JP7807783B2 - Computer program, information processing device, and information processing method - Google Patents

Description

The present invention relates to a computer program, an information processing device, and an information processing method.

Technology is evolving to support doctors in their diagnoses by performing the required image analysis processing on image data obtained from various types of examination equipment (modalities), including MRI (Magnetic Resonance Imaging), X-ray CT (Computed Tomography), and PET (Positron Emission Tomography), to display images of various abnormal areas in the brain and other parts of the body, or to quantify and quantify them.

Meanwhile, various disease treatment guidelines and imaging diagnostic guidelines have been published for the purpose of diagnosing various diseases, and are used by doctors to make diagnoses. Patent Document 1 discloses a method for assigning recommended and non-recommended tags to multiple sentences extracted by analyzing treatment guidelines, and then converting the sentences assigned recommended tags into a computer-interpretable model.

Japanese Patent Application Laid-Open No. 2021-12681

When a doctor diagnoses an abnormality, they need to know how that abnormality is treated in the guidelines. However, in the past, this required doctors to flip through the pages of the guidelines to find the appropriate section or to search the guidelines on a computer, which placed unnecessary effort on the doctor.

The present invention was made in light of these circumstances, and aims to provide a computer program, information processing device, and information processing method that can improve convenience for doctors.

The present application includes multiple means for solving the above problem. As an example, a computer program causes a computer to execute the following process: acquire medical data including medical images; display abnormal areas identified by analyzing the acquired medical data; and, when a first operation on the abnormal area is received, display a guideline related to the abnormal area.

The present invention can provide necessary guidelines and improve convenience for doctors.

FIG. 1 is a diagram illustrating a first example of a configuration of an information processing system according to an embodiment of the present invention. FIG. 1 illustrates an example of a configuration of an information processing device. FIG. 1 shows an example of a brain-related abnormality. FIG. 10 is a diagram showing an example of an abnormality related to a region other than the brain. FIG. 10 is a diagram showing an example of an analysis result of a medical image. FIG. 10 is a diagram showing a first example of a guideline display. FIG. 10 is a diagram illustrating a first example of a method for selecting a guideline. FIG. 10 is a diagram showing an example of a display mode of a guideline. FIG. 10 is a diagram showing a second example of display of a guideline. FIG. 10 is a diagram showing a third example of display of a guideline. FIG. 10 is a diagram showing a fourth example of a guideline display. FIG. 10 is a diagram illustrating an example of history information. FIG. 10 is a diagram illustrating a second example of a method for selecting a guideline. FIG. 10 is a diagram showing a fifth example of a guideline display. FIG. 10 is a diagram illustrating a second example of the configuration of the information processing system according to the present embodiment. FIG. 10 is a diagram illustrating an example of the configuration of a guideline DB. FIG. 10 is a diagram illustrating an example of a processing procedure of an information processing device.

Embodiments of the present invention will now be described with reference to the accompanying drawings. FIG. 1 illustrates a first example of the configuration of an information processing system according to this embodiment. The information processing system includes an information processing device 100. A client device 60 and a web server 200 are connected to the information processing device 100 via a communication network 1. The client device 60 may be configured, for example, as a personal computer, and has a web browser 61, an image viewer, and the like installed. The web server 200 contains a guideline page 210. An image server 50 is connected to the client device 60. The image server 50 receives medical data, including image data and examination data, from an MRI (Magnetic Resonance Imaging) device 10, a PET (Positron Emission Tomography) device 20, a CT (Computed Tomography) device 30, and an examination device 40, and stores the data in a database. The client device 60 acquires medical data from the image server 50 and transmits the acquired medical data to the information processing device 100. The information processing device 100 can identify abnormal areas by analyzing medical data and transmit required information, such as guidelines related to the identified abnormal areas, to the client device 60. The client device 60 can display the guidelines related to the abnormal areas.

Figure 2 is a diagram showing an example of the configuration of the information processing device 100. The information processing device 100 can be configured as a computer, and includes a control unit 101 that controls the entire information processing device 100, a communication unit 102, a memory 103, an analysis unit 104, a display control unit 105, a storage unit 106, and a guideline providing unit 109. The storage unit 106 stores a computer program 107 and history information 108.

The control unit 101 can be configured with a CPU (Central Processing Unit), MPU (Micro-Processing Unit), GPU (Graphics Processing Unit), etc. The control unit 101 can execute processing defined by the computer program 107. In other words, processing by the control unit 101 is also processing by the computer program 107.

