物質画像をカウントして染色物質推定個数情報を生成し、
    前記情報出力工程は、前記染色物質推定種類情報及び前記染色物質推定個数情報を出力する、
    顕微鏡検査支援方法。     Including image information acquisition process, recognition estimation process, counting process, and information output process
    In the image information acquisition step, a microscope image of a stained specimen of a specimen collected from an organism to be inspected is acquired.
    The recognition estimation step recognizes the stained substance image in the microscope image, estimates the type of the stained substance from the stained substance image, and generates the stained substance estimated type information.
    In the counting step, the stained substance images are counted to generate the estimated number of stained substances, and the information is generated.
    The information output step outputs the dyeing substance estimated type information and the dyeing substance estimated number information.
    Microscopic examination support method.
  22. 前記画像取得工程は、前記染色標本の複数の顕微鏡画像を取得し、
    前記認識推定工程は、複数の前記顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する、
    請求項２１記載の顕微鏡検査支援方法。     In the image acquisition step, a plurality of microscopic images of the stained specimen are acquired, and the image acquisition step is performed.
    In the recognition estimation step, the stain substance image is recognized in the plurality of microscope images, and the type of the stain substance is estimated from the stain substance image to generate the stain substance estimation type information.
    The microscopic examination support method according to claim 21.
  23. 前記画像取得工程は、前記染色標本を複数の倍率で撮像した前記顕微鏡画像を取得し、
    前記認識推定工程は、複数の倍率の前記顕微鏡画像の各倍率の顕微鏡画像において、前記染色物質画像を認識し、かつ、前記染色物質画像から染色物質の種類を推定して染色物質推定種類情報を生成する、
    請求項２１又は２２記載の顕微鏡検査支援方法。     In the image acquisition step, the microscope image obtained by capturing the stained specimen at a plurality of magnifications is acquired.
    In the recognition estimation step, the stain image is recognized in the microscope image of each magnification of the microscope image having a plurality of magnifications, and the type of the stain substance is estimated from the stain image to obtain the stain substance estimation type information. Generate,
    The microscopic examination support method according to claim 21 or 22.
  24. 前記認識推定工程は、推定された染色物質の種類の確率を算出して推定種類確率情報を生成し、
    前記情報出力工程は、前記推定種類確率情報を前記染色物質推定種類情報と紐づけて出力する、
    請求項２１から２３のいずれか一項に記載の顕微鏡検査支援方法。     The recognition estimation step calculates the estimated probability of the type of dyeing substance and generates the estimated type probability information.
    The information output step outputs the estimated type probability information in association with the dyeing substance estimated type information.
    The microscopic examination support method according to any one of claims 21 to 23.
  25. 前記認識推定工程は、前記確率の大きさに応じて、推定された複数の染色物質をリスト化した染色物質リスト情報を生成し、
    前記情報出力工程は、前記染色物質リスト情報を出力する、
    請求項２４記載の顕微鏡検査支援方法。     The recognition estimation step generates dyeing substance list information listing a plurality of estimated dyeing substances according to the magnitude of the probability.
    The information output step outputs the dyeing substance list information.
    The microscopic examination support method according to claim 24.
  26. 前記染色物質が、病原体、非病原体、及び前記検査対象生物由来の細胞の少なくとも一つである、請求項２１から２５のいずれか一項に記載の顕微鏡検査支援方法。 The microscopic examination support method according to any one of claims 21 to 25, wherein the staining substance is at least one of a pathogen, a non-pathogen, and a cell derived from the organism to be inspected.
  27. 前記染色物質として、前記検査対象生物由来の細胞を含む場合、
    前記認識推定工程は、前記染色物質推定種類情報及び前記染色物質推定個数情報に基づき、Geckler分類情報を生成し、
    前記情報出力工程は、前記Geckler分類情報を出力する、
    請求項２６記載の顕微鏡検査支援方法。     When the staining substance contains cells derived from the organism to be inspected,
    The recognition estimation step generates Geckler classification information based on the stained substance estimated type information and the stained substance estimated number information.
