Information processing device, information processing method, and program

Abstract

To accurately specify a correspondence relationship between a tissue slice drawn in a tissue image and a clipping position on a specimen image.SOLUTION: An information processing apparatus includes a clipping size specifying unit, a tissue image acquisition unit, a tissue region size specifying unit, and an association unit. The clipping size specifying unit acquires a size of a clipping section set on a pathological specimen in clipping a tissue slice from the pathological specimen. The tissue image acquisition unit acquires a tissue image obtained by imaging the tissue slice. The tissue region size specifying unit specifies a size of the tissue slice drawn in the tissue image. The association unit associates the clipping section with a tissue region where the tissue slice is drawn in the tissue image, based on the size of the clipping section and the size of the tissue slice.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The embodiments disclosed in the present specification and drawings relate to an information processing device, an information processing method, and a program. [Background technology]

[0002] Conventionally, in the field of pathology, etc., specimen images, which are images of the entire tissue specimen, and tissue images, which are images of tissue slices cut out from the specimen at a higher magnification than the specimen image, have been used by doctors and others for pathological tissue diagnosis, etc.

[0003] In such pathological tissue diagnosis, a technique is known in which a tissue slice depicted in a tissue image is displayed in association with a cutout position on a specimen image. For example, Patent Document 1 and Non-Patent Document 1 disclose a technique for associating multiple regions depicted in an image.

[0004] However, it is sometimes difficult to correctly associate the tissue slice depicted in the tissue image with the cut-out position on the specimen image. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2020-135617 [Non-patent literature]

[0006] [Non-Patent Document 1] Toru Tamaki, "Research on methods for extracting object and human regions from images," Doctoral dissertation, Department of Information Engineering, Graduate School of Engineering, Nagoya University, FY2000 Summary of the Invention [Problem to be solved by the invention]

[0007] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to identify with high accuracy the correspondence between a tissue slice depicted in a tissue image and an extraction position on a specimen image. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0008] The information processing apparatus according to the embodiment has a crop size acquisition a tissue image acquisition unit, and a tissue section The apparatus includes a size determination unit and a correspondence unit. acquisition The tissue image acquisition unit acquires the size of the cutout area set on the pathological specimen when cutting out a tissue slice from the pathological specimen. The tissue image acquisition unit acquires a tissue image of the tissue slice. section The size specification section is a tissue image Organizational Areas The associating unit associates the excision region with a tissue region in which the tissue slice is depicted on the tissue image, based on the size of the excision region and the size of the tissue slice. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of the overall configuration of an information processing system according to the first embodiment. [Figure 2] FIG. 2 is a diagram illustrating a flow up to capturing a tissue image according to the first embodiment. [Figure 3] FIG. 3 is a diagram showing an example of measuring the length of an excised portion according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing an example of measuring the length of a tissue region according to the first embodiment. [Figure 5] FIG. 5 is a diagram showing an example of measuring the thickness of a tissue region according to the first embodiment. [Figure 6]FIG. 6 is a diagram showing an example of association between cut-out parts and tissue regions according to the first embodiment. [Figure 7] FIG. 7 is a diagram showing another example of association between cut-out parts and tissue regions according to the first embodiment. [Figure 8] FIG. 8 is a diagram showing an example of association between a plurality of cut-out parts and a plurality of tissue regions according to the first embodiment. [Figure 9] FIG. 9 is a flowchart showing an example of the flow of the association process according to the first embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of the overall configuration of an information processing system according to the second embodiment. [Figure 11] FIG. 11 is a diagram showing an example of determining whether or not to divide a plurality of tissue slices corresponding to a plurality of tissue regions according to the second embodiment. [Figure 12] FIG. 12 is a diagram showing another example of determining whether or not to divide a plurality of tissue slices corresponding to a plurality of tissue regions according to the second embodiment. [Figure 13] FIG. 13 is a diagram showing an example of tissue images of a divided tissue slice and an undivided tissue slice according to the second embodiment. [Figure 14] FIG. 14 is a flowchart showing an example of the flow of the association process according to the second embodiment. [Figure 15] FIG. 15 is a diagram showing an example of a combination of divided tissue sections according to the first modification of the second embodiment. [Figure 16] FIG. 16 is a diagram showing an example of a combination of divided tissue sections according to the second modification of the second embodiment. [Figure 17] FIG. 17 is a diagram showing an example of association between cut-out parts and tissue regions according to the third embodiment. [Figure 18] FIG. 18 is a diagram showing an example of determining whether or not to divide a tissue region according to the second modification of the third embodiment. [Figure 19] FIG. 19 is a diagram showing an example of association between cut-out parts and tissue regions according to the fourth embodiment. [Figure 20] FIG. 20 is a diagram showing an example of association between cut-out parts and tissue regions according to the first modification of the fourth embodiment. [Figure 21] FIG. 21 is a diagram illustrating an example of cutout order information according to the first modification of the fourth embodiment. [Figure 22] FIG. 22 is a diagram showing another example of the cutout order information according to the first modification of the fourth embodiment. [Figure 23] FIG. 23 is a diagram showing an example of an arrangement rule for tissue slices according to the third modification of the fourth embodiment. [Figure 24] FIG. 24 is a diagram showing another example of the arrangement rule of the tissue slice according to the third modification of the fourth embodiment. [Figure 25] FIG. 25 is a diagram showing yet another example of the arrangement rule for tissue slices according to the third modification of the fourth embodiment. [Figure 26] FIG. 26 is a diagram illustrating an example of the overall configuration of an information processing system according to the fifth embodiment. [Figure 27] FIG. 27 is a diagram showing an example of a correspondence relationship between a first position on a tissue image and a second position on a sample image according to the fifth embodiment. [Figure 28] FIG. 28 is a diagram showing an example of a position of interest on a sample image and a corresponding position on a tissue image according to the fifth embodiment. [Figure 29] FIG. 29 is a diagram showing an example of a position of interest on a tissue image and a corresponding position on a specimen image according to the fifth embodiment. [Figure 30] FIG. 30 is a diagram showing an example of a first region on a tissue image according to the fifth embodiment. [Figure 31] FIG. 31 is a diagram showing an example of a second region on a sample image according to the fifth embodiment. [Figure 32] FIG. 32 is a diagram showing an example of display of first information representing a first region and second information representing a second region according to the fifth embodiment. [Figure 33] FIG. 33 is a diagram showing another example of display of the first information representing the first region and the second information representing the second region according to the fifth embodiment. [Figure 34] FIG. 34 is a flowchart showing an example of the flow of the association process according to the fifth embodiment. [Figure 35] FIG. 35 is a diagram showing an example of a connected enlarged image according to the sixth embodiment. [Figure 36] FIG. 36 is a diagram showing an example of a connective tissue image according to the seventh embodiment. [Figure 37] FIG. 37 is a diagram showing an example of correction of the position of interest on a tissue image according to the modifications of the fifth to seventh embodiments. [Figure 38] FIG. 38 is a diagram showing an example of correction of a position of interest on a sample image according to the modifications of the fifth to seventh embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of an information processing device, an information processing method, and a program will be described in detail with reference to the drawings.

[0011] (First embodiment) 1 is a diagram showing an example of the overall configuration of an information processing system S according to the first embodiment. As shown in FIG. 1, the information processing system S includes an information processing device 100, a specimen image storage device 201, a tissue image storage device 202, a first image capturing device 401, and a second image capturing device 402.

[0012] The information processing device 100, the specimen image storage device 201, the tissue image storage device 202, the first photographing device 401, and the second photographing device 402 are communicatively connected to the specimen image storage device 201 and the tissue image storage device 202 via a network 300 such as an in-hospital LAN (Local Area Network).

[0013] The information processing system S may further include a specimen management system, a hospital information system (HIS), a laboratory information system (LIS), a radiology information system (RIS), etc. Alternatively, the information processing system S may be part of a hospital information system. The information processing system S may further include a terminal device such as a personal computer (PC) or a tablet terminal.

[0014] The information processing system S is installed, for example, in a medical institution such as a hospital, a research institute such as a university, an examination center, etc. Furthermore, some or all of the devices constituting the information processing system S may be installed in a cloud environment.

[0015] The first imaging device 401 captures an image of a tissue slice, which is a specimen. In this embodiment, an image of the entire tissue slice, which is a pathological specimen (hereinafter simply referred to as a specimen), is referred to as a specimen image. The first imaging device 401 is, for example, a digital camera, but is not limited to this. For example, the first imaging device 401 may be an analog camera, a video camera, or a spectroscopic camera. The first imaging device 401 may also be an OCT (Optical Coherence Tomography) device, a MicroCT (Computed Tomography) device, a MicroMRI (Magnetic Resonance Imaging) device, an X-ray CT device, an MRI (Magnetic Resonance Imaging) device, or the like, which are capable of capturing three-dimensional tomographic images of the specimen. The first imaging device 401 may also be a three-dimensional scanner or the like that acquires a surface point cloud of the specimen. The specimen image may be processed, for example, by staining, to make abnormal areas more visible. The specimen image is also referred to as a macro image.

[0016] In this embodiment, the specimen is a partial tissue collected from a patient's body, an animal, etc. For example, the specimen is a tissue fragment such as the mucosa and submucosa of the digestive tract excised by endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD), but is not limited thereto and may also be a tissue fragment excised by laparotomy or the like.