The communication unit 102 includes, for example, a communication module and has the ability to communicate with the client device 60 and the web server 200 via the communication network 1. The communication unit 102 can acquire (receive) medical data, including medical images, from the client device 60.

Memory 103 can be configured with semiconductor memory such as SRAM (Static Random Access Memory), DRAM (Dynamic Random Access Memory), or flash memory. A computer program 107 can be loaded into memory 103, and the control unit 101 can execute the computer program 107.

The analysis unit 104 can perform the required analysis processing on the acquired medical data to identify abnormalities. Note that the analysis unit 104 may also be configured by combining multiple individual analysis units corresponding to different diseases. Details of abnormalities will be described later.

The guideline providing unit 109 identifies a uniform resource locator (URL) for displaying a web page of guidelines related to the abnormality identified by the analysis unit 104. The guideline providing unit 109 may provide not only the guidelines related to the abnormality, but also supplementary information when providing the guidelines.

The display control unit 105 generates a display image that visualizes the abnormal area identified by the analysis unit 104. The display control unit 105 can perform display control to display required information on the display screen of the client device 60.

The storage unit 106 can be configured, for example, with a hard disk or semiconductor memory, and may store necessary information in addition to the computer program 107 and history information 108. Details of the history information will be described later.

Next, abnormal regions will be described. Abnormal regions can be determined by analyzing medical images, including MRI images, PET images, SPECT images, X-ray images, and ultrasound images, and determining regions where indicators such as Z-score, SUVR (Standardized Uptake Value Ratio), centiloid, number and size of bleeding in a specific region, and location, number, or shape of abnormal regions satisfy certain conditions. MRI images include, for example, T1-weighted images, T2-weighted images, proton density-weighted images, FLAIR (Fluid-Attenuated Inversion Recovery) images, diffusion-weighted images, MRA (Magnetic Resonance Angiography) images, T2 ^* (T2 star)-weighted images, SWI (Susceptibility-Weighted Imaging) images, QSM (Quantitative Susceptibility Mapping) images, and R2 ^* images. PET images are generated by administering a radiopharmaceutical to a subject via intravenous injection or the like and capturing radiation emitted from the radiopharmaceutical within the body. Images using drugs allow doctors to understand not only the morphology of each part of the body but also how the administered drug is distributed in the body, or the accumulation of substances in the body that react with the drug, which can contribute to improving the accuracy of disease diagnosis. For example, PET images can be taken using what is commonly known as Pittsburgh compound B as a PET radiopharmaceutical (tracer), and the degree of accumulation of amyloid beta protein in the brain can be measured based on the taken PET images, which can be useful for differential diagnosis or early diagnosis of Alzheimer's disease. Furthermore, SPECT images can also be used to examine various parts of the body, such as cerebral blood flow tests for cerebrovascular disorders and dementia, depending on the type of drug.

Figure 3 shows an example of an abnormal area related to the brain. Each image shown in Figure 3 is a display image generated by the display control unit 105.

Figure 3A shows one slice image from a cross-sectional image of the patient's (subject's) brain. The hippocampus, which is the ROI (region of interest), is visualized as an abnormal area, showing the area of cerebral atrophy. Furthermore, Z-scores are displayed in color as quantitative and numerical data for the abnormal area. While the Z-score values are not shown in Figure 3A, they may also be displayed.

Taking an MRI image as an example, the average and standard deviation are calculated for each voxel from the MRI image of a normal case that has undergone brain morphology standardization processing, and the average image and standard deviation image are created by substituting the values of the data (normal standard brain) and the values of the subject's image data (processed image) into the following formula, which calculates the Z score.
z=(M(x,y,z)-I(x,y,z))/SD(x,y,z)
M and SD represent the mean and standard deviation images of a normal control brain, and I represents the processed image. Using the Z-score map, it is possible to quantitatively analyze which regions of a processed image are undergoing changes compared to a normal control brain. For example, voxels with positive Z-score values indicate areas of atrophy compared to a normal control brain, and the larger the value, the greater the statistical deviation. For example, a Z-score of "2" indicates a region exceeding two standard deviations from the mean, which is evaluated as having a statistically significant difference with a risk of approximately 5%. To quantitatively evaluate atrophy within a region, M, SD, and I are calculated for the region of interest, respectively, and the average of all positive Z-scores can be calculated.

