WO2020024227A1 - Procédé d'analyse de cellules, dispositif d'analyse de cellules et support de stockage - Google Patents

Procédé d'analyse de cellules, dispositif d'analyse de cellules et support de stockage Download PDF

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Publication number
WO2020024227A1
WO2020024227A1 PCT/CN2018/098369 CN2018098369W WO2020024227A1 WO 2020024227 A1 WO2020024227 A1 WO 2020024227A1 CN 2018098369 W CN2018098369 W CN 2018098369W WO 2020024227 A1 WO2020024227 A1 WO 2020024227A1
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WIPO (PCT)
Prior art keywords
cells
cell
selected state
voice information
blood sample
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PCT/CN2018/098369
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English (en)
Chinese (zh)
Inventor
祁欢
叶燚
李朝阳
Original Assignee
深圳迈瑞生物医疗电子股份有限公司
深圳迈瑞科技有限公司
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Application filed by 深圳迈瑞生物医疗电子股份有限公司, 深圳迈瑞科技有限公司 filed Critical 深圳迈瑞生物医疗电子股份有限公司
Priority to PCT/CN2018/098369 priority Critical patent/WO2020024227A1/fr
Priority to CN201880088546.3A priority patent/CN111684279B/zh
Publication of WO2020024227A1 publication Critical patent/WO2020024227A1/fr

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    • 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
    • G01N33/487—Physical analysis of biological material of liquid biological material
    • G01N33/49—Blood

Definitions

  • the invention relates to medical device technology, and in particular, to a cell analysis method, a cell analysis device, and a storage medium.
  • Embodiments of the present invention provide a cell analysis method, a cell analysis device, and a storage medium, which can achieve efficient and accurate cell classification.
  • An embodiment of the present invention provides a method for cell analysis, including:
  • Identify the voice information and when it is determined that the voice information is used to check the type of the cell in the selected state, determine the checked type of the cell in the selected state according to the voice information;
  • An embodiment of the present invention further provides a cell analysis device, including:
  • An image receiving device configured to acquire a digital image of a cell in a blood sample
  • a display output device configured to output a digital image of the blood sample
  • a processing device configured to select at least one cell in a digital image of the cells in the blood sample, and the selected at least one cell is in a selected state
  • a voice recognition device configured to receive and recognize voice information
  • the voice recognition device is configured to, when it is determined that the voice information is used to check the kind of the cell in the selected state, determine the checked kind of the cell in the selected state based on the voice information;
  • the speech recognition device is configured to output an approved type of the cell in a selected state
  • the storage device is configured to store the approved type of the cells in the selected state.
  • An embodiment of the present invention further provides a cell analysis device.
  • the cell analysis device includes:
  • Memory for storing executable instructions
  • the processor is configured to execute the cell analysis method provided in the embodiment of the present invention when running executable instructions stored in the memory.
  • An embodiment of the present invention further provides a storage medium storing an executable program, which is used to cause a processor to execute the executable program to implement the cell analysis method provided by the embodiment of the present invention.
  • the selected state corresponding to at least one cell in the blood sample is output, and then the type of cells in the selected state is identified by identifying the voice information.
  • the manual manual review of classification is saved, thereby avoiding the classification errors and low efficiency caused by manual operation, and simplifying the process of manual cell classification.
  • FIG. 1 is a schematic diagram of an optional structure of a cell analysis device according to an embodiment of the present invention.
  • FIG. 2 is an optional flowchart of a cell analysis method according to an embodiment of the present invention
  • FIG. 3 is an optional structural diagram of a cell analysis device according to an embodiment of the present invention.
  • FIG. 4A is a schematic diagram of image display in a cell analysis method according to an embodiment of the present invention.
  • 4B is a schematic diagram of a cell counting operation performed by a cell analysis device according to an embodiment of the present invention.
  • 4C is a schematic diagram of a cell counting operation performed by a cell analysis device according to an embodiment of the present invention.
  • FIG. 5 is a schematic diagram of an optional structure of a cell analysis device according to an embodiment of the present invention.
  • Blood cell analysis that is, blood cell analyzer blood signals, such as red blood cells, white blood cells and other cells in the blood, including classification and counting, for example, including red blood cells, hemoglobin, white blood cell counts and their classification, platelet count and other items; as an example, cell signals
  • the types can include photoelectric, capacitive, resistive, centrifugal, and laser scattering types.
  • Blood cell classification refers to the classification of cells in the blood.
  • white blood cells it can be classified into three categories, including small cell populations (lymphocytes), intermediate cell populations (eosinophils, basophils and monocytes), and Large cell populations; for example, white blood cells can be classified into five categories, including: neutrophil neutrophils / neutrophil neutrophils / eosinophils / basophils, lymphocytes, and monocytes.
  • a thin layer of blood cells is formed on the slide by a slide machine or manually to facilitate observation through a microscope.
  • the slide machine uses a blood sample to make a smear
  • the droplets of blood are dropped on a slide.
  • take another slide as the slide move the slide from the droplet side to the other side, and form a thin layer of blood cells on the slide, so that the blood cell analyzer can analyze it; in addition, make a blood smear
  • the method can be two slides to "push" a thin layer of bleeding cells, or a thin layer of blood cells sprayed.
  • Staining that is, the staining machine or the artificial use of chemical agents to stain the cells in the smear, so that different types of cells have a good degree of recognition
  • the staining machine and the slide machine can be integrated into a slide slide machine.
  • Reading images that is, cell analysis devices (also referred to as radiographers) for sorting and counting cells in blood samples.
  • one or more operations performed may be real-time or may have a set delay; Unless otherwise specified, there is no restriction on the order in which multiple operations are performed.
  • Target classification which specifies the type of cells to be detected according to the available data.
  • the cells to be detected are blood cells, and the target classification information may include: neutral rod-shaped neutrophils, neutrophils Cells, eosinophils, basophils, and lymphocytes.
  • the cell analysis device automatically classifies the cells to be detected, and classifies the cells into target classification information.
