JP2019197500A - Diagnosis support device, diagnosis support system, display control device, diagnosis support method, and diagnosis support program - Google Patents

Abstract

To provide a diagnosis support device capable of assigning an appropriate radiographer to a medical image obtained by photographing an animal and also to provide a diagnosis support system, a display control device, a diagnosis support method and a diagnosis support program.SOLUTION: A diagnosis support device includes: an acquisition part for acquiring a medical image obtained by photographing animal to be interpreted; and an allocation part for assigning a radiographer to the medical image according to information on animal species including at least one of the species and breed of the animal to be interpreted. The diagnosis support device further includes an estimation part for estimating at least one of the species and breed using at least one of the medical image and an optical image obtained by optically photographing the animal to be interpreted.SELECTED DRAWING: Figure 8

Description

  The present disclosure relates to a diagnosis support apparatus, a diagnosis support system, a display control apparatus, a diagnosis support method, and a diagnosis support program.

  Conventionally, selection of a medical image requesting interpretation, input of image-related information including at least one of a target part of a subject of a medical image and a corresponding case, and selection of an interpretation request destination requesting interpretation are performed on the distribution server. A terminal that transmits a medical image and image-related information is disclosed (see Patent Document 1). In this technique, the distribution server determines whether or not the target part or the corresponding case of the medical image is included in the specialized field of the interpretation request destination. Further, the distribution server determines whether to distribute the medical image to the interpretation request destination terminal based on the determination result, or to cancel the distribution of the medical image.

  Further, there is a technique for storing distribution characteristic information including information indicating the attributes of medical image data and information indicating the stage of interpretation, and receiving a value corresponding to the stored distribution characteristic information for each interpretation doctor. It is disclosed (see Patent Document 2). In this technology, an interpreting doctor who is in charge of interpretation regarding an interpretation request, and when determining an interpretation doctor in charge of interpretation at an arbitrary stage, information indicating the attribute of medical image data corresponding to the interpretation request, and an arbitrary The distribution characteristic information is specified using the information indicating the stage. In this technique, an interpreting doctor at an arbitrary stage is determined based on a value for each interpreting doctor corresponding to the specified distribution characteristic information.

  Also, it receives attribute information indicating the type or breed of the animal that provided the specimen, measures the specimen, obtains physical property value information that is the final measurement result of the specimen, and associates the physical property value information with the attribute information in the center. A terminal that transmits to a device is disclosed (see Patent Document 3). In this technique, the central device receives attribute information and physical property value information associated with the attribute information from a plurality of terminals, stores the received physical property value information and attribute information, and stores the stored physical property value information and Output attribute information.

JP 2014-48824 A JP 2017-187869 A JP 2009-145115 A

  By the way, since the body shape and size of animals vary greatly depending on the race, breed, etc., it is required to assign an appropriate reader for interpretation of medical images and perform specialized interpretation. However, in the techniques described in Patent Documents 1 to 3, no consideration is given to assigning an appropriate image interpreter to medical images obtained by photographing animals according to the race, breed, or the like.

  The present disclosure has been made in view of the above circumstances, and is a diagnosis support apparatus, a diagnosis support system, a display control apparatus, and a diagnosis that can assign an appropriate image interpreter to a medical image obtained by photographing an animal. An object is to provide a support method and a diagnosis support program.

  In order to achieve the above object, a diagnosis support apparatus according to the present disclosure includes an acquisition unit that acquires a medical image obtained by photographing an animal to be interpreted, and at least one of a race and a breed of the animal to be interpreted. An assigning unit that assigns a radiogram interpreter to the medical image according to the animal species information included.

  Note that the diagnosis support apparatus of the present disclosure includes an estimation unit that estimates at least one of an animal race and a breed using at least one of a medical image and an optical image obtained by optically photographing an animal to be interpreted. Further, it may be provided.

  In the diagnosis support apparatus according to the present disclosure, the acquisition unit may further acquire a test result of an animal sample to be interpreted.

  In the diagnosis support apparatus of the present disclosure, the specimen may be at least one of blood, urine, saliva, and corneal cells.