[0017] The second imaging device 402 captures an image of at least one slice cut from a tissue slice, which is a specimen, at a magnification higher than that of a specimen image. In this embodiment, an image of at least one slice cut from a tissue slice, which is a specimen, at a magnification higher than that of a specimen image is referred to as a tissue image. The second imaging device 402 is, for example, a WSS (Whole Slide Scanner) or a digital microscope. A WSS is a device that captures a WSI (Whole Slide Imaging) image, which is a highly accurate digital image of the entire or part of a slice placed on a glass slide, but is not limited to this. The tissue image is also referred to as a micro-image.

[0018] The first image capturing device 401 and the second image capturing device 402 do not necessarily have to be included in the information processing system S.

[0019] The sample image storage device 201 is a device that stores sample images captured by the first image capturing device 401. Note that the sample image storage device 201 may store sample images captured by a device other than the first image capturing device 401.

[0020] The tissue image storage device 202 is a device that stores tissue images captured by the second imaging device 402. Note that the tissue image storage device 202 may store specimen images captured by a device other than the second imaging device 402.

[0021] The sample image storage device 201 and the tissue image storage device 202 are, for example, a server device or a PC. The sample image storage device 201 and the tissue image storage device 202 may be collectively referred to as an image storage device. Although the sample image storage device 201 and the tissue image storage device 202 are shown as separate devices in FIG. 1, the sample image storage device 201 and the tissue image storage device 202 may be configured as an integrated device. The sample image storage device 201, the tissue image storage device 202, and the information processing device 100 may be configured as an integrated device.

[0022] FIG. 2 is a diagram illustrating the flow up to capturing a tissue image according to the first embodiment. For example, a specimen 5 collected from a patient P by a diagnostician is transferred to a pathologist or a laboratory technician for pathological diagnosis. At this time, a pathology number is assigned for each request (order) for pathological diagnosis. A different specimen number is assigned for each specimen to be subjected to pathological diagnosis. Note that when there are multiple specimens to be diagnosed in one request for pathological diagnosis, multiple specimen numbers are associated with one pathology number. Hereinafter, in this embodiment, a pathologist or laboratory technician will be referred to as a pathologist or the like.

[0023] The processing performed by the information processing device 100 in this embodiment does not necessarily have to be for the purpose of pathological diagnosis. For example, the processing may be for the purpose of research by a research institute or for the purpose of creating a report at an examination center that performs pathological examinations on behalf of a medical institution.

[0024] A sample image ID is assigned as identification information for a sample image 51 obtained by photographing the sample 5 with a digital camera or the like. The sample image ID may be registered as additional information for the sample image 51. Information related to the sample image 51, such as the pathology number of the sample 5 that is the subject of the photograph of the sample image 51, the sample number of the sample 5, the order number of the pathological diagnosis related to the sample 5, the patient ID of the patient P from whom the sample 5 was obtained, and the photographing date and time of the sample image 51, may also be registered as additional information for the sample image 51. The sample image ID and other information related to the sample image 51 may be displayed as text information on the sample image 51.

[0025] A pathologist or the like cuts out tissue slices 60a to 60e from specimen 5, and after performing processing such as staining, for example, slices the cross sections of tissue slices 60a to 60e thinly and places them on glass slides 7. Hereinafter, when there is no need to distinguish between the individual tissue slices 60a to 60e, they will simply be referred to as tissue slices 60.

[0026] In this embodiment, the group of sections placed on the slide glass 7 is referred to as a tissue specimen 6. The tissue specimen 6 includes at least one tissue section 60.

[0027] In addition, in Figure 2, each tissue slice 60 is placed directly on the glass slide 7, but if the tissue slice 60 is long or depending on the shape of the cutting position, one tissue slice 60 may be divided into multiple pieces and placed on the glass slide 7.

[0028] In FIG. 2, as an example, the tissue slices 60a to 60e are photographed with their cross sections facing the imaging device, but the orientation of the tissue slices is not limited to this. For example, the tissue slice 60 may be photographed in the same orientation as the specimen 5 when the specimen image 51 is photographed. In addition, in FIG. 2, the tissue slice 60 is placed on the glass slide 7 so that the horizontal direction of the tissue image 61 coincides with the longitudinal direction of the tissue region 62, but the orientation is not limited to this. For example, the tissue slice 60 may be placed on the glass slide 7 so that the vertical direction of the tissue image 61 coincides with the longitudinal direction of the tissue region 62. Alternatively, the tissue slice 60 may be placed at an angle on the glass slide 7. The arrangement of the tissue slice 60 is assumed to be determined, for example, by the slice arrangement rules of each medical institution.

[0029] An image such as a WSI image captured of a tissue specimen 6 placed on a glass slide 7 is a tissue image 61. The tissue image 61 depicts the tissue specimen 6 including tissue slices 60a to 60e. Note that, although all of the tissue slices 60 cut from one specimen 5 are arranged on one glass slide 7 in FIG. 2, the tissue slices 60 cut from one specimen 5 may be arranged on multiple glass slides 7. In this case, one specimen image 51 corresponds to multiple tissue images 61.

[0030] A tissue image ID is assigned as identification information for the tissue image 61. The tissue image ID may be registered as additional information for the tissue image 61. Information related to the tissue image 61, such as the pathology number of the specimen 5 from which the section that is the subject of the tissue image 61 was obtained, the specimen number of the specimen 5, the order number for the pathological diagnosis related to the specimen 5, the patient ID of the patient P from whom the specimen 5 was obtained, and the date and time the tissue image 61 was captured, may be registered as additional information for the tissue image 61. The tissue image ID and other information related to the tissue image 61 may be rendered as text information on the tissue image 61. The additional information for the tissue image 61 may also include identification information for the facility, such as a medical institution, that captured the tissue image 61. The identification information for the facility, such as a medical institution, that captured the tissue image 61 may be obtained, for example, from a clinical testing system or a specimen management system.

[0031] The tissue image 61 includes a background region 70 depicting the glass slide 7 and a plurality of tissue regions 62a-62e depicting the tissue specimen 6. Hereinafter, when there is no need to distinguish between the individual tissue regions 62a-62e, they will simply be referred to as tissue regions 62. The tissue regions 62 are also referred to as section regions.

[0032] The information processing device 100 of this embodiment associates the extraction position of each tissue slice 60 in the tissue image 61 with the tissue region 62 in which each tissue slice 60 is depicted in the tissue image 61.

[0033] Returning to FIG. 1, the information processing device 100 is, for example, a server device or a PC, and includes a NW interface 110, a storage circuit 120, an input interface 130, a display 140, and a processing circuit 150.

[0034] The NW interface 110 is connected to the processing circuit 150 and controls the transmission and communication of various data between the information processing device 100 and the first image capturing device 401, the second image capturing device 402, the specimen image storage device 201, and the tissue image storage device 202. The NW interface 110 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like.

[0035] The storage circuitry 120 stores in advance various types of information to be used by the processing circuitry 150. The storage circuitry 120 also stores various programs.

[0036] The input interface 130 may be realized by a trackball, switch buttons, a mouse, a keyboard, a touchpad that performs input operations by touching the operation surface, a touchscreen that integrates a display screen and a touchpad, a non-contact input circuit using an optical sensor, a voice input circuit, etc. The input interface 130 is connected to the processing circuit 150 and converts input operations received from an operator into electrical signals and outputs them to the processing circuit 150. Note that in this specification, the input interface is not limited to those that have physical operation components such as a mouse and a keyboard. For example, an electrical signal processing circuit that receives electrical signals corresponding to input operations from an external input device provided separately from the information processing device 100 and outputs these electrical signals to the processing circuit 150 is also included as an example of the input interface 130.

[0037] The display 140 is a liquid crystal display, an organic electro-luminescence (OEL) display, or the like. The input interface 130 and the display 140 may be integrated. For example, the input interface 130 and the display 140 may be realized by a touch panel. The display 140 is an example of a display unit.

[0038] The processing circuitry 150 is a processor that reads out programs from the storage circuitry 120 and executes them to realize functions corresponding to each program. The processing circuitry 150 of this embodiment includes a specimen image acquisition function 151, a tissue image acquisition function 152, a cutout size specification function 153, a tissue region size specification function 154, a matching function 155, a display control function 156, and a reception function 157. The specimen image acquisition function 151 is an example of a specimen image acquisition unit. The tissue image acquisition function 152 and the cutout size specification function 153 are examples of a tissue image acquisition unit. The tissue region size specification function 154 is an example of a tissue region size specification unit. The matching function 155 is an example of a matching unit. The display control function 156 is an example of a display control unit. The reception function 157 is an example of a reception unit.

[0039] Here, for example, each processing function of the processing circuitry 150, namely, the specimen image acquisition function 151, the tissue image acquisition function 152, the cutout size identification function 153, the tissue region size identification function 154, the association function 155, the display control function 156, and the reception function 157, is stored in the storage circuitry 120 in the form of a computer-executable program. The processing circuitry 150 is a processor. For example, the processing circuitry 150 realizes the function corresponding to each program by reading and executing the program from the storage circuitry 120. In other words, the processing circuitry 150 in a state in which each program has been read has each function shown in the processing circuitry 150 of FIG. 1. 1 has been described as realizing the processing functions performed by specimen image acquisition function 151, tissue image acquisition function 152, cutout size specification function 153, tissue region size specification function 154, association function 155, display control function 156, and reception function 157 in a single processor, but it is also possible to combine multiple independent processors to configure processing circuit 150, and have each processor execute a program to realize the function. Also, while it is described in FIG. 1 as a single memory circuit 120 storing programs corresponding to each processing function, it is also possible to configure multiple memory circuits to be distributed and have processing circuit 150 read out corresponding programs from individual memory circuits.