  • FIG. 1 is a schematic diagram of an optional structure of a cell analysis device 100 according to an embodiment of the present invention, and the modules involved in FIG. 1 are separately described below.
  • the image receiving device 101 is configured to acquire a digital image of a cell in a blood sample.
  • the cell analysis device further includes an imaging device, and the image receiving device 101 can also be connected to an imaging device (not shown in the figure), and the imaging device is configured to transmit a blood sample. And perform photoelectric conversion through the light of the lens group to form a digital image of the cells in the blood sample; the imaging device may be a part of the cell analysis device 100 or an external device of the cell analysis device 100.
  • the imaging device may be configured to photograph cells in the blood sample to form a digital image of the cells in the blood sample.
  • the display output device 102 is configured to output a digital image of the blood sample.
  • the processing device 103 is configured to perform corresponding processing or operation on the digital image of the cells in the blood sample according to the received voice information.
  • the processing device 103 is configured to select at least one cell in a digital image of the cells in the blood sample, and the selected at least one cell is in a selected state;
  • the display output device 102 is configured to output a selected state of at least one cell in the corresponding blood sample to the screen.
  • the display output device 102 is further configured to output a digital image of a cell in a blood sample and a pre-classification of the corresponding cell to a screen.
  • a digital image of cells in a blood sample and a pre-classification corresponding to the digital image can be output to a screen, so as to detect the pre-classification and avoid wrong classification information. .
  • the display output device 102 is further configured to output to the screen a digital image of the cells in the blood sample and target classification information of the cells; and the voice recognition device is configured to judge the When the approved type of the voice information is one of the target classifications, the approved type of the selected cell is determined according to the voice information. Specifically, the voice recognition device can determine whether the approved type of the voice information is One of the target classifications, the verified type of the cells includes: verifying at least one cell type in the target classification information; the approved type of the selected cell is one of the target classifications one. Among them, the verification type is one of the target classifications, which is verified by artificial speech, and the pre-classification is also one of the target classifications, which is realized through machine classification.
  • the display output device 102 is further configured to output to the screen a digital image of cells in the blood sample, target classification information of the cells, and pre-classification information of the cells; the voice The information is used to characterize the matching relationship between the pre-classification information of the verified cell and the target classification information of the cell.
  • the pre-classification information of the cell can be adjusted in time. In order to improve the accuracy of the cell analysis device to classify the cells to be detected.
  • the processing device 103 is further configured to identify at least one of the digital images of the cells in the blood sample before selecting at least one of the cells in the digital images of the blood sample.
  • the processing device 103 is further configured to pre-classify the at least one cell to the target classification information, thereby obtaining pre-classification information of at least one cell in a digital image of the cells in the blood sample.
  • the cell analysis device can implement pre-classification of cells to be detected according to target classification information.
  • the target classification information includes neutrophil neutrophils, neutrophil neutrophils, eosinophils, basophils, and lymphocytes.
  • the type of pre-classifying the cells may not be included in the target classification information.
  • the target classification lists 20 cell types, but the cell analysis device 100 may pre-classify some of the identified cells to
  • the cell category listed in the target classification can also be used to pre-classify the identified cells into categories other than the 20 cell categories listed in the target classification.
  • machine classification to which categories can the cell be pre-classified (machine classification), according to the cell analysis device Depending on the performance of 100.
  • the voice instruction is deemed to be related to The preset information or command does not match, and does not respond to the voice command.
  • the display output device 102 is further configured to output to the screen a classification region corresponding to at least one type included in the pre-classification, and the classification region includes images of cells belonging to the corresponding type in the blood sample.
  • a classification area belonging to at least one cell type can be displayed to a user, so as to implement batch inspection of cell classification results and improve inspection efficiency.
  • the pre-classification information uses at least one of text, graphics, a classification area, and a classification mark to indicate a type to which the cell belongs.
  • the target classification information at least one of text, graphics, classification area, or classification mark is used to indicate the type of cell belonging.
  • the imaging device is provided with a convex lens group (such as a microscope or other equipment with image magnification function), and different magnifications of the lens group are formed by the combination of different convex lenses, such as 100 times, 200 times, etc .;
  • the digital camera in the cell analysis device senses the light from the smear and the convex lens group in order, and forms a digital image of the enlarged cell through the principle of photoelectric conversion.
  • the digital camera and lens group move laterally with respect to the plane of the smear, which can be automatically moved by the controller of the cell analysis device, or can be manually controlled by various human-computer interaction methods. Digital image of smeared blood area.
  • the display output device may be implemented as a display screen for outputting digital images, and the size of the display screen may be flexibly selected according to the use environment of the cell analysis device.
  • the generated digital image can be displayed to the user.
  • an image interface is provided in the cell analysis device for outputting a digital image to a reading device connected to the cell analysis device through the image interface.
  • the types of image interfaces include, but are not limited to, an HDMI interface, a DVI interface, VGA interface, RGB interface, USB interface.
  • the display mode of the cells in the selected state can be distinguished from the display mode of the cells that have not obtained the selected state; for example, the brightness of the cells in the selected state is greater than that of the cells that are not in the selected state; or The display size of the cells is larger than the display size of the cells that are not in the selected state; or, the cells in the selected state have prompt text, symbols, or graphics, for example, a graphic element that surrounds the selected cells is output to the screen to prompt the user
  • the cells in this graphic element are in focus, making it easy for beginners to use.
  • the graphic element can have a dynamic effect, thereby having a high degree of recognition.
  • the position of the selected cell is in a set position on the screen, such as the center position of the screen.
  • the display output device 102 is further configured to output digital images of all cells in the blood sample to the screen.
  • digital images of all cells can be displayed on the screen, so that medical personnel can count the proportion of cells with abnormal morphology in all cells.
  • the display output device 102 is further configured to output to the screen an enlarged digital image of a cell of a set type among all the types involved in the pre-classification.
