JP6516983B2 - Medical image processing apparatus and medical image processing program - Google Patents

Description

  Embodiments of the present invention relate to a medical image processing apparatus and a medical image processing program.

  Recently, in many hospitals, multi-disciplinary team (MDT) has been introduced to realize patient-centered medical care. In MDT, MDT Meetings (MDTM) will be held to share information within the team to determine better treatment policies. In MDTM, information on a patient (for example, an examination result image) is displayed on a screen of a conference room or the like. Participants of MDTM discuss the patient's treatment plan etc. based on the displayed information.

JP, 2014-106768, A

  The information presented to the participants of the MDTM at the time of execution of the MDTM (presentation information) is preferably prepared prior to the MDTM. For example, the radiologist preferably preselects a medical image to explain the condition of the patient.

  In order to select appropriate presentation information, it is necessary for the person presenting the information to correctly grasp the information required by the MDTM. However, in order to correctly grasp the information required by MDTM, it is necessary to grasp the patient's condition and history so far, and to obtain the information possessed by other departments. In addition, it is also necessary to search for and select medical images to be presented by MDTM.

  For this reason, the information presenter needs much time to prepare presentation information for the participants of the MDTM. In particular, when the treatment period of a patient is long and the number of examinations is large, such as treatment of cancer, the time required for preparation becomes long. In some cases, the information presenter may want MDTM to be prepared in advance, which in turn will have a significant negative impact on the results of MDTM.

  In order to solve the problems described above, a medical image processing apparatus according to an embodiment of the present invention, based on examination information on a subject, uses a plurality of statuses forming a guideline indicating a treatment procedure for the subject. A current status determination unit that determines the current status to which the treatment progress status belongs at the time of examination corresponding to examination information, and associating the current status with the examination image included in the examination information And an association unit that generates association information in which each is associated with each status.

FIG. 1 is a block diagram showing an example of a medical image processing apparatus according to a first embodiment of the present invention. Explanatory drawing which shows an example of the guideline acquired by a guideline acquisition part. The figure for demonstrating the transition conditions preset to each status of the guideline shown in FIG. Explanatory drawing which shows an example of test | inspection information. The figure for demonstrating a mode that the present status is determined by the present status determination part 22 which acquired test | inspection information of test | inspection ID 12345 shown in FIG. The figure for demonstrating a mode that the present status is determined by the present status determination part which acquired test | inspection information of test | inspection ID 56789 implemented after test | inspection of test | inspection ID 12345 shown in FIG. Explanatory drawing which shows an example of the status * test | inspection image correlation information which linked | related each of several test | inspection image for every status. Explanatory drawing which shows an example of the view produced | generated by the view production part which concerns on 1st Embodiment. FIG. 7 is a flowchart showing an example of a procedure when generating status / inspection image association information to support preparation of presentation information for MDTM participants by the CPU of the control unit shown in FIG. 1; FIG. A flowchart showing an example of a procedure for generating a view for each association status based on status / inspection image association information in order to support preparation of presentation information for MDTM participants by the CPU of the control unit shown in FIG. . FIG. 7 is a block diagram showing an example of a medical image processing apparatus according to a second embodiment of the present invention. Explanatory drawing which shows an example of a mode when a view is produced | generated using the test | inspection image which adapts a filter condition, when predetermined | prescribed status is "follow-up." Explanatory drawing which shows an example of a mode when a view is produced | generated using the test | inspection image which adapts a filter condition, when predetermined | prescribed status is "relapse / stage VI close examination (relapse checkup)." In order to support the preparation of presentation information for MDTM participants by the CPU of the control unit shown in FIG. 11, a view is generated using an inspection image that matches the filter condition based on status / inspection image association information. The flowchart which shows an example of a procedure. FIG. 8 is a block diagram showing an example of a medical image processing apparatus according to a third embodiment of the present invention. (A) is an explanatory view showing an example of the filter condition in the case where the current status is a recurrence check and the setting status is a recurrence check, (b) is a view V-1, V-2, V-3, V Explanatory drawing which shows an example of the time when each of -4 was actually browsed in MDTM, (c) is an explanatory drawing which shows an example of a situation which calculates the weight of each view according to the browsing time of each view in MDTM, (d 8 is an explanatory drawing showing an example of how the filter condition is updated according to the weight of each view. FIG. 16 is a flowchart showing an example of a procedure when updating the filter condition according to the attention level to each view in the MDTM by the CPU of the control unit shown in FIG. 15; FIG.