[0040] In the above description, an example has been described in which a "processor" reads and executes a program corresponding to each function from a storage circuit. However, the present embodiment is not limited to this. The term "processor" refers to a circuit such as a central processing unit (CPU), a graphics processing unit (GPU), an application-specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)). If the processor is a CPU, for example, the processor realizes a function by reading and executing a program stored in a storage circuit. On the other hand, if the processor is an ASIC, instead of storing a program in the storage circuit 120, the function is directly incorporated as a logic circuit within the processor circuit. Note that each processor in the present embodiment is not limited to being configured as a single circuit per processor, and may be configured as a single processor by combining multiple independent circuits to realize its function. Furthermore, the functions of the multiple components in FIG. 1 may be realized by integrating them into a single processor.

[0041] The sample image acquisition function 151 acquires a sample image 51 from the first image capturing device 401 or the sample image storage device 201 .

[0042] The specimen image 51 to be acquired is designated by, for example, a user operation received by a later-described reception function 157. The user of the information processing device 100 is a pathologist or the like.

[0043] The user specifies the specimen image 51 to be acquired by inputting, for example, a pathology number, a patient ID, a specimen number, an order number, or an imaging date, or a combination of these.

[0044] The user may also select the sample image to be acquired from a list of sample images 51 stored in the sample image storage device 201. The sample image 51 may be stored in advance in the memory circuitry 120 and read out by a user operation.

[0045] The tissue image acquisition function 152 acquires the tissue image 61 from the second image capture device 402 or the tissue image archive device 202 .

[0046] The cut-out size specification function 153 specifies the size of the cut-out portion to be set on the specimen 5 when cutting out a tissue slice 60 from the specimen 5. The size of the cut-out portion is, for example, the length of the cut-out portion on the specimen 5. The size of the cut-out portion may also be the thickness of the cut-out portion on the specimen 5. The size of the cut-out portion may also be, for example, both the length and the thickness of the cut-out portion on the specimen 5. In this embodiment, the size of the cut-out portion includes at least either the length or the thickness of the cut-out portion on the specimen 5.

[0047] 3 is a diagram showing an example of measuring the length of an excision region according to the first embodiment. The portion of an excision line 53 indicating the excision position in a sample image 51 that is included in a sample region 510 corresponds to the excision region of the sample 5.

[0048] As shown in FIG. 3, the cutout size specifying function 153 measures the length of the portion of cutout lines 53a to 53e that indicate the cutout position on the sample image 51, which is included in the sample region 510 in which the sample 5 is depicted. The cutout size specifying function 153 converts the length measured on the sample image 51 into an actual length based on the scale of the sample image 51, thereby measuring the length of the cutout portion from which the tissue slice on the sample 5 has been cut out. In the example shown in FIG. 3, when the length of the cutout line 53a within the sample region 510 is converted into an actual length, it becomes 10 mm. Hereinafter, when the individual cutout lines 53a to 53e are not particularly distinguished from one another, they will simply be referred to as cutout lines 53.

[0049] The cutout size specifying function 153 may also acquire the depth of the cutout portion and the depth of the background portion measured by a depth camera or the like, and measure the difference between the depth of the cutout portion and the depth of the background portion as the thickness of the cutout portion. The positions at which the cutout size specifying function 153 measures the thickness may be at equal intervals, or may only be at locations where the thickness varies greatly. The cutout size specifying function 153 may also acquire the thickness at locations where the thickness varies greatly in addition to the thickness acquired at equal intervals.

[0050] The cutout size specifying function 153 may employ a method other than measuring the size of the cutout portion from the specimen image 51. For example, the cutout size specifying function 153 may acquire the size of the cutout portion input by the user, or may read the size of the cutout portion as data from a file or the like in which the size of the cutout portion is recorded. If the cutout size specifying function 153 measures the size of the cutout portion without using the specimen image 51, the processing circuit 150 of this embodiment may not be provided with the specimen image acquisition function 151.

[0051] Returning to FIG. 1 , the tissue region size identification function 154 identifies the size of the tissue slice 60 depicted in the tissue image 61. The size of the tissue slice 60 is, for example, the length of the tissue slice 60. The size of the tissue slice 60 may also be the thickness of the tissue region 62. In this embodiment, the size of the tissue slice 60 includes at least either the length or the thickness of the tissue slice 60.

[0052] Fig. 4 is a diagram showing an example of measuring the length of a tissue region according to the first embodiment. As shown in Fig. 4, tissue region size specifying function 154 measures the length along the cutout direction of each of multiple tissue regions 62a-62f depicted in tissue image 61. Tissue region size specifying function 154 converts the length measured on tissue image 61 into an actual length based on the scale of tissue image 61, thereby measuring the actual length of tissue slice 60 corresponding to multiple tissue regions 62a-62f. In the example shown in Fig. 4, the length within tissue slice 60 corresponding to tissue region 62a converted to the actual length is 7 mm, and the length within tissue slice 60 corresponding to tissue region 62b converted to the actual length is 3 mm.

[0053] FIG. 5 is a diagram showing an example of measuring the thickness of a tissue region 62 according to the first embodiment. In the example shown in FIG. 5, the cut surface faces forward relative to the imaging direction, and therefore the length of the tissue region 62a in a direction substantially perpendicular to the cutting direction is the thickness of the tissue region 62. As shown in FIG. 5, the tissue region size specifying function 154 converts the thickness of the tissue region 62a depicted in the tissue image 61 into an actual thickness based on the scale of the tissue image 61, thereby measuring the actual thickness of the tissue slice 60 corresponding to the tissue region 62a. The thickness measurement positions by the tissue region size specifying function 154 may be at equal intervals, or may be limited to areas with large thickness variations. Furthermore, the tissue region size specifying function 154 may obtain thicknesses at areas with large thickness variations in addition to the thicknesses obtained at equal intervals.

[0054] It should be noted that the tissue region size identification function 154 may employ a method other than measuring the size of the tissue slice 60 from the tissue region 62 depicted in the tissue image 61. For example, the tissue region size identification function 154 may acquire the size of the tissue slice 60 input by the user, or may read the size of the cut-out portion as data from a file or the like in which the size of the tissue slice 60 is recorded.

[0055] Returning to FIG. 1, the association function 155 associates the excision region with the tissue region 62 based on the size of the excision region and the size of the tissue slice 60 .

[0056] For example, when the difference between the length of the excision portion and the length of the tissue slice 60 along the excision direction is equal to or less than a threshold, the association function 155 associates the excision portion with the tissue region 62 corresponding to the tissue slice 60. The value of the threshold is not particularly limited. The threshold may be input by the user or registered in a setting file. The association function 155 may also calculate the threshold based on statistics of the size of the excision portion or the tissue region 62. The threshold may be a fixed value or may vary depending on the size of the excision portion or the tissue region 62.

[0057] 6 is a diagram showing an example of association between an excision portion and a tissue region 62 according to the first embodiment. In the example shown in FIG. 6, the actual length of the excision portion corresponding to the excision line 53a depicted in the specimen image 51 is 10.2 mm. Furthermore, the length along the excision direction of the tissue slice 60 corresponding to the tissue region 62g depicted in the tissue image 61 is 10.3 mm. In this case, the difference between the length of the excision portion and the length along the excision direction of the tissue slice 60 is 0.1 mm. When the threshold value is 0.1 mm or greater, the association function 155 associates the excision portion corresponding to the excision line 53a depicted in the specimen image 51 with the tissue region 62g depicted in the tissue image 61.

[0058] In addition, the matching function 155 may match the cut-out portion with the tissue region 62 corresponding to the tissue slice 60 without using a threshold value when the length of the cut-out portion matches the length along the cut-out direction of the tissue slice 60.

[0059] 7 is a diagram showing another example of association between an excision portion and a tissue region 62 according to the first embodiment. In the example shown in Fig. 7, the actual length of the excision portion corresponding to the excision line 53a depicted in the specimen image 51 matches the length along the excision direction of the tissue slice 60 corresponding to the tissue region 62g depicted in the tissue image 61. In this case, the association function 155 associates the excision portion corresponding to the excision line 53a depicted in the specimen image 51 with the tissue region 62g depicted in the tissue image 61.

[0060] Similarly, the association function 155 associates all tissue regions 62 depicted in the tissue image 61 with the cut-out lines 53 depicted in the specimen image 51. Fig. 8 is a diagram showing an example of association between a plurality of cut-out regions and a plurality of tissue regions 62 according to the first embodiment. In the example shown in Fig. 8, when the difference between the length of the cut-out region and the length of the tissue slice 60 along the cut-out direction is equal to or less than a threshold, the association function 155 associates the cut-out region with the tissue region 62 corresponding to the tissue slice 60.

[0061] 6 to 8 show an example of association based on the length of the excision site and the length of the tissue slice 60 along the excision direction, but the association function 155 may associate the excision site with the tissue region 62 based on the thickness of the excision site and the thickness of the tissue slice 60. For example, the association function 155 associates the excision site with the tissue region 62 corresponding to the tissue slice 60 based on the thicknesses of multiple locations in the excision site and the thicknesses of multiple locations in the tissue slice 60.