  • the display output device 102 is further configured to output a selected state corresponding to the target cell of the human-machine interactive operation to the screen in response to the human-machine interactive operation.
  • the manner of human-computer interaction includes, but is not limited to, a user issuing a control instruction through a click operation; or a voice operation control instruction to a cell analysis device; a user issuing a control instruction to the cell analysis device through a touch gesture.
  • the selected state is located at the position of the target cell, and forms that can be taken include, but are not limited to, the center position of the screen.
  • one or more cells selected according to human-computer interaction may be output at a time corresponding to the selected state of one or more cells.
  • a plurality of cells in a selected state can be output at one time according to the operation of the medical staff, so as to improve the reading efficiency.
  • the interactive operations include, but are not limited to, input / output device operations such as a mouse, keyboard, trackball, and the like.
  • input / output device operations such as a mouse, keyboard, trackball, and the like.
  • the display output device 102 is further configured to output a selected state switched between the cells of the blood sample to the screen in response to a human-computer interaction operation.
  • the display output device 102 is further configured to newly acquire the selected state cells after switching is any cell that has not acquired the selected state.
  • the cells may be sequentially output according to the arrangement relationship of the cells. Images of cells in adjacent positions that have never been selected.
  • the display output device 102 is further configured such that the newly acquired selected state cells after switching are any cells that have not acquired the selected state.
  • the cells can be fixed according to the arrangement position relationship of the cells. The number of cells at the corresponding position that have not yet obtained the selected state is output, or the cells that meet the display conditions among the cells that have not obtained the selected state are output at intervals.
  • the cells that have not obtained the selected state can be realized. Quickly find and display to increase the speed of reading.
  • the above-mentioned conditions may include: in order to select cells of the same type that have not obtained the selected state, that is, to select cells of the same type in the pre-classification, and when all types of cells have obtained the selected state, continue to select the type that has not obtained the selected state, Outputs the selected state switched in the corresponding cell type.
  • the above-mentioned conditions may include: in order to select according to the arrangement position of the cells in the blood sample, selecting cells adjacent to the cells that have released the selected state and have not achieved the selected state.
  • the display output device 102 is further configured to output a selected state of at least one cell belonging to the corresponding type in the blood sample to the screen in response to a human-machine interaction operation indicating a pre-classification type.
  • a human-machine interaction operation indicating a pre-classification type.
  • the display output device 102 is further configured to output a selected state of automatically switching between cells of a blood sample to a screen without waiting for a human-computer interaction instruction when obtaining a digital image.
  • the display output device 102 is further configured to switch the selected state in the corresponding one or more types of cells when the human-computer interaction operation indicates one or more types included in the pre-classification. .
  • the cell analysis device can be used in conjunction with The selected state is switched in the cells corresponding to the above five cell types, and the selected state is switched in turn in the cells to be selected corresponding to any of the above types of cells in order to improve the medical staff's re-examination of the cell image speed.
  • the directional switching of images of selected states of different types of cells can be implemented, so as to facilitate statistics of corresponding information of different types of cells.
  • the selected state has a set valid time, and in response to the valid time of the selected state reaching, a selected state corresponding to an unselected cell in the blood sample is output to the screen, so that the selected state on the screen is The cells switch.
  • the cells in focus state to be displayed can be automatically switched to achieve full automation of the re-examination process.
  • the display output device 102 is further configured to output the selected state of the corresponding cells to the screen one by one for the cells in the blood sample that have not been verified, and the selected state of each cell is maintained for a valid time. The switching is performed so that the medical staff can re-check the type of the exported cells.
  • a voice recognition device 104 configured to receive and recognize voice information
  • the voice recognition device 104 is configured to, when it is determined that the voice information is used to check the kind of the cell in the selected state, determine the checked kind of the cell in the selected state according to the voice information;
  • the speech recognition device 104 is configured to output the approved type of the cell in the selected state
  • the voice recognition device 104 is further configured to determine the pre-classification of the cells in the selected state when the pre-classification of the cells in the selected state is output to the screen and the voice operation is confirmed to confirm the pre-classification. For approved species.
  • the pre-classification of the cells in the selected state can be checked through voice operations.
  • the voice recognition device 104 is further configured to determine the pre-classification of the cells in the selected state as a check when a pre-classification of the cells in the selected state is output to the screen and a specific voice operation is recognized. kind of.
  • pre-classification of cells to be re-examined can be achieved through voice operations.
  • the specific voice operation includes: confirming a pre-categorized voice operation; or switching a voice operation of a cell in a selected state, wherein the cell in the selected state includes: a cell currently in a selected state is switched from the selected state to Unselected, another cell switches from unselected to selected.
  • the specific voice operation is to confirm the pre-classified voice operation
  • the re-examination of the cells is completed to confirm that the classification of the cells to be re-examined is correct
  • the specific voice operation is a voice operation to switch the selected cell
  • the display output device 102 is further configured to output to the screen the cells in the selected state that are in the corresponding category when determining the types of the cells in the selected state that are approved by the voice operation.
  • the voice recognition device 104 is further configured to cancel the type of the cell that has been verified by a voice operation.
  • the speech recognition device 104 is configured to cancel the type of the cell that has been verified through a voice operation
  • the previous classification result may be cleared through a voice operation to achieve errata for the existing cell classification.
  • the recognition voice information includes at least one of the following: performing continuous voice recognition; and initiating a voice recognition operation when the selected state is output.
  • the pre-classification uses at least one of text, graphics, classification area, and classification mark to indicate the type to which the cell belongs.
  • the voice recognition device 104 is further configured to classify cells in a selected state into a category approved by the voice information.
  • the working process of the speech recognition device 104 includes: when the pre-classification information of the selected cells is output to the screen, and the type approved by the voice information is different from the pre-classification of the cells in the selected state. , Changing the classification of the cells in the selected state to the type approved by the voice information. At this time, when the approved type of the voice information is different from the pre-classification of the cell in the selected state, it indicates that an error has occurred in the previous pre-classification.