  Embodiments of a medical image processing apparatus and a medical image processing program according to the present invention will be described with reference to the attached drawings.

  A medical image processing apparatus according to an embodiment of the present invention is used to prepare presentation information for MDTM participants, and can be an information processing terminal configured of, for example, a personal computer or a workstation.

  Medical image processing apparatuses include viewers of various systems such as an image storage communication system (PACS), a hospital information system (HIS), and a radiology information system (RIS). It may be used as Further, the medical image processing apparatus may be configured to be able to refer to a medical image held in the PACS by remotely using viewer software held by the PACS via the network. Further, the medical image processing apparatus may be realized as one function of an operation console of various modalities.

First Embodiment
FIG. 1 is a block diagram showing an example of a medical image processing apparatus 10 according to the first embodiment of the present invention.

  The medical image processing apparatus 10 includes a display unit 11, an input unit 12, a storage unit 13, a network connection unit 14, and a control unit 15.

  The display unit 11 is configured of a general display output device such as a liquid crystal display or an OLED (Organic Light Emitting Diode) display. The display unit 11 displays various information such as a medical image acquired via the network according to the control of the control unit 15, a view generated by the control unit 15, and the like. The input unit 12 is formed of a general input device such as a keyboard and a ten key, and outputs an operation input signal corresponding to the user's operation to the control unit 15.

  The display unit 11 and the input unit 12 may constitute an operation panel integrally. In this case, the operation panel has a hard key as a part of the input unit 12 such as a button for giving a unique instruction signal to the CPU when pressed by the user, and a display input device. In this case, the display input device includes the display unit 11 and a touch panel as a part of the input unit 12 provided in the vicinity of the display unit 11. The display unit 11 is controlled by the control unit 15 to display information for operating the medical image processing apparatus 10 and a plurality of soft keys for operating the medical image processing apparatus 10. The touch panel gives the control unit 15 information on the position designated by the user on the touch panel.

  The storage unit 13 has a configuration including a recording medium readable by an arithmetic device such as a CPU, such as a magnetic or optical recording medium or a semiconductor memory. The storage unit 13 includes information on the treatment guidelines, the status (hereinafter referred to as the current status) to which the current treatment progress status of the patient (subject) belongs, and information associated with each of the plurality of examination images , Status and inspection image association information). Some or all of the data stored in the storage unit 13 may be downloaded via the network.

  The network connection unit 14 implements various information communication protocols according to the form of the network. The network connection unit 14 connects the medical image processing apparatus 10 with a system such as an external PACS, HIS, or RIS (not shown) according to the various protocols. For this connection, an electrical connection via an electronic network can be applied. Here, the term "electronic network" means an information communication network in general using telecommunication technology, and in addition to a wireless / wired hospital backbone LAN (Local Area Network) and the Internet network, a telephone communication network, an optical fiber communication network, and a cable. It includes communication networks and satellite communication networks.

  The external system PACS, HIS, RIS, etc. holds various medical information such as guidelines, medical image data, examination information, treatment order information, medical chart information, critical path information and the like in accordance with predetermined rules. The medical image processing apparatus 10 acquires these medical information via the network connection unit 14.

  The control unit 15 includes a storage medium such as a CPU, a RAM, and a ROM, and the like, and controls the medical image processing apparatus 10 in accordance with a program stored in the storage medium.

  The CPU of the control unit 15 loads the medical image processing program stored in the storage medium such as the ROM and the data necessary for the execution of this program into the RAM, and according to this program, the presentation information to the participants of the MDTM Execute processing to support preparation.

  The RAM of the control unit 15 provides a work area for temporarily storing programs executed by the CPU and data. A storage medium such as the ROM of the control unit 15 stores an activation program of the medical image processing apparatus 10, a medical image processing program, and various data necessary for executing these programs.