    The information output step outputs the Geckler classification information.
    The microscopic examination support method according to claim 26.
  28. さらに、関連情報取得工程を含み、
    前記関連情報取得工程は、前記染色標本に関する関連情報を取得し、
    前記認識推定工程は、前記関連情報を参照して前記染色物質推定種類情報を生成する、
    請求項２１から２７のいずれか一項に記載の顕微鏡検査支援方法。     In addition, it includes a related information acquisition process.
    The related information acquisition step acquires related information regarding the stained specimen, and obtains the related information.
    The recognition estimation step generates the staining substance estimation type information with reference to the related information.
    The microscopic examination support method according to any one of claims 21 to 27.
  29. 前記関連情報は、前記検体対象生物に関する情報、前記検体に関する情報、及び、環境に関する情報の少なくとも一つである、
    請求項２８記載の顕微鏡検査支援方法。     The related information is at least one of information about the sample target organism, information about the sample, and information about the environment.
    28. The microscopic examination support method according to claim 28.
  30. さらに、推奨情報生成工程を含み、
    前記推奨情報生成工程は、前記染色物質推定種類情報に基づき、推奨情報を生成し、
    前記情報出力工程は、前記推奨情報を出力する、
    請求項２１から２９のいずれか一項に記載の顕微鏡検査支援方法。     In addition, it includes a recommended information generation process.
    The recommended information generation step generates recommended information based on the stained substance estimated type information.
    The information output step outputs the recommended information.
    The microscopic examination support method according to any one of claims 21 to 29.
  31. 前記推奨情報は、推奨検査情報、及び、推奨治療情報の少なくとも一方の情報である請求項３０記載の顕微鏡検査支援方法。 The microscopic examination support method according to claim 30, wherein the recommended information is at least one of the recommended examination information and the recommended treatment information.
  32. さらに、カルテ情報取得工程を含み、
    前記カルテ情報取得工程は、前記検査対象生物のカルテ情報を取得し、
    　前記カルテ情報は、前記細胞推定種類情報及び前記細胞推定個数情報を含み、
    前記推奨情報生成工程は、前記カルテ情報に基づき、前記推奨情報を生成する、
    請求項３１記載の顕微鏡検査支援方法。     In addition, it includes a medical record information acquisition process.
    In the medical record information acquisition step, the medical record information of the organism to be inspected is acquired, and the medical record information is acquired.
    The medical record information includes the cell estimation type information and the cell estimation number information.
    The recommended information generation step generates the recommended information based on the medical record information.
    The microscopic examination support method according to claim 31.
  33. さらに、カルテ情報取得工程を含み、
    前記カルテ情報取得工程は、前記検査対象生物のカルテ情報を取得し、
    　前記カルテ情報は、前記細胞推定種類情報及び前記細胞推定個数情報を含み、
    前記認識推定工程は、前記カルテ情報を用いて、疾患を発症する確率を算出して推定発症確率情報を生成し、
    前記情報出力工程は、前記推定発症確率情報を前記染色物質推定種類情報と紐づけて出力する、
    請求項２１から３２のいずれか一項に記載の顕微鏡検査支援方法。     In addition, it includes a medical record information acquisition process.
    In the medical record information acquisition step, the medical record information of the organism to be inspected is acquired, and the medical record information is acquired.
    The medical record information includes the cell estimation type information and the cell estimation number information.
    The recognition estimation step uses the medical record information to calculate the probability of developing a disease and generate estimated onset probability information.
    The information output step outputs the estimated onset probability information in association with the stained substance estimated type information.
    The microscopic examination support method according to any one of claims 21 to 32.