  • the classification of the selected cells can be changed in time.
  • the voice recognition device 104 is further configured to keep the selected cells in the selected state when the type determined by the voice information is the same as the pre-classification of the cells in the selected state.
  • the pre-classification is unchanged.
  • the working process of the speech recognition device 104 includes: when outputting a pre-classification of the cells in the selected state to the screen, and recognizing that the type approved by the voice information is related to the pre-classification of the cells in the selected state At the same time, the pre-classification of the selected cells is maintained.
  • the voice recognition device is further configured to mark the cells in the blood sample whose type has been verified according to the voice information, so as to realize the timely marking of the corresponding cells in the blood sample which has been completed in the approved type, so as to facilitate The user can see which cells have already been approved for the species, and there is no need to double check.
  • the type approved by the voice information is the same as the pre-classification of the selected cell, which indicates that the previous pre-classification is correct, and the pre-classification of the selected cell can be improved without changing the pre-classification. Processing efficiency can also record the corresponding pre-classification process.
  • the voice recognition device 104 is further configured to classify the cells in a selected state into a type approved by the voice information.
  • the working process of the voice recognition device 104 includes: when the cells in the selected state are not pre-classified and the type approved by the voice information is recognized to the screen, the cells in the selected state are classified. Classify to the type approved by the voice information. At this time, because the pre-classification process may have missed classification, etc., when the type approved by the voice information is recognized, the selected cells are classified into the ones approved by the voice information.
  • the species can be used to classify cells without pre-classification in time.
  • the voice recognition device 104 is further configured to recognize that the pre-classification of the cells in the selected state remains unchanged when the voice information indicates that the cells in the selected state are switched.
  • the working process of the speech recognition device 104 includes: when the pre-classification of the cells in the selected state is output to the screen, and it is recognized that the voice information indicates switching of the cells in the selected state, maintaining the cells in the selected state The pre-classification of the cells is unchanged.
  • the voice information is instructed to switch the selected cells, the pre-classification of the cells in the selected state is kept unchanged, and adjacent selected cells are switched by a single voice instruction, while maintaining the The pre-classification of the corresponding cells is unchanged, which improves the operation speed of cell classification.
  • the voice recognition device 104 is further configured to enable the voice recognition function when it is recognized that there are cells in a selected state before recognizing the voice information. By recognizing that there are cells in the selected state, turning on the speech recognition function can avoid that when other cells in the selected state do not exist, the user's other voice information will interfere with the type verification of the corresponding cells.
  • the voice recognition device 104 is further configured to enable a voice recognition function before recognizing the voice information and when it is recognized that the artificial cell classification process is entered.
  • a voice recognition function when it is recognized that the artificial cell classification process is entered, turning on the voice recognition function can also avoid the interference of other voice information on the verification of the type of the corresponding cell when the selected cells are present but not entered into the artificial cell classification process.
  • the voice recognition device 104 is further configured to compare the acquired voice information with preset information or instructions; when corresponding to the preset information or instructions, responding to the voice information ; When it does not correspond to the preset information or instruction, it does not respond to the voice information.
  • the voice recognition device 104 will respond; other information is related to the preset information or instruction. Inconsistent voice information, such as chat information, noise, etc., will not be responded to, or the aforementioned voice instructions, if spoken in a nonstandard way, will not respond to preset information or instructions.
  • the parameters of the corresponding voice information can be set in advance.
  • the voice information is received, the The acquired voice information is compared with preset characteristic parameters of the approved kind of voice; when corresponding to the corresponding parameter, the voice information is responded to, thereby improving the accuracy of the cell classification operation.
  • the storage device 105 is configured to store an approved type of the selected cell.
  • the application environment is that multiple people recheck the same cell image at the same time, the specific voice operation comes from at least two users, and the voice recognition device 104 is configured to recognize the voice operations of at least two users, and Determine the types of cells in the selected state that are approved by different users' voice operations.
  • the corresponding storage device 105 is configured to store the type approved by each user for the same cell, respectively. For example, when multiple people perform a re-examination on a selected cell at the same time, different people verify the type of the cell through voice information, and the speech recognition device 104 of the cell analysis device can recognize and record each person's approved type of the cell.
  • the display output device 102 can collectively output all the judgment results for comparison.
  • the speech recognition device 104 of the cell analysis device can recognize and record the cells that have been judged as neutral lobulated neutrophils. The number of times, or the number of times it has been determined to be eosinophils can be identified and recorded.
  • the cell analysis device can record the classification results of the same cell by multiple people and record them for review after completing the re-examination.
  • the specific voice operation includes the voice operations of at least two persons
  • the voice recognition device 104 is configured to recognize the voice operations of at least two persons and determine the types of cells selected by the voice operation in the selected state, respectively. .
  • the voice recognition device 104 is further configured to obtain the operation authority value of different users, and the corresponding storage device 105 is configured to separately store information corresponding to each voice operation, and at the same time it will be associated with the highest operation authority value.
  • the corresponding information is marked for priority display.
  • the cell analysis device can be implemented by the intern doctor under the guidance of the instructor. In the process of classifying cells by the cell analysis device, the cell analysis device recognizes the voice operation of the intern doctor. , It can be given a lower authority value, and it can be given a higher authority value after the voice operation of the instructor is recognized. After the classification work is completed (or at the same time), the instructor can check it and correct the error in time. The system makes corrections based on the judgments made by users with higher authority values, and records and outputs the entire process for teaching reference.
  • the display output device is further configured to output the classification statistical information of the cells in the blood sample after verifying the cell type through voice information, so that the user can accurately understand the classification of the cells in the blood sample.
  • the voice recognition device is configured to determine the blood sample according to the voice information when it is determined that the voice information is used to count the number of cells in the blood sample.
  • the number of cells is counted.
  • the process of determining the number of cells in the blood sample according to the voice information may include: (1) dividing the image of the blood sample into several counting units having the same area, and dividing the divided Each counting unit is numbered. (2) The corresponding numbered statistical cells are selected by the processing device 103, and the cell number information is sent to the speech recognition device 104; further, a certain numbered statistical cells may also be selected by corresponding voice instructions.