  The diagnosis support apparatus according to the present disclosure may further include a second estimation unit that estimates a disease in which an animal to be interpreted is likely to be affected using the animal species information, the medical image, and the examination result.

  In the diagnosis support apparatus according to the present disclosure, the allocating unit may allocate a radiogram interpreter to the medical image according to the disease estimated by the second estimating unit in addition to the animal species information.

  In order to achieve the above object, a diagnosis support system according to the present disclosure includes a first acquisition unit that acquires a medical image obtained by photographing an animal to be interpreted, and at least a race and a breed of the animal to be interpreted. An allocating unit that assigns an interpreter to a medical image according to animal species information including one, and a diagnosis support apparatus including information that can determine the size of the medical image and the animal to be interpreted from the diagnosis support apparatus. Using the second acquisition unit to be acquired and the medical image acquired by the second acquisition unit and the information capable of discriminating the size of the animal, information for visually recognizing the medical image and the size of the animal is displayed on the display unit. And a display control unit that performs control.

  In the diagnosis support system of the present disclosure, the diagnosis support apparatus can determine the size of the animal using the size and resolution of the imaging surface of the imaging apparatus used for imaging the medical image and the number of pixels of the medical image. You may further provide the derivation | leading-out part which derives | leads-out information.

  In order to achieve the above object, a display control device of the present disclosure includes a medical image obtained by photographing an animal to be interpreted, and an acquisition unit that obtains information capable of determining the size of the animal to be interpreted. A display control unit that performs control to display the medical image and the information that can visually recognize the size of the animal on the display unit, using the medical image acquired by the acquisition unit and the information that can determine the size of the animal. I have.

  In order to achieve the above object, the diagnosis support method of the present disclosure acquires a medical image obtained by photographing an animal to be interpreted, and includes an animal species including at least one of the species and breed of the animal to be interpreted. The computer executes a process of assigning a radiogram interpreter to the medical image according to the information.

  In order to achieve the above object, the diagnostic support program of the present disclosure acquires a medical image obtained by photographing an animal to be interpreted, and includes at least one of the race and breed of the animal to be interpreted. This is for causing a computer to execute a process of assigning a radiogram interpreter to a medical image according to animal species information.

  According to the present disclosure, it is possible to assign an appropriate image interpreter to a medical image obtained by photographing an animal.

It is a block diagram which shows an example of a structure of the diagnosis assistance system which concerns on embodiment. It is a block diagram which shows an example of the hardware constitutions of the diagnostic assistance apparatus which concerns on embodiment. It is a figure which shows an example of the radiogram interpreter table which concerns on embodiment. It is a figure for demonstrating the radiographer table which concerns on embodiment. It is a figure which shows an example of the animal species estimation model which concerns on embodiment. It is a figure which shows an example of the disease estimation model which concerns on embodiment. It is a block diagram which shows an example of the hardware constitutions of the display control apparatus which concerns on embodiment. It is a block diagram which shows an example of a functional structure of the diagnosis assistance apparatus which concerns on embodiment. It is a block diagram which shows an example of a functional structure of the display control apparatus which concerns on embodiment. It is a flowchart which shows an example of the allocation process which concerns on embodiment. It is a flowchart which shows an example of the display process which concerns on embodiment. It is a figure which shows an example of the display screen of the medical image which concerns on embodiment.

  Hereinafter, exemplary embodiments for carrying out the technology of the present disclosure will be described in detail with reference to the drawings.

  First, the configuration of a diagnosis support system 10 according to the present embodiment will be described with reference to FIG. As shown in FIG. 1, the diagnosis support system 10 includes a diagnosis support device 12 and a plurality of display control devices 14. The diagnosis support apparatus 12 receives a request for interpretation of a medical image obtained by photographing an animal to be interpreted from an animal hospital. In addition to the interpretation request, the animal hospital transmits the identification information of the animal to be interpreted, imaging information including the imaging region and the like, and a medical image to the diagnosis support apparatus 12. The medical image is an image obtained by imaging using a radiographic image capturing apparatus such as a DR (Digital Radiography) cassette, an MRI (Magnetic Resonance Imaging) apparatus, and an ultrasonic diagnostic apparatus. For example, information regarding the imaging apparatus such as the identification information of the imaging apparatus, the size of the imaging surface such as the size of the radiation detection surface in the DR cassette, and the resolution is added to the medical image as attribute information.