  34. さらに、感染臓器推定工程を含み、
    前記感染臓器推定工程は、前記認識推定工程により認識された前記染色物質画像を用いて、前記検体を採取した臓器を感染臓器と推定して推定感染臓器情報を生成し、
    前記情報出力工程は、前記推定感染臓器情報を出力する、
    請求項２１から３３のいずれか一項に記載の顕微鏡検査支援方法。     In addition, it includes an infected organ estimation process.
    In the infected organ estimation step, using the stained substance image recognized by the recognition estimation step, the organ from which the sample is collected is estimated as an infected organ to generate estimated infected organ information.
    The information output step outputs the estimated infected organ information.
    The microscopic examination support method according to any one of claims 21 to 33.
  35. さらに、画像切替判断工程を含み、
    前記画像切替判断工程は、前記画像取得工程において、前記顕微鏡画像の取得時及び前記顕微鏡画像の非取得時を判断し、
    前記認識推定工程及び前記カウント工程は、前記顕微鏡画像の取得時から顕微鏡画像の非取得時に切り替わった後、それぞれ、前記染色物質推定種類情報及び前記染色物質推定個数情報の生成を実施する、
    請求項２１から３４のいずれか一項の記載の顕微鏡検査支援方法。     In addition, it includes an image switching judgment process.
    In the image switching determination step, in the image acquisition step, it is determined when the microscope image is acquired and when the microscope image is not acquired.
    The recognition estimation step and the counting step are switched from the acquisition of the microscope image to the non-acquisition of the microscope image, and then generate the stained substance estimated type information and the stained substance estimated number information, respectively.
    The microscopic examination support method according to any one of claims 21 to 34.
  36. さらに、染色装置制御工程、顕微鏡制御工程、及び検体固定装置制御工程の少なくとも一つを含み、
    前記染色装置制御工程は、前記検体を自動染色して染色標本を調製する染色装置を制御し、
    前記顕微鏡制御工程は、前記染色標本の顕微鏡画像を撮像する顕微鏡を制御し、
    前記検体固定装置制御工程は、スライドガラス上に塗抹された検体に対して固定処理を実施する検体固定装置を制御する、
    請求項２１から３５のいずれか一項の記載の顕微鏡検査支援方法。     Further, it comprises at least one of a staining device control step, a microscope control step, and a sample fixation device control step.
    The staining device control step controls a staining device that automatically stains the sample to prepare a stained sample.
    The microscope control step controls a microscope that captures a microscopic image of the stained specimen.
    The sample fixing device control step controls a sample fixing device that performs a fixing process on a sample smeared on a slide glass.
    The microscopic examination support method according to any one of claims 21 to 35.
  37. 前記顕微鏡制御工程は、前記顕微鏡画像毎に適正画像か否かを判定し、適正画像でないと判定した場合は、スライドガラスの長手方向に保持部を移動し、適正画像であると判定した場合は、スライドガラスの短手方向に保持部を移動するように、前記保持部の移動を制御する、
    請求項３６記載の顕微鏡検査支援方法。     The microscope control step determines whether or not the image is appropriate for each microscope image, and if it is determined that the image is not appropriate, the holding portion is moved in the longitudinal direction of the slide glass, and if it is determined that the image is appropriate. , Control the movement of the holding portion so as to move the holding portion in the lateral direction of the slide glass.
    The microscopic examination support method according to claim 36.
  38. 前記顕微鏡制御工程は、前記スライドガラス全体の濃淡データを取得し、前記濃淡データを解析して予め設定した範囲内の濃さを有する位置を特定し、前記位置から視野探索を開始するように前記顕微鏡を制御する、
    請求項３６又は３７記載の顕微鏡検査支援方法。     In the microscope control step, the shading data of the entire slide glass is acquired, the shading data is analyzed to identify a position having a density within a preset range, and the visual field search is started from the position. Control the microscope,
    The microscopic examination support method according to claim 36 or 37.