  • the speech recognition device 104 recognizes the cell number information characterized by the corresponding voice instruction, and fills it into the corresponding numbered statistical cells to complete the cell number statistics. Therefore, the user does not need to perform manual operations in the process of counting cell numbers by voice instructions, and the entire statistics process is controlled by voice instructions, which reduces the user's operation burden.
  • the image receiving device 101 and the display output device 102 may be implemented by a display
  • the voice recognition device 104 may be implemented by a controller
  • the storage device 105 may be implemented by a memory.
  • the cell analysis device further includes:
  • the imaging device is configured to photograph cells in the blood sample to form a digital image of the cells in the blood sample.
  • the slide-staining machine formed by integrating the staining machine and the slide-setter can push the smear of blood cells that have undergone the staining process to the imaging device, and the imaging device can photograph the cells in the blood sample. To form a digital image of the cells in the blood sample.
  • FIG. 2 is an optional flowchart of a cell analysis method provided by an embodiment of the present invention.
  • the cell analysis method provided by an embodiment of the present invention is applied to a cell analysis device.
  • the cell analysis device includes an image receiving device, a display output device, and a voice recognition device. And storage.
  • an optional flowchart of the cell analysis method provided in the embodiment of the present invention describes the steps shown.
  • Step 201 Obtain a digital image of the cells in the blood sample.
  • Step 202 Output a digital image of the cells in the blood sample.
  • the digital image of the cells in the received blood sample may be a digital image of the cell obtained by an external device, or may be formed by an imaging device carried by the cell analysis device.
  • the cell analysis device may include an imaging device, which forms a digital image of cells in the blood sample by transmitting the blood sample and performing photoelectric conversion through the light of the lens group.
  • outputting a digital image to the screen includes: outputting an enlarged digital image of a cell in a blood sample to the screen, and pre-classifying the corresponding cell.
  • outputting a digital image of a cell in a blood sample and a pre-classification of the corresponding cell to the screen includes: outputting to the screen a classification region corresponding to at least one category included in the pre-classification, and the classification region includes blood.
  • An image of a cell belonging to the corresponding species in the sample is displayed to a user, so as to implement batch inspection of cell classification results and improve inspection efficiency.
  • the outputting or storing the digital image of the blood sample includes: outputting to the screen a digital image of the cells in the blood sample and target classification information of the cells; and identifying the voice.
  • Information, when it is determined that the voice information is used to check the type of the cell in the selected state, determining the checked type of the cell in the selected state based on the voice information includes:
  • the approved type of the selected cell is determined according to the voice information, wherein the approved type of the cells includes: classification information of the target At least one of the selected cell types is checked; the checked type of the selected cells is one of the target classifications.
  • the verification type is one of the target classifications, which is verified by artificial speech, and the pre-classification is also one of the target classifications, which is realized through machine classification.
  • the outputting the digital image of the blood sample includes: outputting to the screen a digital image of the cells in the blood sample, target classification information of the cells, and pre-classification information of the cells;
  • the voice information is used to characterize the matching relationship between the pre-classification information of the cell and the target classification information of the cell.
  • the cell analysis device before selecting at least one cell in a digital image of a cell in the blood sample, identifying at least one cell in a digital image of a cell in the blood sample; Classify to the target classification information, thereby obtaining pre-classification information of at least one cell in a digital image of the cells in the blood sample.
  • the cell analysis device can implement pre-classification of cells to be detected according to target classification information.
  • the pre-classification information uses at least one of text, graphics, classification area, and classification mark to indicate the type of the cell; the target classification information uses text, graphics, classification area, or classification mark. At least one indicates the type to which the cell belongs.
  • a convex lens group (such as a microscope) is provided in the cell analysis device, and different magnifications of the lens group are formed by the combination of different convex lenses, for example, 100 times, 200 times, etc .;
  • the digital camera in the cell analysis device senses the light from the smear and the convex lens group in sequence, and forms a digital image of the enlarged cell through the principle of photoelectric conversion.
  • the digital camera and lens group move laterally relative to the plane of the smear, which can be automatically moved by the controller of the cell analysis device, or can be manually controlled by various human-computer interaction methods, so as to capture the smear.
  • Digital image of smeared blood area Through the technical solution shown in the embodiment of the present invention, an image of a cell to be observed can be obtained automatically.
  • a display screen is provided in the cell analysis device for outputting a digital image.
  • the generated digital image can be displayed to the user.
  • an image interface is provided in the cell analysis device, and is configured to output a digital image to a reading device connected to the cell analysis device through the image interface.
  • the display mode of the cells in the selected state may be different from the display mode of the cells that have not obtained the selected state; for example, the display size of the cells in the selected state is larger than the display size of the cells in the selected state.
  • the cells in the selected state have prompt text, symbols or graphics, for example, a graphic element surrounding the selected cells is output to the screen to remind the user that the cells in the graphic element are in focus, which is convenient for beginners to use .
  • the graphic element can have a dynamic effect, thereby having a high degree of recognition.
  • the position of the cell in the selected state is at a set position in the screen, such as the center position of the screen.
  • outputting a digital image of the blood sample to the screen includes outputting a digital image of all cells in the blood sample to the screen.
  • digital images of all cells can be displayed on the screen, so that medical personnel can count the proportion of cells with abnormal morphology in all cells.
  • outputting the digital image of the blood sample to the screen includes: outputting to the screen an enlarged digital image of a cell of a set type among all the types involved in the pre-classification.
  • Step 203 Select at least one cell in the digital image of the cells in the blood sample, and the selected at least one cell is in a selected state.
  • outputting the selected state of at least one cell in the blood sample to the screen includes: outputting the selected state corresponding to the target cell of the human-computer interactive operation to the screen in response to the human-computer interactive operation.
  • the selected state is located at the position of the target cell, and forms that can be taken include, but are not limited to, the center position of the screen.