Figure 3B displays a 3D image of the left lateral surface of the patient's brain. The abnormal area is visualized as a region of cerebral atrophy in the frontal lobe (left). Although not shown, the right lateral surface may also be displayed at the same time. Furthermore, Z scores are displayed in color as quantitative and numerical data for the abnormal area. Although the numerical values of the Z scores are not shown in Figure 3B, they may also be displayed.

Figure 3C shows a PET image of a patient. The abnormal area is visualized as a region of amyloid beta accumulation in the cerebral cortex. The SUVR value is displayed in color as quantitative and quantified data for the abnormal area. The PET image includes, for example, distribution information (e.g., SUVR values for each voxel) visualizing the distribution of amyloid beta, tau protein, or α-synuclein in the brain. SUVR can be calculated by summing the SUVs (Standardized Uptake Values: amyloid beta accumulation levels) of four regions of the cerebral gray matter (prefrontal cortex, anterior and posterior cingulate cortex, parietal lobe, and lateral temporal lobe) as regions of interest, and dividing them by the SUV of a specific reference region. The accumulation levels (SUVs) of amyloid beta, tau protein, or α-synuclein can be calculated, for example, by counting the number of voxels whose brightness values for each voxel constituting the desired region are equal to or greater than a predetermined threshold. Accumulation (e.g., 00%) can be calculated by the ratio of the count value to the total number of voxels in the desired region. The SUVR for each voxel is the SUV for a given voxel divided by the average SUV for the reference region. The SUVR for each region is the SUV for a given region divided by the average SUV for the reference region.

Figure 3D shows one slice image from the cross-sectional images of the patient's brain. A brain tumor is visualized as an abnormal area. Figure 3 is an example, and the abnormal area is not limited to the example in Figure 3. Also, Figure 3 is a schematic illustration of the abnormal area, and may differ from the actual image.

Figure 4 is a diagram showing an example of an abnormal area related to a body part other than the brain. Each diagram in Figure 4 is a display image generated by the display control unit 105. Figure 4A displays a patient's abdominal QSM (Quantitative Susceptibility Mapping) image, visualizing liver cirrhosis and hepatocellular carcinoma as abnormal areas. Figure 4B displays a patient's contrast-enhanced CT image, visualizing rectal cancer as abnormal areas. Figure 4C displays a patient's FDG (fluorodeoxyglucose)-PET/CT image, visualizing stomach cancer as abnormal areas. Figure 4 is an example, and abnormal areas are not limited to the example in Figure 4. Furthermore, Figure 4 is a schematic illustration of abnormal areas, and may differ from the actual image.

Next, we will explain an example of display on the client device 60.

Figure 5 shows an example of the analysis results of a medical image. Figure 5A shows the image input screen 300. On the image input screen 300, when a doctor selects a patient's medical image on the selection screen 301, the selected medical image 302 is displayed. When the doctor operates the "upload" icon 303, the medical image 302 is sent to the information processing device 100.

The information processing device 100 receives the medical image 302. The analysis unit 104 performs the required analysis processing on the received medical image to identify abnormal areas. The display control unit 105 generates a display image that visualizes the abnormal areas identified by the analysis unit 104, and transmits the generated display image to the client device 60.

Figure 5B shows the analysis results screen 400. On the analysis results screen 400, the medical image area 402 displays a medical image in which the abnormal area 406 is visualized. The patient information area 401 displays attribute information about the patient, such as the patient ID (which may include the name), date of birth, gender, date the medical image was uploaded, and date the medical image was taken. Although not shown, information such as the date of medication, number of medications, and therapeutic drug may also be displayed. The data area 403 displays a "Numerical display" icon 404 and a "Partial area name" icon 405. By operating the "Numerical display" icon 404, quantitative and numerical data related to the abnormal area 406 can be displayed. By operating the "Partial area name" icon 405, the name of the part related to the abnormal area 406, etc., can be displayed.

Next, we will explain examples of how guidelines may be displayed. Guidelines include publicly available guidelines, such as the Dementia Disease Treatment Guidelines included in the Japanese Society of Neurology's Clinical Practice Guidelines, the official guidelines of the Japanese Society of Radiation Oncology, and the diagnostic imaging guidelines included in the guidelines of the Japan Radiological Society. Note that in this specification, the literature and other documents contained in the guidelines are also included in the guidelines.

