Medical image display apparatus, medical image display system, and program

Abstract

To intelligibly display a medical image to be preferentially viewed among a plurality of medical images including a lesion candidate area.SOLUTION: A controller of the medical image display apparatus calculates, for at least two medical images among a plurality of medical images including a lesion candidate region among a series of medical images including the plurality of medical images, lesion information of the lesion candidate region included in each medical image, and displays information indicating that the plurality of lesion candidate regions are included in the medical image for which the lesion information is calculated on a slider bar indicating a temporal or spatial position of a target medical image in the series of medical images in a case where the plurality of lesion candidate regions are included in the medical image for which the lesion information is calculated.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to a medical image display device, a medical image display system, and a program. [Background technology]

[0002] Conventionally, a technique has been known in which a series of medical images including a plurality of medical images is subjected to image analysis, and the position of a medical image including a lesion candidate region is displayed on a slider bar. For example, Patent Document 1 describes displaying on a slider bar a mark indicating the position of a cross-sectional image in which an abnormal shadow candidate has been detected among a plurality of cross-sectional images constituting a CT image. Patent Document 1 also discloses that when displaying the mark, the displayed mark and the undisplayed mark are displayed in a distinguishable manner. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-173910 Summary of the Invention [Problem to be solved by the invention]

[0004] By the way, CAD (Computer Aided Diagnosis) and AI (Artificial Intelligence) When detecting lesion candidate regions by analyzing medical images using methods such as these, the number of detected lesion candidate regions has increased due to improvements in detection performance. As a result, the technology described in Patent Document 1 has a problem in that the number of marks displayed on the slider bar indicating the positions of cross-sectional images containing lesion candidate regions has increased so much that it is unclear which cross-sectional image should be viewed first.

[0005] The present invention has been made in consideration of the above-mentioned problems, and aims to clearly display which medical image should be viewed first among multiple medical images containing lesion candidate regions. [Means for solving the problem]

[0006] In order to solve the above problems, the medical image display device of the present invention comprises: an acquisition unit that acquires a series of medical images including a plurality of medical images; an extraction unit that performs image analysis on the plurality of medical images to extract a plurality of medical images including a lesion candidate region; a calculation unit that calculates lesion information of the lesion candidate region included in each of at least two medical images among the plurality of medical images including the extracted lesion candidate region; a control unit that controls display of information indicating the presence of the lesion candidate region in a plurality of medical images including the lesion candidate region, based on the lesion information of each medical image for which the lesion information has been calculated; Equipped with When the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas, the control unit displays information indicating that the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas on a slider bar that indicates the temporal or spatial position of the target medical image in the series of medical images.

[0007] The medical image display system of the present invention comprises: an acquisition unit that acquires a series of medical images including a plurality of medical images; an extraction unit that performs image analysis on the plurality of medical images to extract a plurality of medical images including a lesion candidate region; a calculation unit that calculates lesion information of the lesion candidate region included in each of at least two medical images among the plurality of medical images including the extracted lesion candidate region; a control unit that controls display of information indicating the presence of the lesion candidate region in a plurality of medical images including the lesion candidate region, based on the lesion information of each medical image for which the lesion information has been calculated; Equipped with When the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas, the control unit displays information indicating that the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas on a slider bar that indicates the temporal or spatial position of the target medical image in the series of medical images.

[0008] The program of the present invention is Computer, an acquisition unit for acquiring a series of medical images including a plurality of medical images; an extraction unit that performs image analysis on the plurality of medical images to extract a plurality of medical images including a lesion candidate region; a calculation unit that calculates lesion information of the lesion candidate region included in each of at least two medical images among the plurality of medical images including the extracted lesion candidate region; a control unit that controls display of information indicating the presence of the lesion candidate region in a plurality of medical images including the lesion candidate region, based on the lesion information of each medical image for which the lesion information has been calculated; It functions as When the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas, the control unit displays information indicating that the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas on a slider bar that indicates the temporal or spatial position of the target medical image in the series of medical images. [Effects of the Invention]

[0009] According to the present invention, it is possible to display a plurality of medical images each containing a lesion candidate region in a manner that makes it easy to know which medical image should be viewed first. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a diagram illustrating the overall configuration of an image display system according to a first embodiment. [Figure 2] FIG. 2 is a block diagram showing the functional configuration of the image interpretation terminal of FIG. 1. [Figure 3]FIG. 3 is a sequence diagram showing the flow from photographing to image display in the first embodiment. [Figure 4] FIG. 10 is a diagram showing an example of a conventional image interpretation screen. [Figure 5] FIG. 10 is a diagram illustrating an example of a correspondence table. [Figure 6] FIG. 1 is a diagram showing an example of an interpretation screen to which the present invention is applied. [Figure 7] FIG. 1 is a diagram showing an example of an interpretation screen to which the present invention is applied. [Figure 8] FIG. 1 is a diagram showing an example of an interpretation screen to which the present invention is applied. [Figure 9] FIG. 10 is a diagram showing a modified example of the detection mark. [Figure 10] FIG. 10 is a diagram illustrating the overall configuration of an image display system according to a second embodiment. [Figure 11] FIG. 10 is a sequence diagram showing the flow from photographing to image display in the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings, but the present invention is not limited to the illustrated examples.