[0062] The association function 155 may also associate the excision site with the tissue region 62 based on both the length and thickness of the excision site and the length and thickness of the tissue slice 60 .

[0063] The correspondence function 155 stores the correspondence between the cut-out portion and the tissue region 62 in the memory circuitry 120.

[0064] 1, the display control function 156 correlates the cut-out portion correlated by the correlation function 155 with the tissue region 62 and displays them on the display 140. The timing of display is not particularly limited, and may be immediately after the correlation process, or when the user performs an inquiry operation for the cut-out portion corresponding to the tissue region 62 while the tissue image 61 is being displayed on the display 140.

[0065] The reception function 157 receives various operations from the user via the input interface 130 .

[0066] Next, the flow of the association process executed by the information processing device 100 of this embodiment configured as above will be described.

[0067] FIG. 9 is a flowchart showing an example of the flow of the association process according to the first embodiment.

[0068] First, the sample image acquisition function 151 acquires a sample image 51 from the first image capturing device 401 or the sample image storage device 201 (S11).

[0069] Then, the cut-out size specifying function 153 specifies the size of the cut-out portion from which the tissue slice 60 is cut out in the specimen 5 (S12). For example, the cut-out size specifying function 153 specifies the actual length of the cut-out portion based on the length of the cut-out portion depicted on the specimen image 51 and the scale of the specimen image 51.

[0070] Furthermore, the tissue image acquisition function 152 acquires the tissue image 61 from the second photographing device 402 or the tissue image storage device 202 (S13).

[0071] Then, the tissue region size identification function 154 identifies the size of the tissue slice 60 depicted in the tissue image 61 (S14). For example, the tissue region size identification function 154 converts the length of the tissue region 62 measured on the tissue image 61 into an actual length based on the scale of the tissue image 61, thereby identifying the actual length of the tissue slice 60 corresponding to the tissue region 62.

[0072] Then, the association function 155 associates the excision site with the tissue region 62 based on the size of the excision site and the size of the tissue slice 60 (S15). For example, when the difference between the length of the excision site and the length of the tissue slice 60 along the excision direction is equal to or less than a threshold, the association function 155 associates the excision site with the tissue region 62 corresponding to the tissue slice 60. The association function 155 stores the association between the excision site and the tissue region 62 in the memory circuitry 120. Here, the processing of this flowchart ends.

[0073] In this flowchart, the cutout size specifying function 153 specifies the length of the cutout portion from the sample image 51, but the length of the cutout portion may be specified without using the sample image 51. In this case, the process of S11 is unnecessary. In this case, in the process of S12, the cutout size specifying function 153 may obtain the size of the cutout portion input by the user, or may read the size of the cutout portion as data from a file or the like in which the size of the cutout portion is recorded.

[0074] In addition, in the processing of S15, the matching function 155 may match the cut-out portion with the tissue region 62 corresponding to the tissue slice 60 without using a threshold value when the length of the cut-out portion matches the length along the cut-out direction of the tissue slice 60.

[0075] In this way, the information processing device 100 of this embodiment associates the excision portion with the tissue region 62 corresponding to the tissue slice 60 based on the size of the excision portion and the size of the tissue slice 60. Therefore, the information processing device 100 of this embodiment can identify the correspondence between the tissue slice 60 depicted in the tissue image 61 and the excision position on the specimen image 51 with high accuracy.

[0076] For example, when a technician or the like arranges the tissue slices 60 on the glass slide 7, the arrangement order of the tissue slices 60 may be changed due to manual work. According to the information processing device 100 of this embodiment, even if the arrangement order of the tissue slices 60 is not a specified order, it is possible to identify the correspondence between the tissue slices 60 depicted in the tissue image 61 and the cut-out positions on the specimen image 51.

[0077] (Modification 1 of the first embodiment) In the first embodiment, the cutout size specifying function 153 and the tissue region size specifying function 154 specify the actual size of the cutout portion from which the tissue slice 60 in the specimen 5 is cut out and the actual size of the tissue slice 60, but the actual sizes do not have to be used. For example, the cutout size specifying function 153 and the tissue region size specifying function 154 may specify the relative sizes of the cutout portion and the tissue region 62 based on the ratio of the scales of the specimen image 51 and the tissue image 61. In this case, the association function 155 associates the cutout portion with the tissue region 62 based on the result of comparing the relative sizes of the cutout portion and the tissue region 62.

[0078] (Second embodiment) In the above-described first embodiment, the information processing device 100 has been described as having a function of determining an excision position for excising the tissue slice 60 from the specimen 5. In this fourth embodiment, the information processing device 100 further determines whether or not it is necessary to divide the tissue slice 60 excised from one excision position, and suggests an appropriate division position.

[0079] 10 is a diagram showing an example of the overall configuration of an information processing system S according to the second embodiment. Similar to the first embodiment, the information processing system S according to the present embodiment includes an information processing device 100, a specimen image storage device 201, a tissue image storage device 202, a first image capturing device 401, and a second image capturing device 402.

[0080] The processing circuitry 150 of the information processing device 100 of this embodiment includes a specimen image acquisition function 151, a tissue image acquisition function 152, a cutout size specification function 153, a tissue region size specification function 154, The system includes an association function 155a, a display control function 156, a reception function 157, and a division presence / absence determination function 158. The division presence / absence determination function 158 is an example of a division presence / absence determination unit.

[0081] The specimen image acquisition function 151, tissue image acquisition function 152, cutout size specification function 153, tissue region size specification function 154, display control function 156, and reception function 157 have the same functions as those in the first embodiment.

[0082] The division presence / absence determination function 158 determines the division state of the plurality of tissue slices 60 corresponding to the plurality of tissue regions 62 based on the size of the cut-out portion and the size of the plurality of tissue regions 62 included in the tissue image 61 .

[0083] For example, the division determination function 158 determines that the tissue slice cut from the cut-out portion has been divided into two or more tissue slices 60 if the difference between the length of the cut-out portion and the sum of the lengths of any two or more tissue slices 60 along the cut-out direction is less than a threshold value.

[0084] The threshold value in this embodiment may be the same as or different from the threshold value used for the association in the first embodiment. The value of the threshold value is not particularly limited. The threshold value may be input by the user or registered in a setting file. Furthermore, the division presence / absence determination function 158 may calculate the threshold value based on statistics of the size of the cut-out portion or the tissue region 62, etc. The threshold value may be a fixed value, or may vary depending on the size of the cut-out portion or the tissue region 62.

[0085] In this case, the association function 155a of this embodiment, which will be described later, associates the cut-out portion with two or more tissue regions 62 corresponding to the two or more tissue slices 60.

[0086] 11 is a diagram showing an example of determining whether or not to divide a plurality of tissue slices 60 corresponding to a plurality of tissue regions 62m, 62n according to the second embodiment. In the example shown in FIG. 11, the actual length of the cut-out portion corresponding to cut-out line 53a depicted in specimen image 51 is 10.2 mm. The length along the cut-out direction of tissue slice 60 corresponding to tissue region 62m depicted in tissue image 61 is 7.2 mm. The length along the cut-out direction of tissue slice 60 corresponding to tissue region 62n depicted in tissue image 61 is 3.1 mm. The sum of the length along the cut-out direction of tissue slice 60 corresponding to tissue region 62m and the length along the cut-out direction of tissue slice 60 corresponding to tissue region 62n is 10.3 mm.

[0087] In this case, the difference between the length of the cut-out portion and the total length of the two tissue slices 60 along the cut-out direction is 0.1 mm. If the threshold value is 0.1 mm or more, the division determination function 158 determines that the two tissue slices 60 corresponding to the tissue regions 62m and 62n are formed by dividing a single tissue slice 60. In this case, the association function 155a of the present embodiment, which will be described later, associates the cut-out portion corresponding to the cut-out line 53a depicted in the specimen image 51 with the tissue regions 62m and 62n.

[0088] Furthermore, the division determination function 158 determines that the tissue slice 60 has not been divided if there is no correspondence where the difference between the length of the cut-out portion and the sum of the lengths of any two or more tissue slices 60 along the cut-out direction is less than a threshold value.

[0089] In addition, the division determination function 158 may determine, without using a threshold value, that two or more tissue slices 60 are formed by dividing one tissue slice 60 when the length of the cut-out portion matches the sum of the lengths of the two or more tissue slices 60 along the cut-out direction.

[0090] FIG. 12 is a diagram showing another example of determining whether or not to divide the plurality of tissue slices 60 corresponding to the plurality of tissue regions 62m, 62n according to the second embodiment.

[0091] 12, the actual length of 10 mm of the cut-out portion corresponding to cut-out line 53a depicted in specimen image 51 matches the sum of the length of 7 mm along the cut-out direction of tissue slice 60 corresponding to tissue region 62m depicted in tissue image 61 and the length of 3 mm along the cut-out direction of tissue slice 60 corresponding to tissue region 62n. In this case, division determination function 158 determines that the two tissue slices 60 corresponding to tissue regions 62m and 62n are formed by dividing a single tissue slice 60.

[0092] The association function 155a of this embodiment has the same functions as those of the first embodiment, and associates the cut-out portion with the plurality of tissue regions based on the determination result of the division presence / absence determination function 158.

[0093] For example, among the multiple tissue regions 62 depicted in the tissue image 61, some may correspond to divided tissue slices 60, while others may correspond to undivided tissue slices 60.