Figure 6 is a diagram showing a first example of a guideline display. As shown in Figure 6A, by performing a first operation (e.g., an operation of moving the cursor 407 to the abnormal portion 406, an operation of tapping the abnormal portion 406, etc.) on the abnormal portion 406 on the analysis result screen 400, a guideline display screen 410 such as that shown in Figure 6B can be displayed. The guideline display screen 410 may be switched to and displayed from the analysis result screen 400, or may be displayed superimposed on a portion of the analysis result screen 400. The guideline display screen 410 displays guidelines 411 related to the abnormal portion 406. The guidelines 411 describe information divided into categories such as summary, recommendations, explanations/evidence, and literature, but the category configuration is not limited to the example of Figure 6. Although not shown, by performing a similar first operation on other portions not identified as the abnormal portion 406, guidelines related to those portions may be displayed.

As described above, the control unit 101 acquires medical data including medical images, displays abnormal areas identified through analysis processing of the acquired medical data, and, when a first operation is received for the displayed abnormal area, displays guidelines related to the abnormal area.

As a result, doctors can simply view an image in which the abnormality is visualized and perform a predetermined first operation on the abnormality, which will display guidelines related to that abnormality. This eliminates the need to flip through pages of guidelines to find the appropriate location or search for guidelines on a computer, improving convenience for doctors. This is particularly helpful for doctors with little experience, as it can help improve their knowledge. It can also help improve the productivity of doctors with some experience.

The evaluation display area 412 displays an evaluation value for the displayed guideline 411. That is, the control unit 101 may display an evaluation for the guideline when displaying the guideline. This allows the doctor to evaluate the validity of the displayed guideline.

The number of times the displayed guideline 411 has been viewed in the past is displayed in the view count display area 413. That is, the control unit 101 may record the number of times the displayed guideline has been viewed in the history information 108 each time it is displayed, and may display the number of times the guideline has been viewed when a guideline related to an abnormality is displayed. This allows the doctor to understand how often the displayed guideline 411 has been viewed in the past, and easily understand that the displayed guideline 411 is useful.

Although not shown, details of terms in the guidelines or cited literature may be displayed by selecting the details of the terms or literature.

Figure 7 shows a first example of a guideline selection method. The control unit 101 extracts keywords related to the abnormal area identified by the analysis unit 104. For example, if the abnormal area is cerebral atrophy of the frontal lobe and the Z-score value indicates atrophy, keywords such as "brain," "frontal lobe," "cerebral atrophy," and "Z-score" can be extracted. As shown in Figure 7, assume that W1, W2, and W3 are extracted as keywords. Also assume that guidelines A to F are pre-associated as guidelines related to the identified abnormal area. The control unit 101 searches the text within each guideline A to F, counts the number of occurrences of keywords W1, W2, and W3, and calculates the total number of occurrences. The control unit 101 can select the guideline with the highest total number of keyword occurrences among guidelines A to F (guideline C in the example of Figure 7) as the guideline related to the abnormal area. Note that the control unit 101 may select guidelines whose total number of occurrences is equal to or exceeds a predetermined threshold, or a predetermined number of guidelines with the highest total number of occurrences.

Figure 8 is a diagram showing an example of the display format of guidelines. In the example of Figure 8, keywords in the text of the guidelines (in the example of Figure 8, "T1-weighted image," "cerebral cortex," "VBM analysis," "Z-score," "amyloid beta," and "tau") are highlighted (enclosed in a frame in the example of Figure 8). In this way, the control unit 101 may extract keywords related to abnormalities and display keywords included in the guidelines related to those abnormalities in a specific display format. This allows the doctor to easily find parts of the text of the displayed guidelines that are particularly related to the abnormality.

Figure 9 is a diagram showing a second example of guideline display. As shown in Figure 9A, by performing a first operation (e.g., an operation of moving cursor 407 to abnormal portion 406, an operation of tapping abnormal portion 406, etc.) on abnormal portion 406 on analysis result screen 400, guideline display screen 420 as shown in Figure 9B can be displayed. Selection information 421 is displayed on guideline display screen 420. Selection information 421 displays multiple selectable guidelines related to the abnormal portion. In the example of Figure 9B, guidelines A, B, ... are displayed selectable. When guideline B is selected in selection information 421, guideline 422 is displayed. Although not shown, a similar first operation may be performed on other portions not identified as abnormal portion 406 to display multiple selectable guidelines related to those portions.

As described above, when the control unit 101 receives a first operation for an abnormal area, it may display selection information for selecting multiple guidelines related to the abnormal area and display the guideline selected by the selection information. If there are multiple guidelines related to the identified abnormal area, it may be possible to display all of the multiple guidelines simultaneously, but this would be cumbersome. Therefore, by having the doctor select and display the desired guideline from the multiple guidelines related to the abnormal area, it is possible to display only the guidelines that the doctor needs.