  Note that a storage medium such as a ROM has a configuration including a recording medium readable by a CPU such as a magnetic or optical recording medium or a semiconductor memory, and a part of the program and data in the storage medium or Like the data stored in the storage unit 13, all may be configured to be downloaded via the network.

  As shown in FIG. 1, the CPU of the control unit 15 functions as at least a guideline acquisition unit 21, a current status determination unit 22, an association unit 23, and a view generation unit 24 according to a medical image processing program. The respective units 21 to 24 use a required work area of the RAM as a temporary storage place of data. Note that these function realization units may be configured by hardware logic such as a circuit without using a CPU.

  FIG. 2 is an explanatory view showing an example of a guideline acquired by the guideline acquiring unit 21. As shown in FIG. The current status is assumed to be "first-time detailed examination (first-time examination)".

  The guideline acquisition unit 21 acquires a guideline stored on the network or stored in advance in the storage unit 13. The guidelines indicate treatment procedures for patients, and are configured by a plurality of statuses (in the example shown in FIG. 2, statuses such as “initial workup”, “partial breast removal”, etc.).

  As the guidelines, for example, various basic guidelines published by National Comprehensive Cancer Network (NCCN), Japan Breast Cancer Society, etc. can be used. Also, the guidelines may be appropriate for each hospital or patient, or may be arranged based on the basic guidelines. FIG. 2 shows an example of invasive breast cancer guidelines prepared based on the NCCN guidelines. As shown in FIG. 2, the guidelines can be described in a flow chart or a description method such as BPMN (Business Process Modeling Notation).

  The current status determination unit 22 determines the current status to which the treatment progress state at the time of the examination corresponding to the examination information belongs based on the examination information of the subject, and causes the storage unit 13 to store it.

  FIG. 3 is a diagram for explaining transition conditions set in advance for each status of the guideline shown in FIG. Moreover, FIG. 4 is explanatory drawing which shows an example of test | inspection information.

  The transition condition from the status upstream of the procedure of the guideline to the next status that can be directly transitioned is previously defined in the status of the transition destination. The information of the transition condition may be included in the guideline as additional information, for example, or may be stored in the network storage or the storage unit 13 as another data in association with the guideline.

  For example, in the example shown in FIG. 2 and FIG. 3, there are three statuses that can be directly transitioned from the “first workup”: “partial breast resection”, “total mastectomy”, and “preoperative chemotherapy”. In each of these three statuses, a transition condition from the status of “first minute inspection” to its own status is set in advance. FIG. 3 shows an example of the transition conditions used in the description of the present embodiment, using a balloon. The transition conditions may be updated by the user via the input unit 12.

  The current status determination unit 22 is currently based on the examination date and examination purpose included in the examination information (target examination information) to be subjected to the current status determination process acquired this time, and the examination information (accompanying examination information) incidental to the patient. Determine the status. The examination information attached to the patient includes, for example, treatment order information, medical chart information, critical path information and the like (see FIG. 4). In the following description, target examination information and incidental examination information shall be appropriately referred to as examination information.

  FIG. 5 is a diagram for describing a situation where the current status is determined by the current status determination unit 22 which has acquired the examination information of the examination ID 12345 shown in FIG. 4.

  As shown in FIG. 5, the current status determination unit 22 acquires the target examination information and the accompanying examination information of the examination ID 12345 performed this time, and determines the transition of the current status based on the examination information.

  Now, it is assumed that the current status prior to the implementation of the examination ID 12345 is "first-time detailed examination". Of the three statuses "partial breast resection," "total mastectomy," and "preoperative chemotherapy" that can be directly transitioned from "initial workup," the status in which the transition condition is satisfied by the acquired examination information is "preoperatively Chemotherapy. Therefore, the current status determination unit 22 determines the current status as "preoperative chemotherapy" based on the examination information of the examination ID 12345, and stores the same in the storage unit 13.

  FIG. 6 is a diagram for explaining the situation where the current status is determined by the current status determination unit 22 that has acquired the examination information of the examination ID 56789 performed after the examination of the examination ID 12345 shown in FIG.