  Furthermore, from the animal hospital, together with an interpretation request, a test result obtained by testing blood as an example of an animal sample is also transmitted to the diagnosis support apparatus 12. Animal specimens are not limited to blood, and may contain at least one of blood, urine, saliva, and corneal cells.

  The display control device 14 is provided for each radiogram interpreter who interprets a medical image. The diagnosis support apparatus 12 and each display control apparatus 14 are connected to the network N so as to be communicable with each other.

  Next, the hardware configuration of the diagnosis support apparatus 12 according to the present embodiment will be described with reference to FIG. As shown in FIG. 2, the diagnosis support apparatus 12 includes a CPU (Central Processing Unit) 20, a memory 21 as a temporary storage area, and a nonvolatile storage unit 22. The diagnosis support apparatus 12 includes a display unit 23 such as a liquid crystal display, an input unit 24 such as a keyboard and a mouse, and a network I / F (InterFace) 25 connected to the network N. The CPU 20, the memory 21, the storage unit 22, the display unit 23, the input unit 24, and the network I / F 25 are connected to the bus 26. Examples of the diagnosis support apparatus 12 include a server computer and a cloud server.

  The storage unit 22 is realized by an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, or the like. The storage unit 22 as a storage medium stores a diagnosis support program 30, an interpreter table 32, an animal species estimation model 34, and a disease estimation model 36. The CPU 20 reads out the diagnostic support program 30 from the storage unit 22, expands it in the memory 21, and executes the expanded diagnostic support program 30.

  FIG. 3 shows an example of the radiogram interpreter table 32. As shown in FIG. 3 and FIG. 4, the radiogram interpreter table 32 includes, for each radiogram interpreter, the species and breed of an interpretable animal, and the site and disease that are good at radiogram interpretation according to the radiographer's experience and ability. Is memorized. It should be noted that an interpreter whose “ALL” is stored in the race column, breed column, site column, and disease column of the interpreter table 32 can interpret medical images of all races and breeds, and can store all sites. And that they are good at interpreting diseases.

  Further, in the radiogram interpreter table 32, the necessity of secondary interpretation (secondary necessity), whether or not secondary interpretation can be handled (secondary charge), and a notification destination are stored for each radiogram interpreter. The secondary necessity column of the radiogram interpreter table 32 stores information indicating whether secondary interpretation is necessary when the corresponding radiogram interpreter performs primary interpretation. For example, young veterinarians with little experience fall under this category. In the example of FIG. 3 and FIG. 4, secondary interpretation is unnecessary when doctor A and doctor B perform primary interpretation, and secondary interpretation is necessary when doctor C and doctor D perform primary interpretation. It represents that. In the secondary charge column of the radiogram interpreter table 32, information indicating whether or not the corresponding radiogram interpreter can take charge of secondary radiogram interpretation is stored. Further, in the notification destination column of the radiogram interpreter table 32, an e-mail address is stored as an example of a contact address of the corresponding radiogram interpreter.

  FIG. 5 shows an example of the animal species estimation model 34. As shown in FIG. 5, the animal species estimation model 34 according to the present embodiment is a neural network including an input layer, a plurality of intermediate layers, and an output layer. A medical image is input to the input layer of the animal species estimation model 34. The output layer of the animal species estimation model 34 outputs animal species information including the animal species and breed corresponding to the input medical image. The animal species estimation model 34 is obtained in advance by learning a plurality of combinations of medical images taken in the past and animal species information corresponding to the medical images as teacher data. The animal species is information for classifying animals such as dogs or cats, poodles or chihuahuas in dogs, and is generally called a race or breed.