[0094] Fig. 13 is a diagram showing an example of a tissue image 61 in which a divided tissue slice and an undivided tissue slice according to the second embodiment are photographed. In the example shown in Fig. 13, the division determination function 158 determines that the two or more tissue slices 60 have been divided when the difference between the length of the cut-out portion and the total length of the two or more tissue slices 60 along the cut-out direction is equal to or less than a threshold value of "0.3 mm."

[0095] In Figure 13, the matching function 155a matches the cut-out portion corresponding to the cut-out line 53a drawn in the specimen image 51 with the tissue regions 62m, 62n drawn in the tissue image 61 based on the judgment result of the division presence / absence judgment function 158.

[0096] 13, the actual length of the cut-out portion corresponding to cut-out line 53b rendered in specimen image 51 is 15.1 mm. The length along the cut-out direction of tissue slice 60 corresponding to tissue region 62o rendered in tissue image 61 is 14.8 mm. In this case, the difference between the actual length of the cut-out portion and the length along the cut-out direction of tissue slice 60 is equal to or less than the threshold, so association function 155a associates the cut-out portion corresponding to cut-out line 53b with tissue region 62o, as in the first embodiment.

[0097] 14 is a flowchart showing an example of the flow of the association process according to the second embodiment. The process from the acquisition of the specimen image 51 in S21 to the determination of the size of the tissue section 60 in S24 is the same as the process from S11 to S14 in the first embodiment described in FIG.

[0098] Then, the division determination function 158 determines the division state of the multiple tissue slices 60 corresponding to the multiple tissue regions 62 based on the size of the cut-out portion and the size of the multiple tissue regions 62 included in the tissue image 61 (S25).

[0099] Then, the association function 155a associates the cut-out portion with the plurality of tissue regions based on the determination result of the division presence / absence determination function 158 (S26). Furthermore, for tissue region 62 determined not to be divided, the association function 155a associates the cut-out portion with tissue region 62 based on the size of the cut-out portion and the size of tissue slice 60. Here, the processing of this flowchart ends.

[0100] (Modification 1 of the second embodiment) In the second embodiment described above, no particular restrictions were placed on the combination of two or more tissue regions 62 used to determine whether or not to divide. In contrast, in this modified example, the division presence / absence determination function 158 limits the tissue regions 62 that can be combined depending on the distance between the tissue regions 62 on the tissue image 61.

[0101] Generally, the divided tissue sections 60 are arranged close to each other, so that a combination of nearby tissue regions 62 is likely to be an appropriate combination of divided tissue sections 60 .

[0102] When selecting a combination of multiple tissue regions 62 to use in determining whether or not to divide, the division determination function 158 of this embodiment selects a combination of a certain tissue region 62 and another tissue region 62 that has the shortest distance from the tissue region 62.

[0103] 15 is a diagram showing an example of a combination of divided tissue slices according to Modification 1 of the second embodiment. For example, in the example shown in FIG. 15, of the multiple tissue regions 62 on the tissue image 61, the tissue region 62 located closest to tissue region 62m is tissue region 62n. In this case, when selecting a combination of the multiple tissue regions 62 to use in determining whether or not to divide, division presence / absence determination function 158 selects the combination of tissue region 62m and tissue region 62n. Furthermore, although tissue region 62p has the same length as tissue region 62n, it is not the tissue region closest to tissue region 62m, so division presence / absence determination function 158 does not select the combination of tissue region 62m and tissue region 62p.

[0104] Furthermore, if the sum of the lengths of the two tissue regions 62 does not reach the length of the cut-out position, the division presence / absence determination function 158 may add to the combination, among the tissue regions 62 other than the two tissue regions 62, the tissue region 62 that is closest to either of the two tissue regions 62. In the example shown in Fig. 15, the division presence / absence determination function 158 adds to the combination tissue region 62q that is closest to tissue region 62p, because the combination of tissue region 62o and tissue region 62p is less than the length of the cut-out position.

[0105] According to this modification, the presence or absence of division of each tissue region 62 is determined based on the arrangement of the tissue slice 60, thereby improving the accuracy of determining the presence or absence of division and of identifying the correspondence between the tissue slice 60 and the cut-out position on the specimen image 51.

[0106] (Modification 2 of the second embodiment) Furthermore, when selecting a combination of multiple tissue regions 62 to be used for determining whether or not to divide, the division presence / absence determination function 158 may limit the tissue regions 62 that can be combined to those tissue regions 62 whose distance is equal to or less than a threshold. The threshold for the distance between the tissue regions 62 is not particularly limited. The threshold may be set by the user or may be determined in advance.

[0107] For example, the division determination function 158 compares the length of the cut-out portion with the sum of the lengths of multiple tissue regions 62 that are at a distance less than a threshold value (e.g., 5 mm) of the distance of the slice regions that are allowed as a combination, and if the difference is less than the threshold value, it determines that the multiple tissue regions 62 have been divided.

[0108] 16 is a diagram showing an example of a combination of divided tissue slices according to Modification 2 of the second embodiment. In the example shown in Fig. 16, the distance between tissue region 62m and tissue region 62n is 2 mm, which is less than the threshold value. In this case, division presence / absence determination function 158 selects tissue region 62m and tissue region 62n as a combination for determining whether or not to divide.

[0109] Furthermore, since the distance between tissue region 62o and tissue region 62q is 3 mm, division determination function 158 selects tissue region 62o to tissue region 62q and tissue region 62p located between tissue region 62o and tissue region 62q as combinations when determining whether or not to divide.

[0110] (Third embodiment) In this third embodiment, a specific description will be given of how to specify the correspondence between the tissue slice 60 and the cut-out position on the specimen image 51 based on the cut-out portion and the thickness of the tissue slice 60.

[0111] FIG. 17 is a diagram showing an example of association between an excised portion and a tissue region 62m according to the third embodiment.

[0112] The cutout size specification function 153 of this embodiment specifies the thickness of a plurality of equally spaced locations in the cutout portion. In the example shown in Fig. 17, the number of specified thickness locations is 10, but is not limited to this number.

[0113] Furthermore, the tissue region size specifying function 154 of this embodiment specifies the thickness of a portion of the tissue slice 60 corresponding to the portion of the excision site whose thickness has been specified. For example, the tissue region size specifying function 154 calculates the thickness of the portion of the tissue slice 60 corresponding to the portion of the excision site whose thickness has been specified, based on the vertical width of the tissue region 62 on the tissue image 61 and the scale of the tissue image 61.

[0114] In addition, the association function 155 of this embodiment compares the thickness of each cut-out portion with the thickness of the tissue region 62, and associates the cut-out portion with the tissue region 62m when the difference between the thicknesses is below a threshold value (e.g., 0.05 mm).

[0115] (Modification 1 of the third embodiment) The association function 155 may compare the thickness of each cut-out portion with the thickness of the tissue region 62 without using a threshold value, and associate the cut-out portion with the tissue region 62 if the thicknesses match.

[0116] (Modification 2 of the third embodiment) Furthermore, the second and third embodiments may be combined. The processing circuit 150 of this modification includes a division presence / absence determination function 158.

[0117] For example, in Figures 11 and 12 of the second embodiment, an example is given of determining whether or not a tissue slice 60 has been divided based on the length of the excision site and the length of the tissue slice 60 along the excision direction, but the division determination function 158 may also determine whether or not two or more tissue slices 60 have been divided based on the thickness at the excision site and the thickness of any two or more tissue slices 60.

[0118] Fig. 18 is a diagram showing an example of determining whether or not to divide tissue regions 62m, 62n according to Modification 2 of the third embodiment. In the example shown in Fig. 18, division determination function 158 compares the thickness of each cut-out portion with the thickness of each portion in each tissue region 62m, 62n included in the combination of multiple tissue regions 62m, 62n, and determines that the multiple slice regions have been formed by division if the difference between the thicknesses is equal to or less than a threshold. The specific thickness portions in tissue regions 62m, 62n that are compared with the specific thickness portions in the cut-out portions are positions that correspond to the specific thickness portions in the cut-out portions.

[0119] In addition, the division determination function 158 may determine that multiple slice areas have been divided when the thickness of each cut-out portion matches the thickness of each portion in each tissue area 62m, 62n included in the combination of multiple tissue areas 62m, 62n, without using a threshold value.

[0120] In addition, the division determination function 158 may determine whether two or more tissue slices 60 have been divided based on both the length and thickness of the excision site and the length and thickness of the tissue slice 60.

[0121] (Fourth embodiment) In the fourth embodiment, the association function 155 associates the excision sites with the tissue regions 62 based on excision order information that defines the order in which the tissue slices 60 are excised from the specimen 5 and on the arrangement rules for the tissue slices 60. Note that the association function 155 may use both the excision order information and the arrangement rules for the tissue slices 60, or may use either one of them.

[0122] The cut-out order information that defines the cut-out order of the tissue slices 60 is an example of arrangement information of the cut-out portions in this embodiment. The content of the cut-out order information may be, for example, "the cut-out positions are arranged in order from the top of the specimen image 51 in the order in which they were cut out from the specimen 5."

[0123] The arrangement rule for the tissue slices 60 is an example of arrangement information for the tissue regions 62 in this embodiment. The content of the arrangement rule for the tissue slices 60 is, for example, that the tissue slices 60 are arranged in the order in which they were cut out from the specimen 5, with the mucous membrane facing upward in the tissue image 61. Note that the cut-out order information and the arrangement information for the tissue regions 62 are not limited to the above examples.