  Now, the current status after examination ID 12345 is "preoperative chemotherapy". As is clear from the acquired examination information of the examination ID 56,789 and the transition conditions set in each status, the current status transits in two stages from "partial breast removal" to "post-operative drug therapy". That is, the current status determination unit 22 determines the current status as “post-operative drug treatment” based on the examination information of the examination ID 56789 and causes the storage unit 13 to store it.

  The transition condition may be described by a human or may be determined using a machine learning classifier such as a support vector machine. When machine learning is performed, it is preferable to use, for example, examination information and a human-determined status as an input, and input the examination method performed this time to a discriminator to identify the current status.

  Also, implementation information may be added to the guidelines. In this case, it is preferable to highlight, for example, color the passed (processed) status on the guideline. By adding implementation information to the guidelines, the user can easily confirm the current status location simply by looking at the guidelines, and can easily grasp the treatment history leading to the current status. it can.

  FIG. 7 is an explanatory view showing an example of status / inspection image association information in which each of a plurality of inspection images is associated with each status. In FIG. 7, MG represents mammography and UL represents an ultrasonic diagnostic apparatus.

  The associating unit 23 acquires information on the current status determined by the current status determining unit 22. The association unit 23 generates status / inspection image association information in which the current status is associated with the inspection image (the inspection image captured in the inspection corresponding to the inspection information) included in the inspection information corresponding to the current status. Are stored in the storage unit 13. The associating unit 23 appends data to the status / inspection image association information each time new inspection information is acquired. As a result, the status / inspection image association information is information in which each of a plurality of inspection images is associated with each status (referred to as association status as appropriate) (see FIG. 7).

  Further, the association unit 23 may associate a report, an electrocardiogram, a blood test result and the like in addition to the test image with respect to the current status.

  Note that FIG. 7 shows an example in the case where the status / inspection image association information is information in which the inspection ID is associated with the status (association status). An inspection image is associated with each inspection ID depending on the inspection content, and the inspection image can be easily referred to from the inspection ID. Further, the examination ID to be added to the status / examination image association information may be only the examination ID including the examination image.

  Further, in the case where a plurality of examinations are associated within the same association status, it is preferable to further associate information of the order in which the examinations were performed in the association status (order within the association status). In addition, modality information used in each examination may be further associated.

  FIG. 8 is an explanatory view showing an example of a view generated by the view generation unit 24 according to the first embodiment.

  The view generation unit 24 classifies a plurality of inspection images based on the status-inspection image association information, generates a view including an inspection image belonging to the classification for each classification, and causes the display unit 11 to display the view. In the present embodiment, the view generation unit 24 classifies a plurality of inspection images for each association status, using the status / inspection image association information as it is, and generates a view for each association status (see FIG. 8).

  In addition, when new examination information is acquired and the current status is transitioned by this examination information, a view corresponding to the new current status may be generated by the examination image captured in the examination of the new examination information ( See "Follow-up" in Figure 8). Also, the view may include a report in addition to the inspection image.

  The inspection image belonging to the view generated by the view generation unit 24 may be added or deleted by the user via the input unit 12.

  Next, an example of the operation of the medical image processing apparatus 10 according to the present embodiment will be described.

FIG. 9 is a flowchart showing an example of a procedure when generating status / examination image association information to support preparation of presentation information for MDTM participants by the CPU of the control unit 15 shown in FIG. In FIG. 9, reference numerals with S attached indicate steps in the flowchart.
This procedure starts when the patient ID is obtained.

  First, in step S1, the guideline acquisition unit 21 acquires the guidelines of the patient to be discussed in the MDTM from the storage unit 13 via the network (see FIG. 2).

  Next, in step S2, the current status determination unit 22 acquires information on the current status from the storage unit 13. For example, the current status determination unit 22 acquires, from the storage unit 13, information indicating that the current status is "first precision inspection" in the guideline shown in FIG.

  Next, in step S3, the current status determination unit 22 acquires a transition condition from the current status to the next status that can directly transition (see FIG. 3).

  Next, in step S4, the current status determination unit 22 acquires examination information. For example, the current status determination unit 22 acquires examination information of the examination ID 12345 shown in FIGS. 4 and 5.