Figure 10 shows a third example of guideline display. As shown in Figure 10A, by performing a first operation (e.g., moving cursor 407 to abnormality 406, tapping abnormality 406, etc.) on abnormality 406 on analysis result screen 400, guideline display screen 430 as shown in Figure 10B can be displayed. Guideline display screen 430 displays guidance information 431. Guidance information 431 is information recommending the viewing order (reference order) of guidelines related to the abnormality. In the example of Figure 10B, guidance is displayed indicating that guidelines 1 to 3 should be referenced in three orders. When a physician operates the "Refer to A1" icon in accordance with the first guidance "First, refer to guideline A1," guideline 432 is displayed. Even if a physician is not immediately sure which guideline to refer to next after referring to guideline A1, they can easily display guideline A2, the next guideline to be referenced, by operating the "Refer to A2" icon in accordance with the second guidance "Next, refer to guideline A2." Similarly, by following the third guidance "Finally, please refer to guideline A3," and operating the "See A3" icon, the final guideline A3 to be referenced can be easily displayed. The guideline reference order may be determined by collecting past guideline reference histories and selecting the most frequently referenced guideline for each abnormality and providing this as guidance information, or by using a reference order determined in advance by an experienced specialist. Although not shown, by performing a similar first operation on other parts not identified as abnormal parts 406, information recommending the viewing order (reference order) of guidelines related to those parts may be displayed.

As described above, when the control unit 101 receives a first operation for an abnormal area, it may display guidance information that guides the doctor in the viewing order of the guidelines related to the abnormal area. This allows the doctor to refer to all guidelines related to the identified abnormal area without missing any, and to view the guidelines in the appropriate order.

Figure 11 shows a fourth example of guideline display. Guidelines related to the identified abnormal area are displayed on the guideline display screen 440. Some doctors may have searched for guidelines themselves in addition to the displayed guidelines. In such cases, by operating the "guideline search" icon 441, for example, a list of guidelines on the guideline page 210 on the web server 200 can be displayed and a guideline can be searched for.

The "Guideline Correction" icon 442 accepts an operation to correct the displayed guideline to the guideline searched for using the "Guideline Search" icon 441. In other words, the control unit 101 may accept an operation to correct the displayed guideline to a different guideline, and change the guideline related to the identified abnormality to the corrected guideline. This makes it possible to correct the displayed guideline to an appropriate guideline even if it is not appropriate.

The "Record" icon 444 can record the displayed guideline or corrected guideline in the history information 108 in association with an abnormality. In other words, when the control unit 101 receives a second operation (such as an operation on the "Record" icon 444) on the displayed guideline or corrected guideline, it may record specific information identifying the guideline (such as a URL that references the guideline) in association with the abnormality. This makes it possible to collect information associating the abnormality with the guideline.

By operating the "Enter comment" icon 443, the doctor can display the comment input field and enter a comment in the comment input field. The entered comment is recorded in the history information 108.

By operating the "Evaluation" icon 445, a doctor can input an evaluation value indicating their assessment of the displayed guidelines, such as "Very useful," "Somewhat useful," "Informative," "Not very useful," or "Not useful at all." The evaluation value may be, for example, on a five-point scale or a numerical value between 0 and 100%. The control unit 101 can record the input evaluation value in the history information 108 in association with the displayed guidelines. This allows the appropriateness of the displayed guidelines to be evaluated not only by less experienced doctors but also by more experienced specialists, making it possible to display appropriate guidelines.

Figure 12 is a diagram showing an example of history information 108. History information 108 can be recorded for each patient. History information 108 associates the date of imaging (which may include the examination date), captured medical image, vital signs, examination data, displayed guidelines, evaluation of the displayed guidelines, entered comments, and corrected guidelines. For example, the imaging date OO/OO/OO is associated with medical image G1 (or a URL for identifying G1, etc.), vital data V1, examination data T1, displayed guideline A1, evaluation 70%, comment C1, and corrected guideline B1. The same applies to other imaging dates.

In this way, the control unit 101 may display a field for entering comments and record the comments entered in the field in association with specific information identifying the abnormal area and guidelines related to the abnormal area. This allows the doctor to understand the situation at the time of past diagnoses at any time and confirm the history of the patient's illness and the effectiveness of treatment, etc.

Figure 13 is a diagram showing a second example of a guideline selection method. As shown in Figure 12, the control unit 101 can collect evaluations of the displayed guidelines. The control unit 101 may calculate an evaluation value for each of multiple guidelines related to the abnormal area based on the collected evaluations, select a guideline related to the abnormal area based on the evaluation value, and display the selected guideline.