[0124] Fig. 19 is a diagram showing an example of association between cut-out sites and tissue regions according to the fourth embodiment. In the example shown in Fig. 19, the specimen 5 depicted in the specimen image 51 is cut out in order from the top of the specimen image 51 based on the cut-out order information. Furthermore, the tissue regions 62 on the tissue image 61 are arranged in order from the top of the tissue image 61, with the mucous membrane direction facing the top of the tissue image 61, based on the arrangement rule of the tissue slice 60.

[0125] The length of the cut-out portion corresponding to cut-out line 53a is 10.1 mm, and the length of the cut-out portion corresponding to cut-out line 53d is 9.9 mm.

[0126] Furthermore, among the plurality of tissue regions 62s to 62w on the tissue image 61, the length of the tissue slice 60 corresponding to the tissue region 62s is 10.2 mm, and the length of the tissue slice 60 corresponding to the tissue region 62v is 9.8 mm.

[0127] The difference between the length of the excision portion corresponding to the excision line 53a and the length of the tissue slice 60 corresponding to the tissue region 62s, and the difference between the length of the excision portion corresponding to the excision line 53a and the length of the tissue slice 60 corresponding to the tissue region 62v are both below a threshold value.

[0128] In this case, there are two tissue regions 62s and 62v as candidates for associating the cut-out portion corresponding to the cut-out line 53a.

[0129] In this way, when there are multiple tissue regions 62 as candidates for association with one cut-out portion, the association function 155 of this embodiment associates the candidate that has the highest likelihood of arrangement when associated with the cut-out portion with the cut-out portion based on the cut-out order information and the arrangement rules of the tissue slices 60.

[0130] 19, the likelihood of the arrangement when tissue region 62s is associated with the cut-out portion corresponding to cut-out line 53a is higher than the likelihood of the arrangement when tissue region 62v is associated with the cut-out portion. Therefore, association function 155 associates tissue region 62s with the cut-out portion corresponding to cut-out line 53a.

[0131] (Modification 1 of the fourth embodiment) Moreover, the second embodiment and the fourth embodiment may be combined. The processing circuit 150 of this modification includes a division presence / absence determination function 158.

[0132] Fig. 20 is a diagram showing an example of association between cut-out portions and tissue regions 62 according to Modification 1 of the fourth embodiment. In the example shown in Fig. 20, the division determination function 158 of this modification determines that the tissue slice 60 cut out from one cut-out portion corresponding to the cut-out line 53a has been divided and depicted in the tissue image 61 as tissue regions 62ad and 62ae.

[0133] In this case, the association function 155 determines the order of the tissue regions 62ad, 62ae based on the cut-out order information and the arrangement rules of the tissue slice 60, and then associates the tissue regions 62ad, 62ae with the cut-out site corresponding to the cut-out line 53a in accordance with the determined order.

[0134] For example, the association function 155 associates the tissue regions 62ad and 62ae with the cut-out portions corresponding to the cut-out line 53a based on the cut-out order information and the arrangement rules of the tissue slice 60 so as to maximize the likelihood of the arrangement.

[0135] (Modification 2 of the fourth embodiment) In this modified example, variations of the cutting order information that defines the cutting order of the tissue slices 60 will be described.

[0136] For example, the cut-out order information may be set by a user. Fig. 21 is a diagram showing an example of cut-out order information according to Modification 1 of the fourth embodiment. In the example shown in Fig. 21, it is assumed that the user has input numbers "1" to "5" indicating the order of the cut-out positions indicated by cut-out lines 53a to 53e onto the sample image 51.

[0137] Alternatively, the association function 155 may acquire the order of the cutout positions from a setting file or the like.

[0138] Alternatively, the association function 155 may determine the order of the cutout positions from the coordinate information of the cutout portions, and use the determination result as cutout order information. For example, the association function 155 may specify the order of the cutout positions based on the direction in which the midpoints of the cutout portions are aligned, or the direction in which both ends of the cutout portions are aligned, or the like.

[0139] Fig. 22 is a diagram showing another example of the cut-out order information according to Modification 1 of the fourth embodiment. In the example shown in Fig. 22, the association function 155 determines that the cut-out positions are arranged in order from the top of the sample image 51 along the direction in which the midpoints of the cut-out portions are arranged.

[0140] (Modification 3 of the fourth embodiment) In this modification, a variation in the arrangement rule of the tissue slice 60 will be described.

[0141] For example, the arrangement rule of the tissue slice 60 may be set by the user, or the association function 155 may acquire the arrangement rule of the tissue slice 60 from a setting file or the like.

[0142] Furthermore, the association function 155 may identify the arrangement rule of the tissue slices 60 by performing image processing on the tissue image 61. For example, the association function 155 determines the mucosal direction by image processing, and identifies the arrangement rule of the tissue slices 60 by assuming that multiple tissue regions 62 are arranged in order from the mucosal direction in the tissue image 61.

[0143] Fig. 23 is a diagram showing an example of the arrangement rule for the tissue slice 60 according to Modification 3 of the fourth embodiment. In the example shown in Fig. 23, multiple tissue regions 62ag to 62ak are arranged in order from the top of the tissue image 61, with the mucous membrane direction facing the upper side of the tissue image 61.

[0144] 24 is a diagram showing another example of the arrangement rule for the tissue slice 60 according to the third modification of the fourth embodiment. In the example shown in Fig. 24, the multiple tissue regions 62al to 62at are lined up in order from the right side of the tissue image 61, with the mucous membrane direction facing the right side of the tissue image 61.

[0145] 25 is a diagram showing yet another example of the arrangement rule for the tissue slice 60 according to Modification 3 of the fourth embodiment. In the example shown in Fig. 25, the multiple tissue regions 62au to 62aw are arranged in order from the upper right side of the tissue image 61, with the mucous membrane direction facing the upper right side of the tissue image 61.

[0146] (Fifth embodiment) In the first to fourth embodiments described above, the information processing device 100 identified the correspondence between the tissue region 62 corresponding to the tissue slice 60 depicted in the tissue image 61 and the cut-out position on the specimen image 51. In this fifth embodiment, the information processing device 100 identifies not only the correspondence between the tissue region 62 and the cut-out position, but also the correspondence between an arbitrary region in the specimen image 51 and an arbitrary region in the tissue image 61.

[0147] 26 is a diagram showing an example of the overall configuration of an information processing system S according to the fifth embodiment. Similar to the first to fourth embodiments, the information processing system S according to this embodiment includes an information processing device 100, a specimen image storage device 201, a tissue image storage device 202, a first image capturing device 401, and a second image capturing device 402.

[0148] The processing circuitry 150 of the information processing device 100 of this embodiment includes a specimen image acquisition function 151, a tissue image acquisition function 152, a cutout size specification function 153, a tissue region size specification function 154, It includes a correspondence function 155a, a display control function 156, a reception function 157, a division presence / absence determination function 158, and a corresponding area specification function 159. The corresponding area specification function 159 is an example of a corresponding area specification unit.

[0149] The specimen image acquisition function 151, tissue image acquisition function 152, cutout size specification function 153, tissue region size specification function 154, reception function 157, and division presence / absence determination function 158 have the same functions as those in the first or second embodiment.

[0150] The correspondence function 155a of this embodiment has the same functions as those of the second embodiment, and determines the correspondence between a first position on the tissue image 61 and a second position on the specimen image 51 based on the result of the division presence / absence determination function 158 determining whether or not division is to be performed.

[0151] 27 is a diagram showing an example of a correspondence relationship between a first position on a tissue image 61 and a second position on a specimen image 51 according to the fifth embodiment. In the example shown in FIG. 27, a plurality of tissue slices 60 cut out from a specimen 5 depicted in the specimen image 51 are depicted as tissue regions 62ax to 62bc on the tissue image 61.

[0152] 27, the association function 155a of this embodiment associates a first position 72 on the tissue image 61 with a second position 71 on the specimen image 51 that corresponds to the first position. The second position 71 on the specimen image 51 is located on the excision site.

[0153] For example, when a first position 72 in a tissue image 61 is determined by a user's operation or the like, the matching function 155a identifies the second position 71 by converting the first position 72 in the tissue image 61 into a second position 71 in the cut-out portion based on the size of the cut-out portion and the size of the tissue slice 60, in the same way as when matching the cut-out portion with the tissue region 62.

[0154] In particular, if the cut-out tissue section 60 is divided, it may be difficult for the user to visually grasp the correspondence between the second position 71 on the specimen image 51 and the first position 72 on the tissue image 61. In the example shown in Fig. 27, the tissue region 62ax and the tissue region 62ay are formed by dividing one tissue section 60, but the correspondence function 155a of this embodiment determines the correspondence between the first position 72 and the second position 71 based on the determination result of the division presence / absence determination function 158 as to whether or not the tissue region 62ax and the tissue region 62ay have been cut out from one cut-out site.

[0155] 28 is a diagram showing an example of a position of interest on a sample image 51 and a corresponding position on a tissue image 61 according to the fifth embodiment. For example, assume that a position of interest is specified on the sample image 51 by a user operation. In this case, the position of interest becomes a second position 71. In addition, in this case, the association function 155a identifies a corresponding position on the tissue image 61 that corresponds to the position of interest on the sample image 51. In this case, the corresponding position on the tissue image 61 becomes a first position 72.