[0012] First Embodiment [Configuration of image display system] FIG. 1 is a diagram showing an example of the system configuration of an image display system 100 (medical image display system) according to the first embodiment. As shown in FIG. 1, the image display system 100 includes a modality 1, an analysis device 2, an image server 3, and an interpretation terminal 4. The devices constituting the image display system 100 are connected via a communication network N such as a local area network (LAN), a wide area network (WAN), or the Internet. The devices constituting the image display system 100 conform to the HL7 (Health Level Seven) and DICOM (Digital Image and Communications in Medicine) standards. Communication between the devices is performed in accordance with HL7 and DICOM. There is no particular limitation on the number of modalities 1, analysis devices 2, interpretation terminals 4, etc.

[0013] Modality 1 captures an image of a subject (a patient's examination area) and generates a medical image of the captured subject. In this embodiment, modality 1 captures an image of a subject and generates a series of medical images including a plurality of medical images. For example, modality 1 is CT (Computed Tomography) or MRI (Magnetic Resonance Imaging), and generates a plurality of consecutive medical images (tomographic images) at different slice positions. Alternatively, modality 1 is a radiological dynamic imaging device, a fluoroscopic device, or an ultrasound diagnostic device, and generates a plurality of temporally consecutive medical images (frame images). In this embodiment, a case where modality 1 is CT or MRI will be described as an example.

[0014] The modality 1 attaches image attribute information relating to the medical image to the generated medical image, and transmits the image to the analysis device 2 and the image server 3. Here, image attribute information includes patient information, examination information, image identification information, etc. Patient information includes patient ID, patient name, date of birth, age, sex, height, weight, etc. Examination information includes examination ID, examination date and time, type of modality, examination area, requesting department, examination purpose, etc. Image identification information includes instance number and UID (Unique ID). The instance number is a number that indicates the position of a certain medical image in a series of medical images. The UID is information for uniquely identifying a medical image.

[0015] The analysis device 2 performs image analysis using computer processing on the series of medical images sent from the modality 1 to extract medical images containing suspected lesion areas, calculates lesion information for the suspected lesion areas in the extracted medical images, and sends (outputs) it to the image server 3.

[0016] Analysis device 2 has the functions of an acquisition unit, extraction unit, and calculation unit of the present invention. The acquisition unit acquires a series of medical images including multiple medical images transmitted from modality 1 via a communication unit (not shown). The extraction unit performs image analysis on multiple medical images from the series of medical images transmitted from modality 1 to extract multiple medical images containing lesion candidate regions. The calculation unit calculates lesion information for the lesion candidate regions contained in each medical image for at least two medical images from the multiple medical images containing the lesion candidate regions extracted by the extraction unit.

[0017] The analysis device 2 realizes the functions of an extraction unit and a calculation unit by, for example, analysis using CAD or a machine learning model (AI analysis). Examples of machine learning model techniques that can be used include, but are not limited to, CNN (Convolutional Neural Network) and FCN (Fully Convolutional Networks). The functions of the extraction unit and the calculation unit are realized, for example, by cooperation between a processor such as a CPU and a program (machine learning model) stored in a storage unit (not shown).

[0018] Here, the lesion information calculated by the analysis device 2 includes at least one of the risk level of the lesion, the certainty level of the lesion, the size of the lesion, the type of the lesion, the mode of change of the lesion between the past and the current examination, and anatomical structure information of the lesion. The risk level of the lesion is a value or class that represents the risk of the lesion in the lesion candidate region, such as the likelihood of canceration. The certainty level of the lesion is a value indicating the probability that the lesion candidate region is a lesion. The size of the lesion is the size (e.g., diameter or radius) of the lesion candidate region. The type of lesion is the type of lesion corresponding to the lesion candidate region. For example, if the medical image is a medical image of the chest, examples of the lesion type include nodule, mass, pneumothorax, etc. The mode of change of the lesion between the past and the current examination is information indicating the mode of change of the lesion (lesion candidate region) between the past (previous) examination and the current examination (increase / decrease in size, new appearance, division, integration, disappearance, etc.). The anatomical structure information of the lesion is information indicating the anatomical structure (site) in which the lesion (lesion candidate region) is located.

[0019] If the lesion information is related to a breast nodule, the lesion information includes at least one of the following: size of the lesion, difference between the previous and current lesion, type of lesion (Solid / P-Solid / GGN), and location of the lesion. The lesion size may be the size of the lesion candidate region itself, or may be information indicating whether the size of the lesion is equal to or greater than a predetermined threshold. The difference between the previous and current lesions is information indicating the difference (increase or decrease in size) between the lesion (lesion candidate region) in the previous (previous) examination and the current examination. The lesion location is information indicating the location where the lesion candidate region is located (e.g., anatomical structure information).

[0020] When the lesion information is lesion information related to a fracture, the lesion information may be information on at least one of the fracture site and the fracture degree. The fracture site is a site with more detail than the above-mentioned anatomical structure. For example, if the second rib is fractured, the information on the above-mentioned anatomical structure is "rib," but the fracture site is "second rib." The fracture degree is information indicating the severity of the fracture.

[0021] When the lesion information is about the head, the lesion information may be at least one of information about the type of lesion (hyperattenuation / hypoattenuation, cerebral aneurysm, white matter) and the location of the lesion. The location of the lesion is information indicating the location where the lesion candidate region exists (e.g., anatomical structure information).

[0022] It is preferable that the lesion information also includes position information (coordinates) of the lesion candidate region in the medical image.

[0023] The analysis device 2 transmits the calculated lesion information to the image server 3 in association with the image attribute information of the medical image from which the lesion information was calculated.