As shown in FIG. 13, suppose guidelines A1, B1, and C1 exist as guidelines related to the identified abnormal area. Suppose the statistical value (e.g., mean, median, mode, etc.) of the evaluation values collected for guideline A1 is 70%, the statistical value of the evaluation values collected for guideline B1 is 85%, and the statistical value of the evaluation values collected for guideline C1 is 80%. In this case, guideline B1, which has the largest statistical value of the evaluation values, can be selected. This allows guidelines with higher evaluations to be preferentially selected and displayed, making it possible to provide more useful guidelines.

Figure 14 is a diagram showing a fifth example of guideline display. As shown in Figure 14A, multiple abnormal areas 406a, 406b, and 406c are displayed on the analysis result screen 400. Note that the number of abnormal areas is not limited to three. By performing a first operation on the abnormal areas 406a, 406b, and 406c (for example, an operation of moving the cursor 407 to the abnormal area 406a, 406b, or 406c, or an operation of tapping the abnormal area 406a, 406b, or 406c), a guideline display screen 450 such as that shown in Figure 14B can be displayed.

The guideline display screen 450 displays three guidelines A11, A12, and B11. In Figure 14B, a space has been inserted at the beginning of guideline A12, causing it to be shifted to the right of guideline A11. Furthermore, another space has been inserted at the beginning of guideline B11, causing it to be shifted to the right of guideline A12. By arranging the display positions of guidelines A11, A12, and B11 in this way, doctors can easily view the guidelines in the order A11, A12, and B11. This allows the guidelines to be weighted when displayed. Note that instead of changing the layout, the size of the guideline display area, the font size of the guidelines, etc. may also be changed.

Figure 14A illustrates an example in which abnormal areas 406a, 406b, and 406c are operated in this order, but the order of operations is not limited to the example in Figure 14A. For example, operations may be performed in the order that the doctor considers most important or in order of increasing interest. Although not shown, similar first operations may be performed on multiple other areas not identified as abnormal areas 406a, 406b, and 406c, thereby weighting and displaying guidelines related to those areas.

As described above, when there are multiple abnormal areas and first operations for the multiple abnormal areas are received, the control unit 101 may display guidelines related to the multiple abnormal areas for which the first operations were received. Furthermore, when there are multiple abnormal areas and first operations for the multiple abnormal areas are received, the control unit 101 may weight the guidelines related to the multiple abnormal areas based on the order in which the first operations were received, and display the guidelines according to the weighting. This allows the doctor to intuitively grasp the importance of the guidelines.

Figure 15 is a diagram showing a second example of the configuration of an information processing system according to this embodiment. The information processing system includes a client device 60 as an information processing device. Differences from the first example shown in Figure 1 include that the functions of the information processing device 100 are incorporated into the client device 60, that the client device 60 is not connected to a communication network 1 such as the Internet, and that a guideline DB 70 is connected to the client device 60.

In the first example illustrated in FIG. 1, the client device 60 is connected to the communication network 1 and can access the web server 200, so the client device 60 can display the guidelines from the guideline web page. In the second example, the client device 60 is not connected to the communication network 1, so the client device 60 accesses the guideline DB 70 and displays the guidelines. Like the information processing device 100, the client device 60 includes a control unit 101, an analysis unit 104, a display control unit 105, a memory unit 106, a computer program 107, history information 108, and a guideline providing unit 109.

Figure 16 is a diagram showing an example of the configuration of the guideline DB70. The guideline DB70 can be configured with columns such as area, abnormal area, guideline, and literature information. The guidelines may be classified into a recommendation order that indicates the priority for viewing or reference. In the example of Figure 16, they are classified into three categories: first recommendation, second recommendation, and third recommendation. For example, if the area is the brain (cerebral area) and the abnormal area is X1, guidelines A1, A2, and A3 are displayed appropriately according to the recommendation order. The doctor can display literature information d11 cited in the guideline by operating the system. The same applies to other areas and abnormal areas.

The client device 60 acquires medical data including medical images, displays abnormal areas identified through analysis processing of the acquired medical data, and, when a first operation is received for the displayed abnormal area, displays guidelines related to the abnormal area.

This allows doctors to view an image in which the abnormality is visualized and simply perform a predetermined first operation on the abnormality, which will display the guidelines related to that abnormality. This eliminates the need to flip through the pages of the guidelines to find the appropriate section or search for the guidelines on a computer, improving convenience for doctors.