  FIG. 6 shows an example of the disease estimation model 36. As shown in FIG. 6, the disease estimation model 36 according to the present embodiment is a neural network including an input layer, a plurality of intermediate layers, and an output layer. In the input layer of the disease estimation model 36, a medical image, a test result obtained by testing a blood of an animal, and animal species information are input. The output layer of the disease estimation model 36 indicates a disease that is likely to be affected, such as a disease that has a probability that an animal corresponding to the input medical image, examination result, and animal species information is affected by a predetermined value (for example, 50%) or more. Output. The disease estimation model 36 includes a plurality of combinations of medical images, examination results, and animal species information captured in the past, and a plurality of combinations of diseases affected by animals corresponding to the medical images, examination results, and animal species information. Is obtained in advance by learning. Note that the output layer of the disease estimation model 36 may output one type of disease or a plurality of types of disease. Diseases that are easily affected by animal species are different, and it is said that there are 700 to 800 animal species, such as dog breeds, and it is difficult to diagnose rare dog breeds even if they are professional human resources. is assumed. For this reason, it is highly convenient for veterinarians to be able to present disease candidates.

  Next, a hardware configuration of the display control device 14 according to the present embodiment will be described with reference to FIG. As illustrated in FIG. 7, the display control device 14 includes a CPU 40, a memory 41 as a temporary storage area, and a nonvolatile storage unit 42. The display control device 14 includes a display unit 43 such as a liquid crystal display, an input unit 44 such as a keyboard and a mouse, and a network I / F 45 connected to the network N. The CPU 40, the memory 41, the storage unit 42, the display unit 43, the input unit 44, and the network I / F 45 are connected to the bus 46. An example of the display control device 14 is a personal computer.

  The storage unit 42 is realized by an HDD, an SSD, a flash memory, or the like. A display control program 48 is stored in the storage unit 42 as a storage medium. The CPU 40 reads out the display control program 48 from the storage unit 42, expands it in the memory 41, and executes the expanded display control program 48.

  Next, a functional configuration of the diagnosis support apparatus 12 according to the present embodiment will be described with reference to FIG. As illustrated in FIG. 8, the diagnosis support apparatus 12 includes an acquisition unit 50, a first estimation unit 52, a second estimation unit 54, an allocation unit 56, a derivation unit 58, and a transmission unit 60. When the CPU 20 executes the diagnosis support program 30, the CPU 20 functions as the acquisition unit 50, the first estimation unit 52, the second estimation unit 54, the allocation unit 56, the derivation unit 58, and the transmission unit 60.

  The acquisition unit 50 acquires, via the network I / F 25, a medical image obtained by photographing an animal to be interpreted, which is transmitted from the animal hospital together with the interpretation request. Furthermore, the acquisition unit 50 also transmits the test result, the animal identification information, and the imaging information obtained by examining the blood of the animal to be interpreted, transmitted together with the interpretation request from the animal hospital, via the network I / F 25. get. The acquisition unit 50 stores the acquired medical image, examination result, animal identification information, and imaging information in the storage unit 22.

  The first estimation unit 52 inputs the medical image acquired by the acquisition unit 50 to the animal species estimation model 34, acquires the animal species information output from the animal species estimation model 34, and thereby acquires the animal to be interpreted. Estimate race and breed.

  The second estimation unit 54 inputs the medical image and the examination result acquired by the acquisition unit 50 and the animal species information including the race and breed estimated by the first estimation unit 52 to the disease estimation model 36, and disease estimation The disease output from the model 36 is acquired. Thereby, the 2nd estimation part 54 estimates the disease which the animal made into an interpretation object tends to suffer from.

  The allocation unit 56 is acquired by the acquisition unit 50 according to the animal species information including the race and breed estimated by the first estimation unit 52, the disease estimated by the second estimation unit 54, and the imaging region. Assign an interpreter to a medical image. Specifically, the allocation unit 56 can interpret the race and breed estimated by the first estimation unit 52 with reference to the radiogram interpreter table 32, and is good at interpretation of the disease estimated by the second estimation unit 54. In addition, an interpreter who is good at interpretation of an imaging region is assigned to a medical image.

  The deriving unit 58 derives information that can determine the size of the animal to be interpreted using the information about the imaging device added as the attribute information of the medical image acquired by the acquiring unit 50. In the present embodiment, the derivation unit 58 has a horizontal length (for example, 430 mm for a 17-inch cassette) as an example of the size of the imaging surface (effective pixel area size) of the imaging device that has captured the medical image, As information that can determine the size of the animal to be interpreted using the number of pixels next to the image or the resolution of the imaging device (for example, a value represented by dpi (dots per inch)) The horizontal length of the medical image from which the actual size can be determined is derived. Then, the derivation unit 58 stores the information that can be used to determine the size of the derived animal as the interpretation target in the storage unit 22 in association with the medical image. Note that the deriving unit 58 may derive the body length of the animal using the medical image and information regarding the imaging device added as attribute information of the medical image.