[0024] The image server 3 is, for example, a PACS (Picture Archiving and Communication System) server, and is an image management device that stores and manages medical images output from the modality 1. The image server 3 is an image server unit in a cloud-based, on-premise, or workstation-based system.

[0025] The image server 3 is provided with an image DB (Data Base) 30. The image DB 30 , a database for storing medical images transmitted from the modality 1 and lesion information transmitted from the analysis device 2. The image DB 30 has an image management table that stores information about the medical images stored in the image DB 30. The image management table stores, for example, patient information, examination information, image identification information, and lesion information for each medical image in association with each other.

[0026] The image interpretation terminal 4 is, for example, a PACS client (PACS viewer). The image interpretation terminal 4 reads out medical images from the image server 3 and displays them for image interpretation. The image interpretation terminal 4 may be an application-type viewer that operates using an application, or a browser-type viewer that operates using a browser. In this embodiment, a case where the image interpretation terminal 4 is an application-type viewer will be described as an example.

[0027] FIG. 2 is a block diagram showing the functional configuration of the image interpretation terminal 4. As shown in FIG. As shown in FIG. 2, the image interpretation terminal 4 includes a control unit 41, a storage unit 42, a communication unit 43, an operation unit 44, a display unit 45, etc., and each unit is connected by a bus 46.

[0028] The control unit 41 is composed of a CPU (Central Processing Unit), RAM (Random Access Memory), etc. The control unit 41 comprehensively controls the operations of each unit of the interpretation terminal 4. For example, the CPU of the control unit 41 reads out various processing programs stored in the storage unit 42, loads them into the RAM, and executes processing on the interpretation terminal 4 side shown in Fig. 3 in accordance with the loaded programs. The control unit 41 functions as a control unit of the present invention.

[0029] The storage unit 42 is configured by a HDD (Hard Disk Drive), a semiconductor memory, etc. The storage unit 42 stores system programs, application programs for executing various processes, and data such as parameters required for executing the programs. For example, the storage unit 42 stores lesion information items used to control the display mode of the detection marks (M1 to M6) on the interpretation screen 451 (see FIGS. 6 to 8). The lesion information items used to control the display mode of the detection marks (M1 to M6) can be set by the user by operating the operation unit 44. The storage unit 42 also stores a correspondence table 421 (see FIG. 5). The correspondence table 421 will be described in detail later.

[0030] The storage unit 42 also has an area for temporarily storing medical images acquired from the image server 3, their image attribute information, and lesion information.

[0031] The communication unit 43 is configured by a network interface, etc. The communication unit 43 transmits and receives data to and from external devices connected via the communication network N.

[0032] The operation unit 44 is composed of a keyboard with various keys, a pointing device such as a mouse, or a touch panel superimposed on the display unit 45. The operation unit 44 outputs to the control unit 41 operation signals input by the user through key operations on the keyboard, mouse operations, or touch operations on the touch panel.

[0033] The display unit 45 is configured by a monitor such as an LCD (Liquid Crystal Display), etc. The display unit 45 displays various screens in accordance with instructions of a display signal input from the control unit 41.

[0034] [Operation of Image Display System 100] Next, the operation of the image display system 100 will be described. 3 is a sequence diagram showing the flow from capturing an image to displaying an image in the image display system 100. Hereinafter, the flow from capturing an image to displaying an image in the image display system 100 will be described with reference to FIG.

[0035] First, the modality 1 photographs a subject and acquires a series of medical images including a plurality of medical images (step S1). Next, the modality 1 attaches image attribute information to the series of acquired medical images and transmits them to the analysis device 2 and the image server 3 (step S2).

[0036] The analysis device 2 receives (acquires) the series of medical images transmitted from the modality 1 (step S3). Next, the analysis device 2 performs image analysis on a plurality of medical images among the series of medical images transmitted from the modality 1, and extracts a plurality of medical images including a lesion candidate region (step S4). In addition, if the same lesion candidate region is captured across multiple medical images, the analysis device 2 extracts, for example, the medical image in which the lesion candidate region is captured most significantly as the medical image containing the lesion candidate region.

[0037] Next, the analysis device 2 calculates lesion information of the lesion candidate region included in each of at least two medical images among the plurality of medical images including the lesion candidate region (step S5).

[0038] Next, the analysis device 2 transmits the calculated lesion information to the image server 3 in association with the image attribute information of the medical image from which the lesion information was calculated (step S6).

[0039] When the image server 3 receives the series of medical images transmitted from the modality 1 (step S7), it stores the series of medical images in the image DB 30 (step S8). That is, the image server 3 stores the received series of medical images in the image DB 30 and writes the image attribute information of each medical image in the image management table.

[0040] Furthermore, upon receiving the lesion information transmitted from the analysis device 2 (step S9), the image server 3 stores the lesion information in the image DB 30 (step S10). That is, the image server 3 writes the lesion information into the record in the image management table in which the image attribute information of the medical image corresponding to the received lesion information is written.

[0041] When the examination information of the medical image to be displayed is specified by the operation unit 44 on the image interpretation terminal 4, the control unit 41 sends an image acquisition request for the specified examination to the image server 3 via the communication unit 43 (step S11). The image server 3 reads out a series of medical images and lesion information of the specified examination from the image DB 30 and transmits them to the image interpretation terminal 4 (step S12).

[0042] When the reading terminal 4 receives (acquires) a series of medical images sent from the image server 3 via the communication unit 43 (step S13), the control unit 41 causes the display unit 45 to display the reading screen 451 for displaying the received medical images (step S14). The user operates the image interpretation screen 451 to perform image interpretation.