  • one or more selected cells can be output according to human-computer interaction operation, and the selected state corresponding to one or more cells is output at one time.
  • the technical solution shown in the embodiment of the present invention it can be achieved that a plurality of cells in a selected state are output at one time according to the operation of the medical staff, so as to improve the reading efficiency.
  • the interactive operations include, but are not limited to, input / output device operations such as a mouse, keyboard, trackball, and the like.
  • input / output device operations such as a mouse, keyboard, trackball, and the like.
  • outputting the selected state of at least one cell in the blood sample to the screen includes: outputting the selected state switched between the cells of the blood sample to the screen in response to a human-computer interaction operation.
  • outputting the selected state of at least one cell in the blood sample to the screen includes: the newly obtained selected state cell after switching is any cell that has not obtained the selected state, or has not obtained the selected state Eligible cells.
  • the selection according to the conditions includes: in order to select cells of the same type that have not obtained the selected state, that is, to select cells of the same type in the pre-classification, and when cells of the same type have achieved the selected state, the selection is continued.
  • the type of the selected state outputs the selected state switched in the corresponding type of cells.
  • the selecting according to the conditions includes: for selecting according to the arrangement position of the cells in the blood sample, selecting among cells adjacent to the cells that release the selected state and have not achieved the selected state.
  • outputting the selected state of at least one cell in the blood sample to the screen includes: outputting at least one of the blood sample belonging to the corresponding type to the screen in response to a human-computer interaction instruction indicating the type of the pre-classification.
  • the selected state of the cell includes: outputting at least one of the blood sample belonging to the corresponding type to the screen in response to a human-computer interaction instruction indicating the type of the pre-classification.
  • the selected state of the cell includes: outputting at least one of the blood sample belonging to the corresponding type to the screen in response to a human-computer interaction instruction indicating the type of the pre-classification.
  • the selected state of the cell includes: outputting at least one of the blood sample belonging to the corresponding type to the screen in response to a human-computer interaction instruction indicating the type of the pre-classification.
  • the selected state of the cell includes: outputting at least one of the blood sample belonging to the corresponding type to the screen in response to a human-computer interaction instruction indicating the type of the pre-classification.
  • outputting the selected state of at least one cell in the blood sample to the screen includes outputting the selected state that is automatically switched between the cells of the blood sample to the screen.
  • outputting the selected state switched between the cells of the blood sample to the screen includes: when the human-computer interactive operation indicates one or more types included in the pre-classification, and the corresponding one or more The selected state is switched in each type of cell.
  • the selected state has a set valid time, and in response to the valid time of the selected state reaching, a selected state corresponding to an unselected cell in the blood sample is output to the screen, so that the selected state on the screen is The cells switch.
  • the cells in focus state to be displayed can be automatically switched to achieve full automation of the re-examination process.
  • the selected state of the corresponding cell is output to the screen one by one, and the selected state of each cell is switched after the valid time, so that medical personnel can The type of the exported cells is re-checked.
  • Step 204 Receive and recognize voice information, and when it is determined that the voice information is used to check the type of the cell in the selected state, determine the checked type of the cell in the selected state according to the voice information.
  • the determining the approved type of the cells in the selected state according to the voice information includes: when a pre-classification of the cells in the selected state is output to the screen, and the voice information
  • the classification of the cells in the selected state is changed to the type approved by the voice information.
  • the approved type of the voice information is different from the pre-classification of the cell in the selected state, it indicates that an error has occurred in the previous pre-classification.
  • the classification of the selected cells can be changed in time.
  • the determining the approved type of the cell in the selected state according to the voice information includes: when a pre-classification of the cell in the selected state is output to the screen, and the identified When the type determined by the voice information is the same as the pre-classification of the cells in the selected state, the pre-classification of the cells in the selected state is kept unchanged. Further, the cells in the blood sample whose type has been verified according to the voice information may be labeled. At this time, it is recognized that the type approved by the voice information is the same as the pre-classification of the selected cell, which indicates that the previous pre-classification is correct, and the pre-classification of the selected cell can be improved without changing the pre-classification.
  • the processing efficiency can also record the corresponding pre-classification process to facilitate the self-learning of the cell analysis device.
  • the determining the approved type of the cell in the selected state according to the voice information includes: when the cell in the selected state is output to the screen and is not pre-classified, and When the type approved by the voice information, the selected cells are classified into the type approved by the voice information. At this time, because the pre-classification process may have missed classification, etc., when the type approved by the voice information is recognized, the selected cells are classified into the ones approved by the voice information.
  • the species can be used to classify cells without pre-classification in time.
  • the determining the approved type of the cell in the selected state according to the voice information includes: when a pre-classification of the cell in the selected state is output to the screen, and the identified The voice information indicates that when the cells in the selected state are switched, the pre-classification of the cells in the selected state is kept unchanged.
  • the voice information is instructed to switch the selected cells, the pre-classification of the cells in the selected state is kept unchanged, and adjacent selected cells are switched by a single voice instruction, while maintaining the The pre-classification of the corresponding cells is unchanged, which improves the operation speed of cell classification.
  • a voice recognition function is turned on before identifying the voice information.
  • a voice recognition function is turned on. By recognizing that there are cells in the selected state, turning on the speech recognition function can avoid that when other cells in the selected state do not exist, the user's other voice information will interfere with the type verification of the corresponding cells.
  • a voice recognition function is enabled.
  • turning on the voice recognition function can also avoid the interference of other voice information on the verification of the type of the corresponding cell when the selected cells are present but not entered into the artificial cell classification process.
  • the identifying the voice information includes: comparing the acquired voice information with a preset characteristic parameter of an approved type of voice; when the acquired voice information corresponds to the preset information or instruction , It responds to the voice information; when the acquired voice information does not correspond to preset information or instructions, the voice information is not responded.
  • the preset information or instructions may be integrated into the voice recognition device 104.
  • the parameters of the corresponding voice information can be set in advance.