  Next, in step S5, the current status determination unit 22 determines whether there is a next status whose transition condition is satisfied by the acquired inspection information. If there is a next status that satisfies the transition condition, the process proceeds to step S6. For example, in the above example, the current status determination unit 22 determines that there is the next status “preoperative chemotherapy” that satisfies the transition condition based on the examination information of the examination ID 12345, and proceeds to step S6. On the other hand, if there is no next status that satisfies the transition condition, the process proceeds to step S7.

  Next, in step S6, the current status determination unit 22 determines the status of the transition destination as the current status and stores the status in the storage unit 13.

  Next, in step S7, the associating unit 23 acquires information on the current status determined by the current status determining unit 22. Then, the association unit 23 generates status / inspection image association information in which the current status is associated with the inspection image included in the inspection information corresponding to the current status, and stores the generated status / inspection image association information in the storage unit 13 (see FIG. 7). ).

  Next, in step S8, the associating unit 23 determines whether or not the processing for all the examination information has been completed. If the process has been completed for all examination information, the series of procedures ends. On the other hand, if there is unprocessed examination information, the process returns to step S2.

  According to the above procedure, status / examination image association information can be generated to support preparation of presentation information for MDTM participants.

  FIG. 10 shows a procedure for generating a view for each association status based on status / inspection image association information in order to support preparation of presentation information for MDTM participants by the CPU of the control unit 15 shown in FIG. It is a flowchart which shows an example. In FIG. 10, reference numerals with numbers attached to S indicate steps in the flowchart.

  This procedure starts when the series of procedures shown in FIG. 9 is completed.

  The view generation unit 24 uses the status and inspection image association information as it is, classifies a plurality of inspection images for each association status, generates a view for each association status (step S11), and causes the display unit 11 to display (step S12). ) (See FIG. 8).

  According to the above-described procedure, it is possible to generate a view for each association status based on the status / inspection image association information in order to support preparation of presentation information for participants of the MDTM.

  The medical image processing apparatus 10 according to the present embodiment can generate status / inspection image association information in which an inspection image is associated with each status of the guideline. Therefore, the user can collectively handle examination information (examination ID, examination image) for each status by referring to the status / examination image association information. In addition, the medical image processing apparatus 10 can generate and display a view for each association status based on the status / inspection image association information. Therefore, the user can significantly shorten the search time of a desired examination image by referring to the view for each association status, and can easily prepare presentation information for MDTM participants.

Second Embodiment
FIG. 11 is a block diagram showing an example of a medical image processing apparatus 10A according to the second embodiment of the present invention.

  The medical image processing apparatus 10A shown in the second embodiment has a filter unit 31, and the view generation unit 24A generates a view based on the inspection image extracted by the filter unit 31 as shown in the first embodiment. It differs from the medical image processing apparatus 10. The other configurations and functions are substantially the same as those of the medical image processing apparatus 10 shown in FIG.

  FIG. 12 is an explanatory diagram showing an example of a view when a view is generated using an inspection image that matches the filter condition when the predetermined status is “follow up”. In FIG. 12, the status / inspection image association information is the same as that shown in FIG.

  The storage unit 13A stores filter conditions in addition to the storage content of the storage unit 13. The filter conditions are preset for each of a plurality of statuses constituting the guideline. The filter condition associates, for example, a predetermined status (setting status), the status of status / examination image association information (association status), and the order in which examinations are performed in the association status (order within association status). (See the middle part of FIG. 12).

  The filter conditions may be updated by the user via the input unit 12. That is, the user can correct the filter condition in consideration of the extraction result by the filter unit 31.

  The filter unit 31 of the control unit 15A extracts the inspection image meeting the filter condition by applying the filter condition set for the predetermined status (setting status) to the status / inspection image association information. . The filter unit 31 acquires status information or current status information selected by the user via the input unit 12 and sets it as a predetermined status.

  Now, it is assumed that "follow-up" is selected by the user and the selection status (predetermined status) is set. In the example shown in FIG. 12, the filter condition when the setting status is "follow up" is that the association status is "follow up", the modality is mammography, and the order in the association status is latest, latest -1. , Is to be the first. For this reason, the filter unit 31 applies these filter conditions associated with the setting status “follow-up” to the status / inspection image association information, and extracts inspection IDs 20001, 20004, and 20005 that match these filter conditions. Do.