Figure 17 is a diagram showing an example of the processing procedure of an information processing device. The information processing device includes an information processing device 100 of a first example and a client device 60 of a second example. For convenience, the following description will be given with the control unit 101 as the main processor of the processing. The control unit 101 acquires medical data including medical images (S11) and identifies abnormal areas through analysis processing (S12). Abnormal areas include, for example, those exemplified in Figures 3 and 4. The control unit 101 displays the identified abnormal areas (S13). Display of the abnormal areas includes, for example, those exemplified in Figure 5.

The control unit 101 determines whether or not a predetermined operation has been performed (S14). If no predetermined operation has been performed (NO in S14), the control unit 101 continues processing in step S14. If a predetermined operation has been performed (YES in S14), the control unit 101 displays guidelines in accordance with the predetermined operation (S15). Examples of guideline displays include those exemplified in Figures 6, 9, 10, and 14.

The control unit 101 determines whether or not a predetermined operation has been performed on the displayed guideline (S16), and if a predetermined operation has been performed (YES in S16), executes processing according to the operation (S17) and performs the processing of step S18 described below. Examples of processing according to the operation include the processing illustrated in FIG. 11.

If the specified operation has not been performed (NO in S16), the control unit 101 determines whether or not to terminate the processing (S18). If the processing is not to be terminated (NO in S18), the processing continues from step S16 onwards. If the processing is to be terminated (YES in S18), the processing terminates.

The computer program of this embodiment causes a computer to acquire medical data including medical images, display abnormal areas identified by analyzing the acquired medical data, and, when a first operation on the abnormal area is received, display guidelines related to the abnormal area.

The computer program of this embodiment causes the computer to execute a process in which, when a first operation on the abnormal portion is received, selection information for selecting multiple guidelines related to the abnormal portion is displayed, and the guideline selected by the selection information is displayed.

The computer program of this embodiment causes the computer to execute a process in which, when a first operation on the abnormal portion is received, guidance information is displayed that guides the user in the viewing order of guidelines related to the abnormal portion.

The computer program of this embodiment causes the computer to execute a process in which, when a second operation on a displayed guideline is received, specific information identifying the guideline is associated with the abnormality and recorded.

The computer program of this embodiment causes a computer to execute a process that displays a field for entering comments, associates the comments entered in the field with specific information identifying the abnormal part and the guideline associated with the abnormal part, and records them.

The computer program of this embodiment causes the computer to accept an operation to correct a displayed guideline to a different guideline, and to execute processing to change the guideline associated with the abnormal portion to the corrected guideline.

The computer program of this embodiment causes the computer to record the number of times a displayed guideline has been viewed, and to display this number of views when displaying a guideline related to the abnormality.

The computer program of this embodiment causes the computer to execute the following processes: collect evaluations of the displayed guidelines, calculate evaluation values for each of the multiple guidelines associated with the abnormal area based on the collected evaluations, select a guideline associated with the abnormal area based on the evaluation values, and display the selected guideline.

The computer program of this embodiment causes the computer to execute a process that extracts keywords related to the abnormality and displays the keywords included in the guidelines related to the abnormality in a specific display format.

The computer program of this embodiment causes the computer to execute a process in which, when a first operation is received for multiple abnormal areas, guidelines related to the multiple abnormal areas for which the first operation was received are displayed.

The computer program of this embodiment causes the computer to execute a process in which, when first operations for multiple abnormal areas are received, the computer weights the guidelines related to the multiple abnormal areas based on the order in which the first operations were received, and displays the guidelines in accordance with the weighting.

The computer program of this embodiment causes the computer to execute a process to display a guideline related to a part that has not been identified as an abnormal part when a first operation is received on the part.

The information processing device of this embodiment includes an acquisition unit that acquires medical data including medical images, a first display unit that displays abnormal areas identified by analyzing the acquired medical data, and a second display unit that displays guidelines related to the abnormal areas when a first operation on the abnormal areas is received.

The information processing method of this embodiment acquires medical data including medical images, displays abnormal areas identified through analysis processing of the acquired medical data, and, when a first operation on the abnormal area is received, displays guidelines related to the abnormal area.