  39. 前記染色装置制御工程は、染色工程の一工程である脱色工程における脱色時間を前記検体毎に指定可能であり、指定された前記脱色時間で脱色工程を実施するように染色装置を制御する、
    請求項３６から３８のいずれか一項に記載の顕微鏡検査支援方法。     In the dyeing device control step, the decolorization time in the decolorization step, which is one step of the dyeing step, can be specified for each sample, and the dyeing device is controlled so that the decolorization step is performed at the designated decolorization time.
    The microscopic examination support method according to any one of claims 36 to 38.
  40. さらに、優先度設定工程を含み、
    前記優先度設定工程は、前記検体毎に任意の優先度を設定可能であり、
    前記染色装置制御工程、前記顕微鏡制御工程、及び前記検体固定装置制御工程の少なくとも一つは、前記優先度の高い順に、前記染色装置、前記顕微鏡、及び検体固定装置の処理が実施されるように制御する、
    請求項３６から３９のいずれか一項に記載の顕微鏡検査支援方法。     In addition, it includes a priority setting process.
    In the priority setting step, any priority can be set for each sample.
    At least one of the staining device control step, the microscope control step, and the sample fixing device control step is such that the staining device, the microscope, and the sample fixing device are processed in descending order of priority. Control,
    The microscopic examination support method according to any one of claims 36 to 39.
  41. 請求項２１から４０のいずれか一項に記載の方法の各工程を、手順として、コンピュータに実行させるプログラム。 A program for causing a computer to execute each step of the method according to any one of claims 21 to 40 as a procedure.
  42. 請求項４１記載のプログラムを記録するコンピュータ読み取り可能な記録媒体。 A computer-readable recording medium for recording the program according to claim 41.
  43. 保持部、移動部、染色試薬供給部、及び、制御部を含み、
    前記保持部は、スライドガラスを保持可能であり、
    前記スライドガラスには、検査対象生物から採取された検体が塗抹されており、
    前記移動部は、前記保持部に連結して前記保持部を移動可能であり、
    前記染色試薬供給部は、複数の試薬滴下部を含み、
    複数の前記試薬滴下部は、染色工程に応じて並んで配置され、
    複数の前記試薬滴下部の各前記試薬滴下部は、前記染色工程に応じて一種類の試薬を滴下可能であり、
    前記保持部は、前記試薬滴下部の下方に配置され、
    前記制御部は、前記移動部を制御することにより、前記保持部を、前記染色工程に応じて前記スライドガラスに供給が必要な試薬を滴下可能な前記試薬滴下部の下方に位置するように移動させる、
    自動染色装置。     Includes holding section, moving section, staining reagent supply section, and control section.
    The holding portion can hold the slide glass and can hold the slide glass.
    The slide glass is smeared with a sample collected from the organism to be inspected.
    The moving portion can be connected to the holding portion to move the holding portion.
    The staining reagent supply unit includes a plurality of reagent dropping units.
    The plurality of reagent dropping portions are arranged side by side according to the dyeing step.
    Each of the reagent dropping parts of the plurality of reagent dropping parts can drop one kind of reagent according to the dyeing step.
    The holding portion is arranged below the reagent dropping portion.
    By controlling the moving unit, the control unit moves the holding unit so as to be located below the reagent dropping unit capable of dropping the reagent that needs to be supplied to the slide glass according to the dyeing step. Let,
    Automatic dyeing device.
  44. 前記制御部は、前記試薬滴下部により脱色液が前記スライドガラスに滴下された後に、前記移動部を制御することにより、前記スライドガラスの長手方向及び短手方向の少なくとも一方を軸として、前記スライドガラスが傾くように前記保持部を駆動させる、
    請求項４３の自動染色装置。     The control unit controls the moving unit after the decolorizing liquid is dropped onto the slide glass by the reagent dropping unit, so that the slide is centered on at least one of the longitudinal direction and the lateral direction of the slide glass. The holding portion is driven so that the glass is tilted.
    The automatic dyeing apparatus according to claim 43.