  The transmission unit 60 refers to the radiogram interpreter table 32 and sends an e-mail to the e-mail address of the radiographer's notification destination allocated by the allocation unit 56, thereby notifying the radiographer that the medical image has been allocated. To do. This e-mail includes, for example, identification information for specifying a medical image to be interpreted.

  Next, a functional configuration of the display control device 14 according to the present embodiment will be described with reference to FIG. As illustrated in FIG. 9, the display control device 14 includes an acquisition unit 70 and a display control unit 72. The CPU 40 functions as the acquisition unit 70 and the display control unit 72 by executing the display control program 48.

  The acquisition unit 70 acquires from the diagnosis support apparatus 12 information that can determine the medical image to be interpreted and the size of the animal to be interpreted. The display control unit 72 uses the information that can determine the size of the medical image and the animal acquired by the acquisition unit 70 to control the display unit 43 to display information that enables the visual recognition of the size of the medical image and the animal. Do.

  Next, with reference to FIG.10 and FIG.11, the effect | action of the diagnosis assistance system 10 which concerns on this embodiment is demonstrated. When the CPU 20 executes the diagnosis support program 30, the assignment process shown in FIG. 10 is executed. The assignment process shown in FIG. 10 is executed, for example, when the diagnosis support apparatus 12 receives a medical image interpretation request transmitted from an animal hospital. When the CPU 40 executes the display control program 48, the display process shown in FIG. 11 is executed. The display process shown in FIG. 11 is executed, for example, when an interpreter inputs a medical image display instruction via the input unit 44. In the present embodiment, this display instruction includes identification information for specifying a medical image to be interpreted.

  In step S10 of FIG. 10, the acquisition unit 50 acquires, via the network I / F 25, a medical image obtained by photographing an animal to be interpreted, which is transmitted together with the interpretation request from the animal hospital. Furthermore, the acquisition unit 50 also transmits the test result, the animal identification information, and the imaging information obtained by examining the blood of the animal to be interpreted, transmitted together with the interpretation request from the animal hospital, via the network I / F 25. get. The acquisition unit 50 stores the acquired medical image, examination result, animal identification information, and imaging information in the storage unit 22.

  In step S12, as described above, the derivation unit 58 can determine the size of the animal to be interpreted using the information regarding the imaging device added as the attribute information of the medical image acquired by the process of step S10. Information is derived. Then, the deriving unit 58 stores the information that can be used to determine the size of the derived animal as the interpretation target in the storage unit 22 in association with the medical image stored in the storage unit 22 by the process of step S10.

  In step S14, the first estimation unit 52 inputs the medical image acquired by the processing in step S10 to the animal species estimation model 34, and acquires the animal species information output from the animal species estimation model 34, thereby interpreting the image. Estimate the race and breed of the target animal.

  In step S16, the second estimation unit 54 inputs the medical image and the examination result acquired by the process of step S10 and the animal species information including the race and breed estimated by the process of step S14 to the disease estimation model 36. The disease output from the disease estimation model 36 is acquired. Thereby, the 2nd estimation part 54 estimates the disease which the animal made into an interpretation object tends to suffer from.

In step S18, the assigning unit 56 can interpret the race and breed estimated by the process of step S14 with reference to the interpreter table 32, and is good at interpretation of the disease estimated by the process of step S16. Interpreters who are good at interpreting parts are acquired as candidates for primary interpreters. In step S20, the assigning unit 56 assigns the radiogram interpreter having the lowest work-in-progress rate among candidates acquired by the process in step S18 as the primary radiogram interpreter of the medical image acquired by the process in step S10. This work-in-progress rate is calculated by the following equation (1), for example.
In-process ratio = Number of unread interpretations already assigned as interpreters ÷ Number of interpretations per day (1)

  In step S22, the transmission unit 60 refers to the radiogram interpreter table 32, and the medical image is allocated by transmitting an e-mail to the e-mail address to which the radiogram interpreter is notified in the process of step S20. Notify the reader.