[0043] FIG. 4 is a diagram showing an example of a conventional image interpretation screen 450. As shown in FIG. As shown in FIG. 4, a conventional image interpretation screen 450 is provided with a medical image display area 450a and a slider bar 450b having a slider 450c. The medical image display area 450a is an area that displays the medical image corresponding to the position of the slider 450c among the series of medical images to be displayed. The slider bar 450b is a bar-shaped UI (User Interface), i.e., an operating means, for specifying a medical image to be displayed from a series of medical images. The longitudinal direction of the slider bar 450b indicates a direction perpendicular to the surface (cross section) of the subject in the series of medical images. One end (e.g., the upper end) of the slider bar 450b corresponds to the slice position of the first captured medical image, and the other end (e.g., the lower end) corresponds to the slice position of the last captured medical image. The position of the slider 450c indicates the slice position of the medical image currently displayed in the medical image display area 450a. When the slider 450c is moved on the slider bar 450b, the medical image displayed in the medical image display area 450a is changed to the medical image corresponding to the position of the slider 450c after the movement.

[0044] A detection mark M0 is displayed on slider bar 450b of interpretation screen 450. Detection mark M0 is information indicating the presence of a lesion candidate region in a medical image that includes the lesion candidate region. Detection mark M0 is displayed in association with the position on slider bar 450b of the medical image that includes the lesion candidate region.

[0045] 4, detection marks M0 are displayed in the same display format at the positions of all medical images containing lesion candidate regions. Therefore, when there are many medical images containing lesion candidate regions and many detection marks M0 are displayed, the user may not know which medical image to prioritize. In Patent Document 1, displayed and undisplayed images are displayed in a distinguishable manner, but the user cannot recognize which medical image should be prioritized for interpretation.

[0046] Therefore, the control unit 41 controls the display of information indicating the presence of a lesion candidate region in each medical image containing a lesion candidate region, based on the lesion information of each medical image for which the lesion information has been calculated. In one embodiment, the control unit 41 controls the display of a detection mark as information indicating the presence of a lesion candidate region in a medical image containing a lesion candidate region, based on the lesion information of each medical image for which the lesion information has been calculated, on the display of the interpretation screen 451. Note that the medical image display area 451a, slider bar 451b, and slider 451c on the interpretation screen 451 are similar to the medical image display area 450a, slider bar 450b, and slider 450c described above, respectively, and therefore the same description will be used herein.

[0047] For example, the control unit 41, based on the lesion information of each medical image for which lesion information has been calculated, differentiates the display mode of at least one of the detection marks serving as information indicating the presence of a lesion candidate region in a medical image containing the lesion candidate region from the display mode of the other detection marks. For example, the control unit 41 differentiates the display mode of the at least one detection mark from the display mode of the other detection marks by controlling at least one of the size, color, and design of the detection mark based on the lesion information of each medical image.

[0048] For example, in step S14, the control unit 41 controls the display of the detection mark based on the lesion information of the medical image, using the items of lesion information and correspondence table 421 used to control the display mode of the detection mark, which are stored in the memory unit 42. Fig. 5 is a diagram showing an example of the correspondence table 421. As shown in Fig. 5, the correspondence table 421 stores, for each item of lesion information, a value range of the item and a display mode of a detection mark to be displayed at a position on a medical image that includes a lesion candidate region that falls within that value range, in association with each other. The correspondence table 421 stores display modes that differ in at least one of the size, color, and design of the detection mark depending on the value range of each item. Note that the values ​​are not limited to numerical values ​​and may include character strings, etc. The control unit 41 acquires, for each medical image for which lesion information has been calculated, items of lesion information stored in the storage unit 42 and used to control the display mode. Next, the control unit 41 references the correspondence table 421 and displays a detection mark with a display mode corresponding to the range of values ​​of the acquired lesion information item at a position on the slider bar 451b corresponding to the medical image. This allows the control unit 41 to control at least one of the size, color, and design of the displayed detection mark to be different between medical images with different value ranges for a predetermined item of lesion information. In other words, the control unit 41 can make the display mode of at least one detection mark different from the display mode of other detection marks between medical images with different value ranges for a predetermined item of lesion information.

[0049] Fig. 6 is a diagram showing an example of the interpretation screen 451. Fig. 6 shows a display example of the interpretation screen 451 when the item of lesion information used to control the display mode of the detection mark is "size," and in the correspondence table 421, a first size diamond (◇) is associated with "6 mm or more," and a second size diamond smaller than the first size is associated with "less than 6 mm."

[0050] As shown in FIG. 6, detection marks M1 and M2 are displayed on slider bar 451b on interpretation screen 451. Detection marks M1 and M2 are information indicating the presence of a lesion candidate region in a medical image that includes the lesion candidate region. Detection mark M1 is displayed in association with a position on slider bar 451b of a medical image that includes a lesion candidate region that is 6 mm or larger in size. Detection mark M2 is displayed in association with a position on slider bar 451b of a medical image that includes a lesion candidate region that is less than 6 mm in size. 6, a detection mark M1 is displayed at the position of a medical image that includes a lesion candidate region of 6 mm or more, and a detection mark M2 of a different size from the detection mark M1 is displayed at the position of a medical image that includes a lesion candidate region of less than 6 mm. Therefore, the user can recognize which medical images include lesion candidate regions of 6 mm or more, and can easily recognize which medical images should be given priority for interpretation.