  45. 前記制御部は、前記脱色液の滴下前の前記スライドガラスの保持状態を基準としたとき、前記スライドガラスの長手方向及び短手方向の少なくとも一方を軸として、前記軸ではない短手方向及び長手方向の少なくとも一方の前記スライドガラスの各端部の傾きが前記基準から予め規定した度合いになるように前記保持部を時計回り及び反時計回りの少なくとも一方に駆動させる、
    請求項４４記載の自動染色装置。     When the holding state of the slide glass before dropping the decolorizing liquid is used as a reference, the control unit has at least one of the longitudinal direction and the lateral direction of the slide glass as an axis, and the lateral direction and the longitudinal direction other than the axis. The holding portion is driven in at least one of clockwise and counterclockwise so that the inclination of each end of the slide glass in at least one direction is a predetermined degree from the reference.
    The automatic dyeing apparatus according to claim 44.
  46. 自動染色装置、顕微鏡装置、及び、顕微鏡検査支援装置を含み、
    前記顕微鏡検査支援装置は、請求項１から２０のいずれか一項に記載の装置である、
    自動染色物質推定システム。     Including automatic staining equipment, microscopic equipment, and microscopic examination support equipment,
    The device according to any one of claims 1 to 20, wherein the microscopic examination support device is the device according to any one of claims 1 to 20.
    Automatic stain estimation system.
  47. 前記自動染色装置は、請求項４３から４５のいずれか一項に記載の装置である、請求項４６の自動染色物質推定システム。 The automatic dyeing substance estimation system according to claim 46, wherein the automatic dyeing apparatus is the apparatus according to any one of claims 43 to 45.
  48. 前記顕微鏡検査支援装置は、表示部を含み、
    前記表示部は、前記情報出力部が出力する情報を表示可能である、
    請求項４６又は４７記載の自動染色物質推定システム。     The microscopic examination support device includes a display unit and includes a display unit.
    The display unit can display the information output by the information output unit.
    The automated stain estimation system according to claim 46 or 47.
  49. 前記表示部は、同一の視野に対して異なる焦点で撮像された顕微鏡画像を表示可能である、
    請求項４８記載の自動染色物質推定システム。     The display unit can display microscope images captured at different focal points for the same field of view.
    The automated stain estimation system according to claim 48.
  50. さらに、ユーザ端末を含み、
    前記ユーザ端末は、前記情報出力部が出力する情報を表示可能であり、
    他のユーザ端末と共有可能な状況下にある前記情報出力部が出力する情報に対して、任意の情報を追記可能である、
    請求項４６から４９のいずれか一項に記載の自動染色物質推定システム。     In addition, including user terminals,
    The user terminal can display the information output by the information output unit.
    Arbitrary information can be added to the information output by the information output unit that can be shared with other user terminals.
    The automated stain estimation system according to any one of claims 46 to 49.
  51. さらに、検体固定装置を含む、
    請求項４６から５０のいずれか一項に記載の自動染色物質推定システム。     In addition, including a sample fixation device,
    The automated stain estimation system according to any one of claims 46 to 50.
  52. 前記顕微鏡検査支援装置において、
    前記情報出力部は、出力する情報に応じて、通報情報も出力する、
    請求項４６から５１のいずれか一項に記載の自動染色物質推定システム。     In the microscopic examination support device
    The information output unit also outputs report information according to the information to be output.
    The automated staining substance estimation system according to any one of claims 46 to 51.