  • the voice information is received, the The acquired voice information is compared with preset characteristic parameters of the approved kind of voice; when corresponding to the corresponding parameter, the voice information is responded to, thereby improving the accuracy of the cell classification operation.
  • recognizing the voice information to obtain the approved type of the cells in the selected state includes: when a pre-classification of the cells in the selected state is output to the screen, and a voice operation is confirmed to confirm the pre-classification, It is determined that the cells in the selected state are pre-classified as an approved species.
  • the pre-classification of the cells in the selected state can be checked through voice operations.
  • recognizing voice information to obtain an approved type of cells in a selected state includes: when a pre-classification of cells in a selected state is output to a screen, and a specific voice operation is recognized, determining the The pre-classified cells of the selected state are of the approved type.
  • the specific voice operation includes at least one of the following: confirming a pre-classified voice operation; switching a voice operation of a cell in a selected state.
  • the type of the cell in the selected state determined by the voice operation when the type of the cell in the selected state determined by the voice operation is determined, it is output to the screen that the cell in the selected state is in the classification region of the corresponding type.
  • the type of cells that have been approved is canceled by a voice operation.
  • the recognition voice information includes at least one of the following: performing continuous voice recognition; and initiating a voice recognition operation when the selected state is output.
  • the method further includes:
  • the classification statistical information of the cells in the blood sample is output, so that the user can accurately understand the classification of the cells in the blood sample.
  • the number of cells in the blood sample is determined to be counted according to the voice information.
  • the process of determining the number of cells in the blood sample according to the voice information may include: (1) dividing the image of the blood sample into several counting units having the same area, and counting each of the divided Units are numbered. (2) A corresponding numbered statistical cell is selected by the processing device 103, and a voice instruction characterizing the number of cells is issued to the voice recognition device 104. Further, a certain numbered statistical cell may be selected by the corresponding voice instruction.
  • the speech recognition device 104 recognizes the cell number information characterized by the corresponding voice instruction, and fills it into the corresponding numbered statistical cells to complete the cell number statistics. Therefore, the user does not need to perform manual operations in the process of counting cell numbers by voice instructions, and the entire statistics process is controlled by voice instructions, which reduces the user's operation burden.
  • Step 205 Output or store the approved type of the selected cells.
  • FIG. 3 is a schematic diagram of an optional structure of a cell analysis device according to an embodiment of the present invention. As shown in FIG. 3, an optional structure diagram of a cell analysis device provided by an embodiment of the present invention. The modules are described separately.
  • the accommodating portion 301 is configured to accommodate one or more smears at one time.
  • the digital imaging device 308 includes a first objective lens 304, a second objective lens 305, a third objective lens 306, an eyepiece 307, and a digital camera 310.
  • the voice recognition device 309 is configured to recognize voice information and determine a type of a cell selected in a selected state by voice operations.
  • the voice recognition device 309 may be provided in the digital imaging device 308.
  • FIG. 4A is a schematic diagram of image display in a cell analysis method according to an embodiment of the present invention.
  • images of cells in multiple fields of a smear can be output to the display area at one time, and the output can be performed by voice operations
  • the classification of cells was verified and errata.
  • medical personnel can conveniently observe the images of cells in multiple fields of the smear in one display area at a time, which is more convenient for them to count the proportion of diseased cells, and can also pass Speech manipulation reclassifies cells that have been misclassified.
  • FIG. 4B is a schematic diagram of the cell counting work performed by the cell analysis device according to the embodiment of the present invention.
  • the number of platelets PKT
  • FIG. 4B when the number of platelets (PLT) can be counted by the cell analysis device, first, the blood sample The images of platelet cells are divided into several counting units with the same area, and each divided counting unit is numbered. As shown in FIG. 4B, the image of the platelet cells of the blood sample is divided into 16 count areas with the same area, and the number of platelet cells in each area is counted.
  • FIG. 4C is a schematic diagram of cell counting performed by the cell analysis device according to the embodiment of the present invention.
  • the corresponding number is selected by the processing device A statistical cell, and send a voice instruction to the voice recognition device to characterize the number of platelet cells.
  • the speech recognition device recognizes the cell number information characterized by the corresponding voice instruction and fills it into the corresponding numbered statistical cells to complete the counting of the number of platelet cells.
  • FIG. 5 is a schematic diagram of an optional structure of a cell analysis device according to an embodiment of the present invention.
  • the cell analysis device 500 may include a medical device with a cell classification function, a portable analyzer, and the like.
  • the cell analysis device 500 shown in FIG. 5 includes at least one processor 501, a memory 502, at least one network interface 504, and a user interface 503.
  • the various components in the cell analysis device 500 are coupled together via a bus system 505.
  • the bus system 505 is configured to implement connection and communication between these components.
  • the bus system 505 includes a data bus, a power bus, a control bus, and a status signal bus. However, for the sake of clarity, various buses are marked as the bus system 505 in FIG. 5.
  • the user interface 503 may include a display, a keyboard, a mouse, a trackball, a click wheel, keys, buttons, a touch panel, or a touch screen.
  • the memory 502 may be a volatile memory or a non-volatile memory, and may also include both volatile and non-volatile memories.
  • the non-volatile memory may be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), or an erasable programmable read-only memory (EPROM, Erasable Programmable Read- Only Memory), Electrically Erasable and Programmable Read-Only Memory (EEPROM), Magnetic Random Access Memory (FRAM, ferromagnetic random access memory), Flash Memory (Flash Memory), Magnetic Surface Memory , Compact disc, or read-only compact disc (CD-ROM, Compact Disc-Read-Only Memory); the magnetic surface memory can be a disk memory or a tape memory.
  • the volatile memory may be random access memory (RAM, Random Access Memory), which is used as an external cache.