[0051] 7 is a diagram showing another example of the image interpretation screen 451. In FIG. 7, the item of the lesion information used to control the display mode of the detection mark is “nodule type”, and “Solid 10 shows an example of the image interpretation screen 451 in which a diamond (◇) is associated with "Partial Solid," a triangle (△) is associated with "Partial Solid," and a circle (○) is associated with "GGN."

[0052] As shown in FIG. 7, detection marks M3 to M5 are displayed on slider bar 451b on interpretation screen 451. Detection marks M3 to M5 are information indicating the presence of a lesion candidate region in a medical image that includes a lesion candidate region. Detection mark M3 is displayed in association with the position on slider bar 451b of the medical image that includes a lesion candidate region with a nodule type of "Solid." Detection mark M4 is displayed in association with the position on slider bar 451b of the medical image that includes a lesion candidate region with a nodule type of "Partial Solid." Detection mark M5 is displayed in association with the position on slider bar 451b of the medical image that includes a lesion candidate region with a nodule type of "GGN." 7, the detection mark M3 displayed at the position of the medical image containing a lesion candidate region with a nodule type of "Solid," the detection mark M4 displayed at the position of the medical image containing a lesion candidate region with a nodule type of "Partial Solid," and the detection mark M5 displayed at the position of the medical image containing a lesion candidate region with a nodule type of "GGN" are displayed with different designs. Therefore, the user can recognize which medical image contains which type of nodule, and can easily recognize which medical image should be given priority for interpretation.

[0053] In addition, the control unit 41 may control the display of information indicating the presence of a lesion candidate area in multiple medical images that contain a lesion candidate area by hiding at least one piece of information indicating the presence of a lesion candidate area based on the lesion information of each medical image for which lesion information has been calculated. For example, in the correspondence table 421, for each item of lesion information, a detection mark of a predetermined shape, size, and color is associated with a range of values ​​that should be given priority for interpretation, and "non-display" is associated with other value ranges, and these are stored. In step S14, the control unit 41 acquires, for each medical image for which lesion information has been calculated, an item of lesion information that is used to control the display mode of the detection mark, which is stored in the storage unit 42. Next, the control unit 41 refers to the correspondence table 421, and if the display mode corresponding to the value range of the acquired item of lesion information is a predetermined detection mark, the control unit 41 displays the detection mark at a position on the slider bar 451b corresponding to the medical image. If the display mode corresponding to the value range of the acquired item of lesion information is non-display, the detection mark is not displayed at a position on the slider bar 451b corresponding to the medical image. In this way, among medical images containing a lesion candidate region, a detection mark can be displayed on the slider bar 451b at the position of the medical image whose lesion information satisfies a predetermined condition, and the detection mark can be hidden at the position of the medical image that does not satisfy the predetermined condition. This allows the user to easily recognize which medical image should be given priority for interpretation.

[0054] In addition, in step S14, the control unit 41 may control the display of a detection mark, which is information indicating the presence of a lesion candidate area in a medical image that includes a lesion candidate area, based on a comparison of the lesion information of each medical image for which lesion information has been calculated. For example, if multiple medical images for which lesion information has been calculated include lesion information indicating that the lesion size is 2 mm or more in diameter, the control unit 41 displays the detection mark M6 at a position corresponding to the medical image having the top four lesion information sizes. The control unit 41 also hides the detection marks corresponding to medical images other than the above.

[0055] Fig. 8 is a diagram showing another example of the interpretation screen 451. Fig. 8 shows an example in which detection mark M6 is displayed at positions corresponding to medical images having lesion information of the top four largest lesion candidate regions among the lesion information having a diameter of 2 mm or more, and detection marks are not displayed at positions corresponding to other medical images. 8, the detection mark M6 is displayed only at positions corresponding to medical images that have the top four largest lesion candidate regions with diameters of 2 mm or more. This allows the user to easily recognize which medical image should be given priority in interpretation.

[0056] Note that when controlling the display of a detection mark, which is information indicating the presence of a lesion candidate region in a medical image containing a lesion candidate region, based on a comparison of the lesion information of each medical image in which the lesion information has been calculated, the control unit 41 does not need to compare all of the lesion candidate regions in the multiple medical images. Furthermore, it is not necessary to control the display of all of the information indicating the presence of a lesion candidate region. For example, the control unit 41 may control the display of information indicating the presence of at least a lesion candidate region in a first medical image based on first lesion information of a first lesion candidate region included in at least a first medical image and second lesion information of a second lesion candidate region included in a second medical image.

[0057] [Variation 1] In the first embodiment described above, when the same lesion candidate region is detected across multiple medical images, the analysis device 2 extracts the medical image in which the lesion candidate region is largest as the medical image containing the lesion candidate region. Alternatively, when the same lesion candidate region is detected across multiple medical images, the analysis device 2 may extract all medical images containing the lesion candidate region as medical images containing the lesion candidate region and calculate lesion information for the extracted medical images. The control unit 41 of the image interpretation terminal 4 may then control the display of information indicating the presence of lesion candidate regions in multiple medical images containing the lesion candidate region, based on the lesion information for each medical image for which lesion information has been calculated. For example, when two lesion candidate regions are detected across multiple medical images, the control unit 41 may display information M7 indicating the presence of one lesion candidate region on the left side of the slider bar 451b and information M8 indicating the presence of the other lesion candidate region on the right side, as shown in FIG. 9 . At this time, control unit 41 displays information M7 and M8, with the length in the direction (left or right) perpendicular to slider bar 451b representing the size (radius or diameter) of the lesion candidate region detected from each medical image, and the vertical direction representing the position of the medical image, allowing the user to recognize the range and size of the two lesion candidate regions included in the series of medical images.