  The view generation unit 24A generates a view including the inspection image extracted by the filter unit 31. In the above example, the view generation unit 24A generates the view V-2 using the inspection images of the inspection IDs 20001, 20004 and 20005, and causes the display unit 11 to display the view V-2 (see the lower part of FIG. 12).

  FIG. 13 is an explanatory view showing an example of a view when a view is generated using an inspection image that matches the filter condition when the predetermined status is “relapse / VI stage close inspection (relapse check)”. is there.

  The filter condition may have multiple association statuses associated with one set status (predetermined status). Also, multiple views may be associated with one setting status (predetermined status). In FIG. 13, in the filter condition, the association status “recurrence check” and “first check” are associated with the setting status “recurrence check”, and the views V-3 and V-4 are associated An example of Further, as shown in FIG. 13, filter conditions may be set such that a view is generated for each modality.

  In the example shown in FIG. 13, when “recurrent checkup” is set as the selection status, the filter unit 31 extracts the examination IDs 10001 and 30001 for the view V-3, and the examination IDs 10002 and 30002 for the view V-4. To extract. The view generation unit 24A generates the view V-3 using the inspection IDs 10001 and 30001, and generates the view V-4 using the inspection IDs 10002 and 30002, and displays the view V-4 on the display unit 11 (see the lower part of FIG. 13). .

  Thus, the user can easily prepare a view for MDTM. Also, an ID may be attached to each of the views prepared for MDTM. In this case, these views can be easily reused in subsequent MDTMs.

  FIG. 14 is a view using inspection images that match filter conditions based on status / inspection image association information in order to support the preparation of presentation information for MDTM participants by the CPU of the control unit 15A shown in FIG. It is a flowchart which shows an example of the procedure at the time of producing | generating. In FIG. 14, reference numerals with numbers attached to S indicate steps in the flowchart.

  In step S21, the filter unit 31 acquires status information or current status information selected by the user via the input unit 12, and sets it as a predetermined status (setting status).

  Next, in step S22, the filter unit 31 refers to the storage unit 13A to acquire the filter condition associated with the setting status.

  Next, in step S23, the filter unit 31 applies the filter condition to the status-inspection image association information, and extracts inspection images of the inspection IDs 20001, 20004, and 20005 matching the filter conditions.

  Next, in step S24, the view generation unit 24A generates a view including the inspection image extracted by the filter unit 31 (see the lower part of FIG. 12 and the lower part of FIG. 13).

  According to the above-described procedure, in order to support preparation of presentation information for MDTM participants, a view can be generated using an inspection image that matches the filter condition based on the status / inspection image association information.

  The medical image processing apparatus 10A according to the present embodiment has the same effects as the medical image processing apparatus 10 according to the first embodiment. In addition, the medical image processing apparatus 10A can narrow down the examination image according to the filter condition using the status / examination image association information, and easily generate and display a view constituted by the narrowed examination image. it can. Therefore, the user can grasp the inspection status more easily and highly than the case of simply confirming the view for each association status. In addition, when a filter condition is set such that a view is generated for each modality, an image group captured by the same modality is stored in the same view, which facilitates comparative interpretation.

Third Embodiment
FIG. 15 is a block diagram showing an example of a medical image processing apparatus 10B according to the third embodiment of the present invention.

  The medical image processing apparatus 10B shown in the third embodiment includes the feedback unit 41 and the activity collecting unit 42, and updates the filter condition according to the attention level for each view in the MDTM, as shown in the second embodiment. It differs from the image processing apparatus 10A. Other configurations and operations are not substantially different from those of the medical image processing apparatus 10A shown in FIG. 11, so the same configurations are denoted by the same reference numerals and the description thereof will be omitted.

  FIG. 16A is an explanatory view showing an example of filter conditions in the case where the current status is a recurrence check and the setting status is a recurrence check. FIG. 16B is an explanatory view showing an example of time when each of the views V-1, V-2, V-3 and V-4 is actually browsed in the MDTM. FIG. 16C is an explanatory drawing showing an example of how to determine the weight of each view according to the viewing time of each view in the MDTM. FIG. 16D is an explanatory view showing an example of how the filter condition is updated according to the weight of each view.