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Citations (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS5672845A (en) * 1979-11-19 1981-06-17 Hitachi Ltd Detecting apparatus of examination position of sample
JPH08285746A (en) * 1995-04-18 1996-11-01 Aloka Co Ltd Biological tissue processor
JP2000276545A (en) * 1999-03-29 2000-10-06 Hitachi Ltd Pathological image system
JP2000346769A (en) * 1999-04-23 2000-12-15 Leica Microsystems Nussloch Gmbh Automatic coloring apparatus for coloring sample for microscopic observation
JP2004333151A (en) * 2003-04-30 2004-11-25 Tokyo Aircraft Instrument Co Ltd Acidophilic bacterium inspecting system
JP2005527811A (en) * 2002-04-15 2005-09-15 ヴェンタナ メディカル システムズ インコーポレイテッド System for automatically staining large-capacity slides
JP2005283418A (en) * 2004-03-30 2005-10-13 Sysmex Corp Method and program for displaying specimen image
JP2010523979A (en) * 2007-04-05 2010-07-15 オーレオン ラボラトリーズ， インコーポレイテッド System and method for treatment, diagnosis and prediction of medical conditions
JP2010203949A (en) * 2009-03-04 2010-09-16 Nec Corp System, method and program for diagnostic imaging support, and storage medium therefor
JP2010204110A (en) * 2006-01-20 2010-09-16 Sakura Finetex Usa Inc Automatic system and method for processing biological sample
JP2012003214A (en) * 2010-05-19 2012-01-05 Sony Corp Information processor, information processing method, program, imaging device and imaging device having light microscope
JP2012141287A (en) * 2010-12-28 2012-07-26 Sakura Finetex Usa Inc Automated system and method of processing biological specimens
JP2013515264A (en) * 2009-12-22 2013-05-02 アボット・ラボラトリーズ Method for determining blood smear morphology by blood cell count
JP2015057590A (en) * 2013-06-03 2015-03-26 シスメックス株式会社 Bacterium analysis method and specimen analysis device
JP2015516149A (en) * 2012-03-19 2015-06-11 ヴェンタナ メディカル システムズ， インク． Gram staining method with improved decolorization of crystal violet-iodine complex from gram negative bacteria
JP2015522853A (en) * 2012-06-29 2015-08-06 ゼネラル・エレクトリック・カンパニイ Biological sample processing and imaging system and method
JP2015537229A (en) * 2012-12-13 2015-12-24 コーニンクレッカ フィリップス エヌ ヴェＫｏｎｉｎｋｌｉｊｋｅ Ｐｈｉｌｉｐｓ Ｎ．Ｖ． Cartridge and apparatus for preparing biological samples
JP2016001141A (en) * 2014-06-12 2016-01-07 コニカミノルタ株式会社 Diagnosis support information generation method, image processing apparatus, diagnosis support information generation system, and image processing program
JP2017122610A (en) * 2016-01-06 2017-07-13 コニカミノルタ株式会社 Image processing device and program
JP2018054472A (en) * 2016-09-29 2018-04-05 ケーディーアイコンズ株式会社 Information processing device and program
JP2018088173A (en) * 2016-11-29 2018-06-07 ケーディーアイコンズ株式会社 Information processing device
JP2018517895A (en) * 2015-04-20 2018-07-05 ベンタナ メディカル システムズ， インコーポレイテッド Inkjet deposition of reagents for histological samples
JP2019204313A (en) * 2018-05-24 2019-11-28 日本電子株式会社 Biological tissue image processing system and machine learning method
WO2020016126A2 (en) * 2018-07-16 2020-01-23 Ventana Medical Systems, Inc. Automated slide processing systems, consumable stainer units, and related technologies
WO2020016127A2 (en) * 2018-07-16 2020-01-23 Ventana Medical Systems, Inc. Automated slide processing systems, consumable slide processing modules, and reagent cartridges
JP2020056709A (en) * 2018-10-03 2020-04-09 セイコーエプソン株式会社 Electric field stirring device, electric field stirring method, and pathological specimen manufacturing device
JP2020173204A (en) * 2019-04-12 2020-10-22 コニカミノルタ株式会社 Image processing system, method for processing image, and program