[0058] [Variation 2] In the image display system 100 of the first embodiment, the analysis device 2 has the functions of an acquisition unit, an extraction unit, and a calculation unit, and the interpretation terminal 4 has the functions of a control unit and a display unit. However, the device having the functions of an acquisition unit, an extraction unit, a calculation unit, a control unit, and a display unit is not limited to the above example.

[0059] For example, if the image display system 100 does not include the analysis device 2, the interpretation terminal 4 may be configured to have all the functions of the acquisition unit, extraction unit, calculation unit, control unit, and display unit of the medical image display device of the present invention. For example, the storage unit 42 of the interpretation terminal 4 stores a program for causing the control unit 41 to execute the functions of the acquisition unit, extraction unit, calculation unit, and control unit of the present invention. The control unit 41 executes the functions of the acquisition unit, extraction unit, calculation unit, and control unit in cooperation with the program stored in the storage unit 42, and also causes the display unit 45 to function as a display unit.

[0060] Furthermore, if the image display system 100 does not include the analysis device 2, the image server 3 may be configured to include the functions of an acquisition unit, extraction unit, calculation unit, and control unit as the medical image display device of the present invention. For example, the image server 3 executes the functions of the acquisition unit, extraction unit, calculation unit, and control unit through cooperation between a processor such as a CPU and a program stored in a storage unit. Note that, when controlling the display of information indicating the presence of a lesion candidate region in multiple medical images, the image server 3 may, as a control unit, control the display of the information on its own display unit. Alternatively, when controlling the display of information indicating the presence of a lesion candidate region in multiple medical images, the image server 3 may, as a control unit, control the display of the image interpretation terminal 4.

[0061] Furthermore, the analysis device 2 may be configured to have all the functions of an acquisition unit, extraction unit, calculation unit, control unit, and display unit as the medical image display device of the present invention. For example, the analysis device 2 may be equipped with a display unit, and when controlling the display of information indicating the presence of a lesion candidate region in a plurality of medical images as a control unit, the analysis device 2 may control the display of the information on its own display unit. Alternatively, when controlling the display of information indicating the presence of a lesion candidate region in a plurality of medical images as a control unit, the analysis device 2 may control the display of the image interpretation terminal 4 to display the information.

[0062] <Second embodiment> A second embodiment of the present invention will now be described.

[0063] The image display system 100 shown in Fig. 1 is installed in a relatively large medical facility. On the other hand, small medical facilities such as private practice clinics often use medical image display devices that integrate the functions of an analysis device, an image server, and an interpretation terminal. Below, we will explain an example of applying the present invention to a medical image display device for such a small medical facility.

[0064] Fig. 10 is a diagram showing an example of an image display system 200 in the second embodiment. As shown in Fig. 10, the image display system 200 includes a modality 1 and a medical image display device 6. The modality 1 and the medical image display device 6 are connected via a communication network N1 such as a LAN. The modality 1 is the same as that described in the first embodiment, and the description thereof will be used here.

[0065] As shown in FIG. 10, the medical image display device 6 includes a control unit 61, a storage unit 62, a communication unit 63, an operation unit 64, and a display unit 65, and each unit is connected via a bus 66.

[0066] The control unit 61 is composed of a CPU, RAM, etc. The control unit 61 comprehensively controls the operation of each unit of the medical image display device 6. Specifically, the CPU of the control unit 61 reads out various processing programs stored in the storage unit 62, loads them into the RAM, and executes various processes according to the loaded programs.

[0067] The storage unit 62 is composed of a hard disk drive (HDD), semiconductor memory, etc. The storage unit 62 stores system programs, application programs for executing various processes, and data such as parameters required for program execution. The programs stored in the storage unit 62 include programs that cause the computer (control unit 61) to function as the acquisition unit, extraction unit, calculation unit, and control unit of the present invention. The acquisition unit acquires a series of medical images, including multiple medical images, transmitted from modality 1 via a communication unit (not shown). The extraction unit performs image analysis on multiple medical images from the series of medical images transmitted from modality 1 to extract multiple medical images containing lesion candidate regions. The calculation unit calculates lesion information for the lesion candidate regions contained in at least two medical images among the multiple medical images containing the lesion candidate regions extracted by the extraction unit. The control unit controls the display of information indicating the presence of lesion candidate regions in the multiple medical images containing the lesion candidate regions, based on the lesion information for each medical image for which lesion information has been calculated. The lesion information is the same as that described in the first embodiment, and therefore the same description is hereby incorporated by reference.

[0068] The control unit 61 realizes functions as an extraction unit and a calculation unit by, for example, analysis using CAD or a machine learning model (AI analysis) in cooperation with a program stored in the storage unit 62. As a machine learning model method, for example, CNN or FCN can be used, but is not particularly limited.

[0069] The storage unit 62 includes a correspondence table 621 and an image DB 622. The correspondence table 621 is similar to the correspondence table 421 described in the first embodiment, and the description thereof is therefore incorporated herein. The image DB 622 is a database for storing medical images transmitted from the modality 1 and lesion information calculated from the medical images. The image DB 622 has an image management table that stores information about the medical images stored in the image DB 622. The image management table stores, for example, patient information, examination information, image identification information, and lesion information for each medical image in association with each other.