  • RAM random access memory
  • RAM Random Access Memory
  • many forms of RAM are available, such as Static Random Access Memory (SRAM, Static Random Access Memory), Synchronous Static Random Access Memory (SSRAM, Static Random Access, Memory), Dynamic Random Access DRAM (Dynamic Random Access Memory), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM, Double Data Rate Synchronous Dynamic Random Access Memory), enhanced Type Synchronous Dynamic Random Access Memory (ESDRAM, Enhanced Random Dynamic Access Memory), Synchronous Link Dynamic Random Access Memory (SLDRAM, Sync Link Dynamic Random Access Memory), Direct Memory Bus Random Access Memory (DRRAM, Direct Rambus Random Access Memory).
  • SRAM Static Random Access Memory
  • SSRAM Synchronous Static Random Access Memory
  • SDRAM Synchronous Dynamic Random Access Memory
  • DDRSDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • the memory 502 in the embodiment of the present invention includes, but is not limited to, tri-state content addressable memory and static random access memory capable of storing various types of data such as cell images, cell classification information, and voice operations to support the operation of the cell analysis device 500.
  • data include: any computer program for operating on the cell analysis device 500, such as an operating system 5021 and an application 5022, a cell image, a usage record, cell classification information, and the like.
  • the operating system 5021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks.
  • the application program 5022 may include various applications, such as a client with a cell classification function, or an application program, etc., and is used to implement photoelectric conversion of light transmitted through a blood sample and passing through a lens group to form cells in the blood sample.
  • Digital image Digital image of blood sample is output to the screen; Selected state of at least one cell in the corresponding blood sample is output to the screen; Recognize voice information to determine the type of cell selected by the voice operation; Stored in the selected state Business of various applications including the approved type of cells.
  • a program for implementing the cell analysis method according to the embodiment of the present invention may be included in the application program 5022.
  • the method disclosed in the foregoing embodiment of the present invention may be applied to the processor 501, or implemented by the processor 501.
  • the processor 501 may be an integrated circuit chip and has a signal processing capability. In the implementation process, each step of the above method may be completed through operations in the form of hardware integrated logic circuits or software in the processor 501.
  • the aforementioned processor 501 may be a general-purpose processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like.
  • DSP Digital Signal Processor
  • the processor 501 may implement or execute various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention.
  • a general-purpose processor may be a microprocessor or any conventional processor.
  • the steps of the method disclosed in the embodiments of the present invention can be directly implemented as a hardware decoding processor, or can be performed by using a combination of hardware and software modules in the decoding processor.
  • the software module may be located in a storage medium.
  • the storage medium is located in the memory 502.
  • the processor 501 reads the information in the memory 502 and completes the steps of the foregoing method in combination with its hardware.
  • the cell analysis device 500 may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable Logic Devices (PLDs), and Complex Programmable Logic Devices (PLDs).
  • ASICs Application Specific Integrated Circuits
  • DSPs Programmable Logic Devices
  • PLDs Programmable Logic Devices
  • PLDs Complex Programmable Logic Devices
  • CPLD Complex, Programmable, Logic, Device
  • FPGA Field Programmable Gate Array
  • FPGA Field-Programmable Gate Array
  • general-purpose processor controller, microcontroller (MCU, Microcontroller Unit), microprocessor (Microprocessor), or other Electronic component implementation for performing cellular analysis methods.
  • MCU microcontroller
  • Microcontroller Unit Microcontroller Unit
  • Microprocessor Microprocessor
  • an embodiment of the present invention further provides a computer-readable storage medium, such as a memory 502 including a computer program, and the computer program may be executed by the processor 501 of the cell analysis apparatus 500 to complete the foregoing method steps.
  • the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disk, or CD-ROM, or various devices including one or any combination of the above memories, such as Portable analyzers and more.
  • An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon.
  • the computer program executes: photoelectrically converting light transmitted through a blood sample and passing through a lens group to form blood. Digital images of cells in the sample; output digital images of blood samples to the screen; output selected states corresponding to at least one cell in the blood sample to the screen; recognize voice information to determine the type of cells in the selected state that are approved by voice operations; Stores the selected type of cells in the selected state.
  • the embodiments of the present invention may be provided as a method, a system, or a computer program product. Therefore, the embodiments of the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including magnetic disk memory, optical memory, and the like) containing computer-usable program code.
  • computer-usable storage media including magnetic disk memory, optical memory, and the like
  • Embodiments of the present invention are described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and combinations of processes and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program operations.
  • These computer program operations may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to work in a particular manner such that the operations stored in the computer-readable memory produce a manufactured article including a processing device, the processing The device implements the functions specified in one or more flowcharts and / or one or more blocks of the block diagram.

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Abstract

La présente invention concerne un procédé d'analyse de cellules, un dispositif d'analyse de cellules (100) et un support de stockage. Le procédé d'analyse de cellules comprend : l'acquisition d'une image numérique de cellules dans un échantillon de sang (201) ; la délivrance en sortie de l'image numérique des cellules dans l'échantillon de sang (202) ; la réception d'informations vocales ; et la conduite, en fonction des informations vocales reçues, d'un traitement correspondant ou d'une opération correspondante par rapport à l'image numérique des cellules dans l'échantillon de sang (204).
PCT/CN2018/098369 2018-08-02 2018-08-02 Procédé d'analyse de cellules, dispositif d'analyse de cellules et support de stockage WO2020024227A1 (fr)

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CN201880088546.3A CN111684279B (zh) 2018-08-02 2018-08-02 一种细胞分析方法、细胞分析装置及存储介质

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CN105210083A (zh) * 2013-03-15 2015-12-30 霍罗杰克股份有限公司 用于查验和分析细胞学标本的系统和方法
CN104850860A (zh) * 2015-05-25 2015-08-19 广西师范大学 细胞图像识别方法及细胞图像识别装置

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CN116385443A (zh) * 2023-06-06 2023-07-04 珠海横琴圣澳云智科技有限公司 基于图像的样本质量确定方法和装置
CN116385443B (zh) * 2023-06-06 2023-08-11 珠海横琴圣澳云智科技有限公司 基于图像的样本质量确定方法和装置

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