  In step S24, the allocating unit 56 refers to the radiogram interpreter table 32 and determines whether or not the radiogram interpreter allocated by the process in step S20 is a radiogram interpreter that needs secondary radiogram interpretation. If this determination is affirmative, the process proceeds to step S26. If the determination is negative, the allocation process ends. In step S26, the assigning unit 56 can interpret the race and breed estimated by the process of step S14 with reference to the radiographer table 32, and is good at the interpretation of the disease estimated by the process of step S16. Interpreters who are good at reading and can take charge of secondary interpretation are obtained as candidates for secondary interpretation.

  In step S28, the assigning unit 56 selects the radiogram interpreter with the lowest in-process ratio among the candidates acquired by the process of step S26 according to the above equation (1) as the secondary of the medical image acquired by the process of step S10. Assign as an interpreter. In step S30, the transmission unit 60 refers to the radiogram interpreter table 32, and the medical image is allocated by transmitting an e-mail to the e-mail address to which the radiogram interpreter is notified by the process in step S28. Notify the reader. When the process of step S30 ends, the allocation process ends. The radiogram interpreter who has received the e-mail transmitted from the diagnosis support apparatus 12 operates his / her own display control apparatus 14 and inputs a display instruction for a medical image via the input unit 44.

  In step S40 of FIG. 11, the acquisition unit 70 acquires a medical image specified by the identification information input by the interpreter and information that can determine the size of the animal to be interpreted. In step S42, the display control unit 72 uses the information that can determine the size of the medical image and the animal acquired by the processing in step S42 to display information that enables the visual recognition of the size of the medical image and the animal. Control to display on the screen. When the process of step S42 ends, the display control process ends.

  By the process in step S42, as shown in FIG. 12 as an example, in addition to the medical image, the horizontal length of the medical image in which the actual size of the animal can be determined is displayed. For example, in the case of a dog, even if the same toy poodle is used, the size varies considerably depending on whether it is a tea cup size or a normal size. Thus, the accuracy of diagnosis can be increased by displaying the information that can visually recognize the size of the animal together with the medical image. Usually, when interpreting images, an image is often displayed in a full screen. This is to ensure ease of interpretation. If the target is a human, this was not a problem. However, in the case of an animal, the size of the original animal cannot be known at the moment when the image is displayed on the full screen. For example, when measuring the size of a tumor, it is obvious that a strange value has come out due to an operational error, or whether it is a plausible value depending on the size of the animal's body, etc. Animal size information may be useful.

  As described above, according to the present embodiment, a medical image obtained by photographing an animal to be interpreted is acquired, and the medical image is obtained according to the animal species information including the species and breed of the animal to be interpreted. An image reader is assigned to the image. Therefore, it is possible to assign an appropriate radiographer to a medical image obtained by photographing an animal.

  In addition, although the said embodiment demonstrated the case where the race and kind of an animal were estimated using a medical image, it is not limited to this. For example, the species and breed of an animal may be estimated using an optical image obtained by photographing an animal using a photographing apparatus that optically photographs a subject such as a digital camera. In this case, the form which inputs an optical image to the input layer of the animal species estimation model 34 is illustrated. Moreover, it is good also as a form which estimates the race and breed of an animal using both a medical image and an optical image. In this case, the form which inputs both a medical image and an optical image to the input layer of the animal species estimation model 34 is illustrated. The medical image is an image by radiation or ultrasound, and includes everything other than an optical image.

  Moreover, in the said embodiment, it is good also as a form which re-learns the disease estimation model 36 by feeding back to the disease estimation model 36 the result of the diagnosis performed by the image interpreter interpreting a medical image.

  In addition, various processors other than the CPU may execute various processes executed by the CPU executing software (programs) in the above embodiment. As a processor in this case, in order to execute specific processing such as PLD (Programmable Logic Device) and ASIC (Application Specific Integrated Circuit) whose circuit configuration can be changed after manufacturing FPGA (Field-Programmable Gate Array) or the like. Examples include a dedicated electric circuit that is a processor having a circuit configuration designed exclusively. Further, the above-described various processes may be executed by one of these various processors, or a combination of two or more processors of the same type or different types (for example, a combination of a plurality of FPGAs and CPUs and FPGAs). Etc.). More specifically, the hardware structure of these various processors is an electric circuit in which circuit elements such as semiconductor elements are combined.