[0070] The communication unit 63 is configured by a network interface, etc. The communication unit 63 transmits and receives data to and from external devices connected via the communication network N1.

[0071] The operation unit 64 is composed of a keyboard with various keys, a pointing device such as a mouse, or a touch panel superimposed on the display unit 65. The operation unit 64 outputs operation signals input by the user through key operations on the keyboard, mouse operations, or touch operations on the touch panel to the control unit 61.

[0072] The display unit 65 is configured by a monitor such as an LCD, etc. The display unit 65 displays various screens in accordance with instructions of a display signal input from the control unit 61.

[0073] Next, the operation of the image display system 200 of the second embodiment will be described. 11 is a sequence diagram showing the flow from capturing an image to displaying an image in the image display system 200. Hereinafter, the flow from capturing an image to displaying an image in the image display system 200 will be described with reference to FIG.

[0074] First, modality 1 photographs a subject and acquires a series of medical images including a plurality of medical images (step T1). Next, the modality 1 attaches image attribute information to the series of acquired medical images and transmits them to the medical image display device 6 (step T2).

[0075] The control unit 61 of the medical image display device 6 receives (acquires) the series of medical images transmitted from the modality 1 via the communication unit 63 (step T3), and stores the acquired series of medical images in the image DB 622 (step T4). That is, the control unit 61 stores the received series of medical images in the image DB 622, and writes the image attribute information of each medical image in the image management table.

[0076] Next, the control unit 61 performs image analysis on a plurality of medical images among the series of medical images transmitted from the modality 1, and extracts a plurality of medical images including a lesion candidate region (step T5). The process of step T5 is similar to the process of step S4 in FIG. 3, and therefore the same explanation will be used.

[0077] Next, the control unit 61 calculates lesion information of the lesion candidate region included in each of at least two medical images among the plurality of medical images including the extracted lesion candidate region (step T6).

[0078] Next, the control unit 61 stores the calculated lesion information in the image DB 622 in association with the medical image from which the lesion information was calculated (step T7). The control unit 61 writes the lesion information into the record in the image management table of the image DB 622 in which the image attribute information of the medical image corresponding to each piece of lesion information is written.

[0079] Then, the control unit 61 causes the display unit 65 to display the interpretation screen 651 for displaying the medical image received from the modality 1 (step T8).

[0080] 6 to 8, the image interpretation screen 651 displayed by the control unit 61 in step T8 displays a medical image display area 651a, a slider bar 651b, and a slider 651c. The medical image display area 651a, the slider bar 651b, and the slider 651c are similar to the medical image display area 451a, the slider bar 451b, and the slider 451c, respectively, and therefore the same explanations will be used.

[0081] Detection marks (M1 and M2 in FIG. 6, M3 to M5 in FIG. 7, M6 in FIG. 8, etc.) are displayed on slider bar 651b of image interpretation screen 651. The detection marks are information indicating the presence of a lesion candidate region in a medical image that includes the lesion candidate region. The detection marks are displayed in association with the position on slider bar 651b of the medical image that includes the lesion candidate region.

[0082] Based on the lesion information of each medical image for which lesion information has been calculated, the control unit 61 differentiates the display mode of at least one of the detection marks, which are used as information indicating the presence of a lesion candidate region in a medical image containing the lesion candidate region, from the display mode of the other detection marks. The method of controlling the display mode of the detection marks by the control unit 61 is similar to the method of controlling the display mode of the detection marks by the control unit 41 described in the first embodiment and its modified examples, and therefore the description thereof is hereby incorporated by reference.

[0083] The user operates slider 651c of slider bar 651b on interpretation screen 651 to display the desired medical image in medical image display area 651a and perform interpretation. On slider bar 651b, a detection mark, which is information indicating the presence of a lesion candidate region in the medical image containing the lesion candidate region, is displayed in a display mode corresponding to the lesion information of the medical image. Therefore, the user can easily recognize which medical image should be given priority in interpretation.

[0084] As described above, the image display system 100 and the medical image display device 6 comprise an acquisition unit that acquires a series of medical images including a plurality of medical images; an extraction unit that performs image analysis on the plurality of medical images to extract a plurality of medical images containing candidate lesion regions; a calculation unit that calculates lesion information for the candidate lesion regions contained in at least two of the plurality of medical images containing the extracted candidate lesion regions; and a control unit that controls the display of information indicating the presence of candidate lesion regions in the plurality of medical images containing the candidate lesion regions, based on the lesion information for each medical image for which lesion information has been calculated. Therefore, based on the lesion information, it is possible to display in a way that makes it easy to understand which medical image should be viewed first among a plurality of medical images that contain lesion candidate regions.

[0085] The present invention is not limited to the above-described embodiment, and various modifications are possible without departing from the spirit of the present invention.

[0086] For example, in the above embodiment, a case has been described in which only one item of lesion information is used to control the display mode of information (such as a detection mark) indicating the presence of a lesion candidate region in a medical image containing a lesion candidate region. However, the display mode of the information may be controlled based on multiple items of lesion information. For example, the control unit 41 (61) scores each of the multiple items in the lesion information according to a range of values, multiplies the score of each item by a weighting coefficient predetermined for each of the multiple items, and sums the scores. Then, the control unit 41 (61) displays the information in a display mode corresponding to the summed value based on a table storing the correspondence between the range of the summed value and the display mode of the information. In this way, information (such as a detection mark) indicating the presence of a lesion candidate region in a medical image containing a lesion candidate region can be displayed in a display mode that reflects the multiple items of lesion information.