REFERENCE SIGNS LIST 1 Communication network 10 MRI device 20 PET device 30 CT device 40 Inspection device 50 Image server 60 Client device 61 Web browser 70 Guideline DB
REFERENCE SIGNS LIST 100 Information processing device 101 Control unit 102 Communication unit 103 Memory 104 Analysis unit 105 Display control unit 106 Storage unit 107 Computer program 108 History information 109 Guideline providing unit 200 Web server 210 Guideline page

Claims (15)

On the computer,
Acquire medical data, including medical images;
Displaying abnormal areas identified through analysis of acquired medical data,
When a first operation on the abnormal portion is received, a guideline related to the abnormal portion is displayed ;
When a second operation on the displayed guideline is received, specific information for identifying the guideline is recorded in association with the abnormal portion .
A computer program that executes a process. On the computer,
When a first operation on the abnormal portion is received, selection information for selecting a plurality of guidelines related to the abnormal portion is displayed;
Displaying a guideline selected by the selection information;
The computer program product of claim 1 , which executes a process. On the computer,
when a first operation on the abnormal portion is received, displaying guidance information that guides the user in the viewing order of guidelines related to the abnormal portion;
3. The computer program according to claim 1, which executes a process. On the computer,
Display the comment field,
The comment entered in the entry field, the abnormal part, and specific information for identifying a guideline related to the abnormal part are recorded in association with each other.
The computer program according to any one of claims 1 to 3 , which causes a process to be executed. On the computer,
Accepts the operation to correct the displayed guideline to another guideline,
changing the guideline associated with the anomaly to a corrected guideline;
5. A computer program product according to claim 1 , which causes a process to be executed. On the computer,
Record the number of times the displayed guidelines are viewed,
When displaying the guideline related to the abnormal part, the number of times the guideline has been viewed is displayed.
6. A computer program product according to claim 1 , which causes a process to be executed. On the computer,
Collect evaluations of the displayed guidelines,
Calculating an evaluation value for each of a plurality of guidelines related to the abnormal portion based on the collected evaluations;
selecting a guideline associated with the abnormality based on the evaluation value;
View the selected guideline,
7. A computer program product according to claim 1, which causes a process to be executed. On the computer,
extracting keywords related to the abnormal portion;
displaying the keyword included in the guideline related to the abnormal portion in a specific display mode;
A computer program product according to any one of claims 1 to 7 , which causes a process to be executed. On the computer,
When a first operation for a plurality of abnormal portions is received, a guideline related to the plurality of abnormal portions for which the first operation is received is displayed.
A computer program product according to any one of claims 1 to 8 , which causes a process to be executed. On the computer,
When first operations for a plurality of abnormal portions are received, weighting the guidelines related to the plurality of abnormal portions based on the order in which the first operations are received;
Displaying the guidelines according to the weighting.
10. A computer program product according to claim 1, which causes a process to be executed. On the computer,
Acquire medical data, including medical images;
Displaying abnormal areas identified through analysis of acquired medical data,
When a first operation on the abnormal portion is received, a guideline related to the abnormal portion is displayed;
Display the comment field,
The comment entered in the entry field, the abnormal part, and specific information for identifying a guideline related to the abnormal part are recorded in association with each other.
A computer program that executes a process. an acquisition unit that acquires medical data including medical images;
a first display unit that displays an abnormal area identified by an analysis process on the acquired medical data;
a second display unit that displays a guideline related to the abnormal portion when a first operation on the abnormal portion is received ;
a recording unit that, when a second operation on the displayed guideline is received, records specific information that identifies the guideline and the abnormal portion in association with each other;
Equipped with
Information processing device. an acquisition unit that acquires medical data including medical images;
a first display unit that displays an abnormal area identified by an analysis process on the acquired medical data;
a second display unit that displays a guideline related to the abnormal portion when a first operation on the abnormal portion is received;
an entry field display section that displays an entry field for entering comments;
a recording unit that records the comment entered in the entry field, the abnormal part, and specific information that identifies a guideline related to the abnormal part in association with each other;
Equipped with
Information processing device. Acquire medical data, including medical images;
Displaying abnormal areas identified through analysis of acquired medical data,
When a first operation on the abnormal portion is received, a guideline related to the abnormal portion is displayed ;
When a second operation on the displayed guideline is received, specific information for identifying the guideline is recorded in association with the abnormal portion .
An information processing method that causes a computer to execute a process . Acquire medical data, including medical images;
Displaying abnormal areas identified through analysis of acquired medical data,
When a first operation on the abnormal portion is received, a guideline related to the abnormal portion is displayed;
Display the comment field,
The comment entered in the entry field, the abnormal part, and specific information for identifying a guideline related to the abnormal part are recorded in association with each other.
An information processing method that causes a computer to execute a process.