Patent Citations (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS5672845A (en) * 1979-11-19 1981-06-17 Hitachi Ltd Detecting apparatus of examination position of sample
JPH08285746A (en) * 1995-04-18 1996-11-01 Aloka Co Ltd Biological tissue processor
JP2000276545A (en) * 1999-03-29 2000-10-06 Hitachi Ltd Pathological image system
JP2000346769A (en) * 1999-04-23 2000-12-15 Leica Microsystems Nussloch Gmbh Automatic coloring apparatus for coloring sample for microscopic observation
JP2005527811A (en) * 2002-04-15 2005-09-15 ヴェンタナ メディカル システムズ インコーポレイテッド System for automatically staining large-capacity slides
JP2004333151A (en) * 2003-04-30 2004-11-25 Tokyo Aircraft Instrument Co Ltd Acidophilic bacterium inspecting system
JP2005283418A (en) * 2004-03-30 2005-10-13 Sysmex Corp Method and program for displaying specimen image
JP2010204110A (en) * 2006-01-20 2010-09-16 Sakura Finetex Usa Inc Automatic system and method for processing biological sample
JP2010523979A (en) * 2007-04-05 2010-07-15 オーレオン ラボラトリーズ， インコーポレイテッド System and method for treatment, diagnosis and prediction of medical conditions
JP2010203949A (en) * 2009-03-04 2010-09-16 Nec Corp System, method and program for diagnostic imaging support, and storage medium therefor
JP2013515264A (en) * 2009-12-22 2013-05-02 アボット・ラボラトリーズ Method for determining blood smear morphology by blood cell count
JP2012003214A (en) * 2010-05-19 2012-01-05 Sony Corp Information processor, information processing method, program, imaging device and imaging device having light microscope
JP2012141287A (en) * 2010-12-28 2012-07-26 Sakura Finetex Usa Inc Automated system and method of processing biological specimens
JP2015516149A (en) * 2012-03-19 2015-06-11 ヴェンタナ メディカル システムズ， インク． Gram staining method with improved decolorization of crystal violet-iodine complex from gram negative bacteria
JP2015522853A (en) * 2012-06-29 2015-08-06 ゼネラル・エレクトリック・カンパニイ Biological sample processing and imaging system and method
JP2015537229A (en) * 2012-12-13 2015-12-24 コーニンクレッカ フィリップス エヌ ヴェＫｏｎｉｎｋｌｉｊｋｅ Ｐｈｉｌｉｐｓ Ｎ．Ｖ． Cartridge and apparatus for preparing biological samples
JP2015057590A (en) * 2013-06-03 2015-03-26 シスメックス株式会社 Bacterium analysis method and specimen analysis device
JP2016001141A (en) * 2014-06-12 2016-01-07 コニカミノルタ株式会社 Diagnosis support information generation method, image processing apparatus, diagnosis support information generation system, and image processing program
JP2018517895A (en) * 2015-04-20 2018-07-05 ベンタナ メディカル システムズ， インコーポレイテッド Inkjet deposition of reagents for histological samples
JP2017122610A (en) * 2016-01-06 2017-07-13 コニカミノルタ株式会社 Image processing device and program
JP2018054472A (en) * 2016-09-29 2018-04-05 ケーディーアイコンズ株式会社 Information processing device and program
JP2018088173A (en) * 2016-11-29 2018-06-07 ケーディーアイコンズ株式会社 Information processing device
JP2019204313A (en) * 2018-05-24 2019-11-28 日本電子株式会社 Biological tissue image processing system and machine learning method
WO2020016126A2 (en) * 2018-07-16 2020-01-23 Ventana Medical Systems, Inc. Automated slide processing systems, consumable stainer units, and related technologies
WO2020016127A2 (en) * 2018-07-16 2020-01-23 Ventana Medical Systems, Inc. Automated slide processing systems, consumable slide processing modules, and reagent cartridges
JP2020056709A (en) * 2018-10-03 2020-04-09 セイコーエプソン株式会社 Electric field stirring device, electric field stirring method, and pathological specimen manufacturing device
JP2020173204A (en) * 2019-04-12 2020-10-22 コニカミノルタ株式会社 Image processing system, method for processing image, and program

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