[0087] In the above embodiment, the series of medical images of the present invention is described as a series of consecutive medical images (tomographic images) at different slice positions generated by CT or MRI, but this is not limiting. For example, the series of medical images may be a series of medical images that are consecutive in time, such as radiological dynamic images, fluoroscopic images, or ultrasound images. In this case, the longitudinal direction of the slider bar 451b (651b) indicates the time axis. The position of the slider 451c (651c) indicates the time position of the medical image currently displayed in the medical image display area 451a (651a). In the above embodiment, the longitudinal direction of the slider bar 451b (651b) is the up-down direction, but it may be the left-right direction. Also, in the above embodiment, the slider bar 450b (651b) is an operation means for specifying a medical image to be displayed from a series of medical images, but it may be an operation means for continuously displaying a series of medical images.

[0088] In the above embodiment, the display mode of the detection mark is switched depending on the item of the lesion information, but this is not limiting. For example, a switching button may be provided on the image interpretation screen 451 (651), and the control unit 41 may switch the display mode of the detection mark in response to the operation of the switching button.

[0089] In the above embodiment, the lesion candidate region is detected by image analysis, but instead, a region designated by a radiologist (user) on a medical image may be detected as the lesion candidate region. In this case, the lesion information of the lesion candidate region may be calculated by computer processing or may be input by the radiologist.

[0090] In the above description, examples have been disclosed in which a hard disk or a semiconductor nonvolatile memory is used as a computer-readable medium for the program according to the present invention, but the present invention is not limited to these examples. Portable recording media such as CD-ROMs can also be used as other computer-readable media. Furthermore, carrier waves can also be used as a medium for providing data for the program according to the present invention via a communication line.

[0091] In addition, the detailed configuration and detailed operation of each device constituting the image display system can be modified as appropriate without departing from the spirit of the invention. [Explanation of symbols]

[0092] 1. Modality 2 Analysis device 3. Image Server 30 Image DB 4. Image reading terminal 41 Control Unit 42 Storage section 421 compatible table 43 Communications Department 44 Control section 45 Display section 46 Bus 6 Medical image display devices 61 Control Unit 62 Storage section 621 compatible table 622 Image DB 63 Communications Department 64 Operation section 65 Display section Bus 66

Claims

1. an acquisition unit that acquires a series of medical images including a plurality of medical images; an extraction unit that performs image analysis on the plurality of medical images to extract a plurality of medical images including a lesion candidate region; a calculation unit that calculates lesion information of the lesion candidate region included in each of at least two medical images among the plurality of medical images including the extracted lesion candidate region; a control unit that controls display of information indicating the presence of the lesion candidate region in a plurality of medical images including the lesion candidate region, based on the lesion information of each medical image for which the lesion information has been calculated; Equipped with When the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate regions, the control unit displays information indicating that the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate regions on a slider bar that indicates the temporal or spatial position of the target medical image in the series of medical images.

2. 2. The medical image display device of claim 1, wherein the control unit displays, for a slider bar indicating the temporal or spatial position of a target medical image in the series of medical images, information indicating one of the plurality of lesion candidate regions on one side of the slider bar at a position of the slider bar corresponding to a medical image including the plurality of lesion candidate regions, and displays information indicating another of the plurality of lesion candidate regions on the other side of the slider bar, as information indicating that the target medical image includes the plurality of lesion candidate regions.

3. The medical image display device according to claim 1 , wherein the control unit changes a display mode of the information indicating that the plurality of lesion candidate regions are included based on the corresponding lesion information.

4. 2. The medical image display device according to claim 1, wherein, when the extraction unit extracts at least one of the plurality of lesion candidate regions in a plurality of medical images, the control unit displays, on the slider bar, information indicating that the lesion candidate region has been extracted in the plurality of medical images.

5. The medical image display device according to claim 1 , wherein the control unit determines a length of the information in a direction perpendicular to the axis of the slider bar in accordance with a size of the lesion candidate region.

6. an acquisition unit that acquires a series of medical images including a plurality of medical images; an extraction unit that performs image analysis on the plurality of medical images to extract a plurality of medical images including a lesion candidate region; a calculation unit that calculates lesion information of the lesion candidate region included in each of at least two medical images among the plurality of medical images including the extracted lesion candidate region; a control unit that controls display of information indicating the presence of the lesion candidate region in a plurality of medical images including the lesion candidate region, based on the lesion information of each medical image for which the lesion information has been calculated; Equipped with A medical image display system in which, when the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas, the control unit displays information indicating that the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas on a slider bar that indicates the temporal or spatial position of the target medical image in the series of medical images.

7. Computer, an acquisition unit for acquiring a series of medical images including a plurality of medical images; an extraction unit that performs image analysis on the plurality of medical images to extract a plurality of medical images including a lesion candidate region; a calculation unit that calculates lesion information of the lesion candidate region included in each of at least two medical images among the plurality of medical images including the extracted lesion candidate region; a control unit that controls display of information indicating the presence of the lesion candidate region in a plurality of medical images including the lesion candidate region, based on the lesion information of each medical image for which the lesion information has been calculated; It functions as The control unit is a program that, when the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas, displays information indicating that the medical image for which the calculation unit has calculated lesion information contains multiple lesion candidate areas on a slider bar that indicates the temporal or spatial position of the target medical image in the series of medical images.

Images