[0156] Furthermore, when a second position 71 in the cut-out portion in the specimen image 51 is determined by a user operation or the like, the association function 155 identifies the first position 72 by converting the second position 71 in the specimen image 51 into a first position 72 in the tissue image 61 based on the size of the cut-out portion and the size of the tissue slice 60. Note that when the tissue slice 60 is divided into multiple pieces, the association function 155a identifies the first position 72 based on the total size of the multiple sections after division and the size of the cut-out portion.

[0157] 29 is a diagram showing an example of a position of interest on a tissue image 61 and a corresponding position on a sample image 51 according to the fifth embodiment. In the example shown in FIG. 29, for example, a position of interest is specified on the tissue image 61 by a user operation. In this case, the position of interest becomes a first position 72. In addition, in this case, the association function 155a identifies a corresponding position on the sample image 51 that corresponds to the position of interest on the tissue image 61. In this case, the corresponding position on the sample image 51 becomes a second position 71.

[0158] Furthermore, the corresponding region identifying function 159 identifies a first region 701 on the tissue image 61 based on the first position 72 identified by the association function 155a, and identifies a second region 702 on the specimen image 51 based on the second position 71. The first region 701 is a region of a predetermined size that includes the first position 72. The second region 702 is a region of a predetermined size that includes the second position 71. The sizes of the first region 701 and the second region 702 are not particularly limited, and may be set by the user or may be predetermined, for example. The predetermined sizes of the first region 701 and the second region 702 may be different.

[0159] The first region 701 is a region of interest on the tissue image 61 , and the second region 702 is a region of interest on the specimen image 51 .

[0160] Fig. 30 is a diagram showing an example of a first region 701 on a tissue image 61 according to the fifth embodiment. Although the first position 72 is not shown in Fig. 30, the first region 701 shown in Fig. 30 is a region of a specified size centered on the first position 72 shown in Fig. 28.

[0161] Fig. 31 is a diagram showing an example of a second region 702 on a sample image 51 according to the fifth embodiment. Although the second position 71 is not shown in Fig. 31, the second region 702 shown in Fig. 31 is a region of a specified size centered on the second position 71 shown in Fig. 28.

[0162] Returning to FIG. 26, the display control function 156 has the same functions as in the second embodiment and displays first area information representing the first area 701 and second area information representing the second area 702 on the display 140.

[0163] Fig. 32 is a diagram showing an example of the display of first region information representing a first region 701 and second region information representing a second region 702 according to the fifth embodiment. In the example shown in Fig. 32, the display control function 156 causes the display 140 to display a tissue image 61 on which a rectangle representing the first region 701 is superimposed and displayed, and a specimen image 51 on which a rectangle representing the second region 702 is superimposed and displayed.

[0164] The rectangle representing the first region 701 is an example of first region information and a graphic representing the first region 701. The rectangle representing the second region 702 is an example of second region information and a graphic representing the second region 702.

[0165] 33 is a diagram showing another example of the display of first region information representing the first region 701 and second region information representing the second region 702 according to the fifth embodiment. In the example shown in Fig. 32, the display control function 156 causes the display 140 to display a first enlarged image 670 obtained by cutting out and enlarging the first region 701 from the tissue image 61, and a second enlarged image 570 obtained by cutting out and enlarging the second region 702 from the specimen image 51.

[0166] The first enlarged image 670 is an example of first region information. The second enlarged image 570 is an example of second region information. The enlargement ratios of the first enlarged image 670 and the second enlarged image 570 may be different. The center positions of the first enlarged image 670 and the second enlarged image 570 are defined as a first position 72 and a second position 71, respectively.

[0167] 33, the center positions of the first enlarged image 670 and the second enlarged image 570 are aligned, but the first enlarged image 670 and the second enlarged image 570 may be displayed based on another position. For example, the display control function 156 may display the first enlarged image 670 and the second enlarged image 570 so that they are aligned at predetermined positions such as the upper left positions of the first area 701 and the second area 702, or at positions designated by the user.

[0168] The display control function 156 may display both the tissue image 61 displayed with a rectangle representing the first region 701 superimposed thereon and the specimen image 51 displayed with a rectangle representing the second region 702 superimposed thereon, as well as the first enlarged image 670 and the second enlarged image 570 shown in Fig. 33, on the display 140. In this case, the display control function 156 may display only either the first enlarged image 670 or the second enlarged image 570.

[0169] Furthermore, the display control function 156 may switch between displaying the tissue image 61 on which a rectangle representing the first region 701 is superimposed and the specimen image 51 on which a rectangle representing the second region 702 is superimposed, in response to a user operation, rather than displaying these images side by side. The display control function 156 may also superimpose and display the second enlarged image 570 on the tissue image 61 on which a rectangle representing the first region 701 is superimposed. The display control function 156 may also superimpose and display the first enlarged image 670 on the specimen image 51 on which a rectangle representing the second region 702 is superimposed.

[0170] FIG. 34 is a flowchart showing an example of the flow of the association process according to the fifth embodiment.

[0171] The processes of acquiring the specimen image 51 in S31 and acquiring the tissue image 61 in S32 are similar to the processes of S11 and S13 in the first embodiment shown in Fig. 9. The process of determining division in S33 is similar to the process of S25 shown in Fig. 14.

[0172] Next, the reception function 157 acquires the position of interest on the tissue image 61 or the specimen image 51 designated by the user's operation (S34).

[0173] Then, the association function 155a identifies a corresponding position on the specimen image 51 or tissue image 61 that corresponds to the position of interest on the tissue image 61 or specimen image 51 (S35).

[0174] Then, the corresponding area specifying function 159 specifies a first area 701 on the tissue image 61 and a second area 702 on the specimen image 51 (S36).

[0175] Then, the display control function 156 causes the display 140 to display the first information representing the first area 701 and the second information representing the second area 702 (S37). Here, the processing of this flowchart ends.

[0176] In this way, the information processing device 100 of this embodiment determines the correspondence between the first position on the tissue image 61 and the second position on the specimen image 51 based on the result of the determination by the division presence / absence determination function 158. Furthermore, the information processing device 100 of this embodiment displays first information representing the first region 701 and second information representing the second region 702 on the display 140. Therefore, in addition to the same effects as those of the first and second embodiments, the information processing device 100 of this embodiment allows the user to easily grasp the correspondence between the first position 72 on the tissue image 61 and the second position 71 on the specimen image 51 even when the tissue slice 60 is divided into multiple parts.

[0177] (Sixth embodiment) In the above-described fifth embodiment, an example was given in which the first region 701 is not on the division position of the tissue slice 60 in the tissue image 61. However, there is a case in which the first region 701 includes the division position of the tissue slice 60 in the tissue image 61. In this sixth embodiment, when the first region 701 includes the division position of the tissue slice 60, the information processing device 100 displays a joined enlarged image that shows a state in which the multiple tissue slices 60 included in the first region 701 are joined at the division position.

[0178] The processing circuit 150 of the information processing device 100 of this embodiment has a concatenated image generating function in addition to the same configuration as in the fifth embodiment. The concatenated enlarged image generating unit is an example of the concatenated enlarged image generating unit.

[0179] When the first region 701 includes a division position of the tissue slice 60, the connected enlarged image generation unit generates a connected enlarged image that represents the state in which multiple tissue slices 60 included in the first region 701 are joined at the division position.

[0180] Fig. 35 is a diagram showing an example of a connected enlarged image 660 according to the sixth embodiment. As shown in Fig. 35, first regions 701a and 701b on the tissue image 61 corresponding to the second region 702 on the specimen image 51 include the division positions of the tissue regions 62bd and 62be.

[0181] In this way, when the division position of the tissue slice 60 is included within the first region 701, the display control function 156 of this embodiment divides the figure representing the first region 701 at the division position, and displays the divided figures superimposed on the multiple tissue regions 62bd, 62be on the tissue image 61 corresponding to the divided tissue slice 60.

[0182] In this case, the combined magnified image generating unit generates a combined magnified image 660 that represents a state in which the portions of the tissue region 62bd and the tissue region 62be that are included in the first regions 701a and 701b are joined at the division position. Specifically, the combined magnified image generating unit generates a combined magnified image 660 in which the tissue region 62bd and the tissue region 62be are adjacent to each other at the division position.

[0183] Then, the display control function 156 of this embodiment causes the enlarged connected image 660 to be displayed on the display 140.

[0184] According to the information processing device 100 of this embodiment, when the first area 701 includes the division position of the tissue slice 60, a concatenated enlarged image 660 is displayed, which shows the state in which the multiple tissue slices 60 included in the first area 701 are joined at the division position, so that even when the first area 701 includes the division position of the tissue slice 60 in the tissue image 61, the user can understand the state in which the multiple tissue slices 60 are joined at the division position.

[0185] (Seventh embodiment) In the seventh embodiment, when a tissue slice 60 is divided, the information processing device 100 generates a connective tissue image from a tissue image 61 in which the division positions of each tissue region 62 are arranged adjacent to each other.

[0186] The processing circuitry 150 of the information processing device 100 of this embodiment has a connective tissue image generating function in addition to the same configuration as in the fifth embodiment. The connective tissue image generating function is an example of a connective tissue image generating section.