  Moreover, although the said embodiment demonstrated the aspect by which the diagnostic assistance program 30 was beforehand memorize | stored (installed) in the memory | storage part 22, it is not limited to this. The diagnosis support program 30 is provided in a form recorded on a recording medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), and a USB (Universal Serial Bus) memory. Also good. The diagnosis support program 30 may be downloaded from an external device via a network.

  In the above embodiment, the display control program 48 is stored in the storage unit 42 in advance. However, the present invention is not limited to this. The diagnosis support program 30 may be provided in a form recorded on a recording medium such as a CD-ROM, a DVD-ROM, and a USB memory. The display control program 48 may be downloaded from an external device via a network.

DESCRIPTION OF SYMBOLS 10 Diagnosis support system 12 Diagnosis support apparatus 14 Display control apparatus 20, 40 CPU
21, 41 Memory 22, 42 Storage unit 23, 43 Display unit 24, 44 Input unit 25, 45 Network I / F
26, 46 Bus 30 Diagnosis support program 32 Interpreter table 34 Animal species estimation model 36 Disease estimation model 48 Display control program 50, 70 Acquisition unit 52 First estimation unit 54 Second estimation unit 56 Allocation unit 58 Derivation unit 60 Transmission unit 72 Display control unit N network

Claims (11)

An acquisition unit for acquiring a medical image obtained by photographing an animal to be interpreted;
An assigning unit that assigns an interpreter to the medical image according to animal species information including at least one of the race and breed of the animal to be interpreted;
Diagnosis support device comprising The estimation unit for estimating at least one of the race and the breed using at least one of the medical image and an optical image obtained by optically photographing the animal to be interpreted. Diagnosis support device. The diagnosis support apparatus according to claim 1, wherein the acquisition unit further acquires a test result of the specimen of the animal to be interpreted. The diagnosis support apparatus according to claim 3, wherein the specimen is at least one of blood, urine, saliva, and corneal cells. The diagnosis according to claim 3 or 4, further comprising: a second estimation unit that estimates a disease in which the animal to be interpreted is likely to be affected using the animal species information, the medical image, and the examination result. Support device. The diagnosis support apparatus according to claim 5, wherein the assigning unit assigns an interpreter to the medical image according to the disease estimated by the second estimating unit in addition to the animal species information. A first acquisition unit that acquires a medical image obtained by photographing an animal to be interpreted, and interpretation of the medical image according to animal species information including at least one of the species and breed of the animal to be interpreted An allocating unit for allocating a person, a second acquiring unit for acquiring information capable of determining the size of the medical image and the animal to be interpreted from the diagnostic supporting device, and the second A display control unit that performs control to display on the display unit the information that can visually recognize the size of the medical image and the animal, using information that can determine the size of the medical image and the animal acquired by the acquisition unit; A diagnostic support system including a display control device comprising: The diagnosis support apparatus derives information for determining the size of the animal using the size and resolution of the imaging surface of the imaging apparatus used for imaging the medical image and the number of pixels of the medical image. The diagnosis support system according to claim 7, further comprising a unit. An acquisition unit for acquiring a medical image obtained by photographing an animal to be interpreted, and information capable of determining the size of the animal to be interpreted;
A display control unit that performs control to display the medical image and information capable of visually recognizing the size of the animal on the display unit, using the medical image acquired by the acquisition unit and information that can determine the size of the animal; ,
A display control device. Obtain a medical image obtained by photographing an animal to be interpreted,
A diagnostic support method in which a computer executes a process of assigning an interpreter to the medical image according to animal species information including at least one of a race and a breed of an animal to be interpreted. Obtain a medical image obtained by photographing an animal to be interpreted,
A diagnostic support program for causing a computer to execute a process of assigning an interpreter to the medical image according to animal species information including at least one of a race and a breed of an animal to be interpreted.