[0187] Fig. 36 is a diagram showing an example of a connective tissue image 67 according to the seventh embodiment. As shown in Fig. 36, the connective tissue image generation function generates a connective tissue region 62bde by combining divided tissue region 62bd and tissue region 62be so that their division positions are adjacent, based on the presence or absence of division determined by division presence / absence determination function 158. The connective tissue image generation function also combines other divided tissue regions 62 included in the tissue image 61 so that their division positions are adjacent.

[0188] The display control function 156 of this embodiment may display a graphic representing the first region 701 on the connective tissue image 67, and may also display a graphic representing the second region 702 on the specimen image 51. The graphic representing the first region 701 and the graphic representing the second region 702 are, for example, rectangular shapes similar to those in FIG.

[0189] Furthermore, the display control function 156 of this embodiment displays the connective tissue image 67 on the display 140 so that the size of the connective tissue image 67 and the size of the portion of the specimen image 51 that corresponds to the connective tissue image 67 are approximately the same. By matching the sizes when displayed on the display 140 in this way, the user can easily grasp the correspondence between the specimen 5 depicted in the specimen image 51 and the tissue slice 60 depicted in the connective tissue image 67.

[0190] (Modifications of the fifth to seventh embodiments) Furthermore, the processing circuitry 150 of the information processing device 100 may further include a correction function for correcting the focus position designated by the user. The correction function is an example of a correction section.

[0191] 37 is a diagram showing an example of correction of the position of interest on a tissue image 61 according to the modifications of the fifth to seventh embodiments. When a position outside the tissue region 62 on the tissue image 61 is designated by the user as the position of interest (second position 71), the correction function moves the position of interest to a position on the tissue region 62 that is closest to the designated position of interest. Alternatively, as shown in FIG. 37, when the position of interest designated by the user is near the division position, the correction function moves the position of interest to a position on the tissue region 62 that would have been continuous if the tissue slice 60 had not been divided.

[0192] 38 is a diagram showing an example of correction of a position of interest on a sample image 51 according to the modifications of the fifth to seventh embodiments. When a position on the sample image 51 that is off the cut-out line 53 is specified by the user as a position of interest, the correction function moves the position of interest to a position on the cut-out line 53 that is closest to the specified position of interest.

[0193] According to the information processing device 100 of this modified example, by correcting the attention position in this way, even if the user is unfamiliar with the operation, the attention position can be set at an appropriate position for diagnosis or the like.

[0194] The various data handled in this specification are typically digital data.

[0195] According to at least one of the embodiments described above, it is possible to identify with high accuracy the correspondence between the tissue slice depicted in the tissue image and the cut-out position on the sample image.

[0196] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0197] 5 specimens 6 Tissue specimen 51 Sample images 53, 53a~53e Cutting lines 60,60a~60e tissue section 61 Tissue Images 62,62a~62z,62aa~62az,62ba~62bi tissue area 62bde,62bfg,62bhi Consolidated tissue area 67 Connective Tissue Images 71 Second Position 72 First Position 100 Information processing device 110 Network Interface 120 Memory circuit 130 Input Interface 140 Display 150 Processing Circuit 151 Sample image acquisition function 152 Tissue image acquisition function 153 Cutout size specification function 154 Tissue area size identification function 155,155a Mapping function 156 Display Control Function 157 Reception Function 158 Split presence / absence determination function 159 Corresponding area identification function 201 Sample Image Storage Device 202 Tissue Image Storage Device 300 Network 401 First imaging device 402 Secondary Camera 510 Specimen Area 570 Second Enlarged Image 660 linked enlarged images 670 First Enlarged Image 701,701a,701b First Region 702 Second Realm S Information Processing System

Claims

1. an excision size acquisition unit that acquires the size of an excision site set on a pathological specimen when a tissue slice is excised from the pathological specimen; a tissue image acquisition unit for acquiring a tissue image obtained by photographing the tissue slice; a tissue slice size specifying unit that specifies the size of the tissue slice depicted in the tissue region of the tissue image; a correlation unit that correlates the excised portion with the tissue region in which the tissue slice is depicted on the tissue image based on the size of the excised portion and the size of the tissue slice; An information processing device comprising:

2. a specimen image acquisition unit that acquires a specimen image obtained by photographing the pathological specimen; the cutout size acquisition unit acquires the size of the cutout region based on the size of the cutout region depicted on the sample image and the scale of the sample image. The information processing device according to claim 1 .

3. the associating unit associates the excision site with the tissue region corresponding to the tissue slice when a difference between the length of the excision site and the length of the tissue slice is equal to or less than a threshold value; 3. The information processing device according to claim 1.

4. the associating unit associates the excision site with the tissue region corresponding to the tissue section based on thicknesses of multiple locations in the excision site and thicknesses of multiple locations in the tissue section; The information processing device according to claim 1 .

5. the tissue image includes a plurality of tissue regions in which a plurality of tissue slices are depicted; a division determination unit that determines whether or not the plurality of tissue sections corresponding to the plurality of tissue regions are divided based on the size of the excision site and the size of the plurality of tissue regions, the associating unit associates the cut-out portion with the plurality of tissue regions based on a determination result of the division presence / absence determining unit. The information processing device according to claim 1 .

6. the division determination unit determines that the two or more tissue slices are formed by dividing a single tissue slice when a difference between a length of the cut-out portion and a total length of two or more tissue slices corresponding to any two or more tissue regions among the plurality of tissue regions depicted in the tissue image is equal to or less than a predetermined threshold value; The information processing device according to claim 5 .

7. the division determination unit determines a division state of the tissue section based on thicknesses at multiple locations in the excision site and thicknesses at multiple locations in any two or more of the tissue regions.

7. The information processing device according to claim 5 or 6.

8. When selecting a combination of a plurality of tissue regions to be used for determining whether or not to divide the tissue region, the division determination unit selects a combination of a certain tissue region and another tissue region that has a minimum distance from the certain tissue region. The information processing device according to claim 5 .

9. the division presence / absence determination unit selects a combination of tissue regions in which a distance between the tissue regions is equal to or less than a predetermined threshold when selecting a combination of a plurality of tissue regions to be used for determining whether or not to divide the tissue regions. The information processing device according to claim 5 .

10. The associating unit further associates the cut-out portion with the tissue region based on location information of the cut-out portion or location information of the tissue region. The information processing device according to claim 1 .

11. the tissue image includes a plurality of tissue regions in which a plurality of tissue slices are depicted; a division determination unit that determines whether or not the plurality of tissue sections corresponding to the plurality of tissue regions are divided, the associating unit specifies a correspondence relationship between a first position on the tissue image and a second position on the sample image based on a result of the determination by the division presence / absence determining unit. The information processing device according to claim 2 .

12. a corresponding region specifying unit that calculates a first region on the tissue image that includes the first position based on the first position, and specifies a second region on the sample image that includes the second position based on the second position; a display control unit that causes a display unit to display first region information representing the first region and second region information representing the second region, The information processing device according to claim 11.

13. the display control unit causes the display unit to display a first enlarged image obtained by cutting out and enlarging the first region from the tissue image and a second enlarged image obtained by cutting out and enlarging the second region from the sample image. The information processing device according to claim 12.

14. the display control unit causes a graphic representing the first region to be displayed on the tissue image, and causes a graphic representing the second region to be displayed on the specimen image; 14. The information processing device according to claim 12 or 13.

15. a combined enlarged image generating unit configured to generate a combined enlarged image representing a state in which a plurality of tissue slices included in the first region are joined at the division position when the division position of the tissue slice is included in the first region, the display control unit displays the enlarged connected image as an image in the first region. The information processing device according to any one of claims 12 to 14.

16. when a division position of the tissue slice is included in the first region, the display control unit divides a figure representing the first region at the division position, and displays the divided figures superimposed on a plurality of tissue regions on the tissue image corresponding to the divided tissue slices, respectively. The information processing device according to any one of claims 12 to 14.

17. a connective tissue image generating unit configured to generate, from the tissue image, a connective tissue image in which the divided positions of the tissue regions are arranged adjacent to each other when the tissue section is divided, the display control unit causes a graphic representing the first region to be displayed on the connective tissue image, and causes a graphic representing the second region to be displayed on the specimen image. The information processing device according to any one of claims 12 to 14.

18. the display control unit causes the display unit to display the connective tissue image so that a size of the connective tissue image and a size of a portion of the sample image corresponding to the connective tissue image are approximately equal to each other. The information processing device according to claim 17.

19. an excision size acquisition step in which the information processing device acquires the size of an excision site set on the pathological specimen when cutting out a tissue slice from the pathological specimen; a tissue image acquisition step in which the information processing device acquires a tissue image obtained by photographing the tissue slice; a tissue slice size specifying step in which the information processing device specifies a size of the tissue slice depicted in the tissue region of the tissue image; a correspondence step in which the information processing device corresponds the excised portion to the tissue region in which the tissue slice is depicted on the tissue image based on the size of the excised portion and the size of the tissue slice; An information processing method including:

20. an excision size acquisition step of acquiring the size of an excision site set on the pathological specimen when a tissue slice is excised from the pathological specimen; a tissue image acquisition step of acquiring a tissue image of the tissue slice; a tissue slice size specifying step of specifying a size of the tissue slice depicted in the tissue region of the tissue image; a matching step of matching the excision region with the tissue region in which the tissue slice is depicted on the tissue image based on the size of the excision region and the size of the tissue region; A program that causes a computer to execute the following.

Images