  The storage unit 13B stores, in addition to the storage content of the storage unit 13A, information on the attention level for each view in the MDTM (hereinafter, referred to as MDTM activity information). The MDTM activity information is information on the degree of attention for each view in the MDTM. As the MDTM activity information, for example, the viewing time of each view (such as the time of active display), a flag indicating whether it is a view added during MDTM, the number of speakers viewing each view, the speaking time, the utterance Volume (incandescence) etc. are included. FIG. 16 shows an example in which the MDTM activity information is the browsing time of each view.

  The activity collection unit 42 of the control unit 15B collects and stores the MDTM activity information (information on the attention level to each view) of the meeting participant in the MDTM executed by presenting a plurality of views generated by the view generation unit 24B. The information is stored in the unit 13B (see FIG. 16B). In addition, various techniques are conventionally known as techniques for collecting information of MDTM activity information (collection techniques of active display time of image, speech recognition technique, etc.), and any of these can be used. It is.

  The feedback unit 41 of the control unit 15B determines the weight of each view on the basis of the MDTM activity information (information on the degree of attention to each view in the MDTM). FIG. 16C shows an example in the case of determining the weight of each view by the number of views × each view viewing time / total view total viewing time. In this formula, the views having a predetermined reference time or less may not be counted in the number of views (see view V-1 in FIG. 16B and FIG. 16C).

  Further, the feedback unit 41 sets the current status at the time of execution of the MDTM as a selected status, and updates the filter condition of the selected status according to the degree of attention to each view. In the example shown in FIG. 16 (d), V-2 (see FIG. 16 (a)) which was not initially associated with the filter condition of the setting status “recurring checkup” is associated according to the weight, The filter conditions are updated (see FIG. 16 (d)). At this time, the filter condition may be updated so that an inspection image whose weight is equal to or less than a predetermined value is not displayed.

  For example, if the current status is a recurrence check, it is assumed that in MDTM, views V-3 and V-4 are mainly referred to (see FIG. 16 (a)). However, when the viewing time of each view in the MDTM is actually collected, it is assumed that the view V-2 is viewed for a longer time than the view V-3 (see FIG. 16B). In this case, it is preferable to prepare the view V-2 in advance in MDTM when the current status is a recurrent examination. Therefore, the feedback unit 41 updates the filter condition of the current status at the time of execution of the MDTM in accordance with the degree of attention to each view (see FIGS. 16C and 16D).

  FIG. 17 is a flowchart showing an example of the procedure when the filter condition is updated according to the degree of attention to each view in the MDTM by the CPU of the control unit 15B shown in FIG. In FIG. 17, reference numerals with S attached indicate steps in the flowchart.

  In step S31, the feedback unit 41 acquires the filter condition from the storage unit 13B (see FIG. 16A).

  Next, in step S32, the activity collection unit 42 collects MDTM activity information (information on the attention level to each view) of the meeting participant in the MDTM executed by presenting a plurality of views generated by the view generation unit 24B. And store them in the storage unit 13B (see FIG. 16B).

  Next, in step S33, the feedback unit 41 obtains the weight of each view based on the MDTM activity information (information of the attention level to each view in the MDTM) (see FIG. 16C). Then, the feedback unit 41 sets the current status at the time of execution of the MDTM as the selected status, and updates the filter condition of the selected status according to the degree of attention to each view (see FIG. 16 (d)).

  According to the above procedure, the filter condition can be updated according to the degree of attention to each view in the MDTM.

  The medical image processing apparatus 10B according to the present embodiment has the same effects as the medical image processing apparatus 10A according to the second embodiment. Further, the medical image processing apparatus 10B can update the filter condition in accordance with the degree of attention of each view in the MDTM. For this reason, the filter conditions used in the medical image processing apparatus 10B progress to learning each time MDTM is executed, and evolve into a more user-friendly one.

  Further, the updated content of the filter condition by the feedback unit 41 of the medical image processing apparatus 10B may be shared among the patients, and may be applied to, for example, filter conditions for other patients. For example, similar patients may be extracted according to the degree of similarity of the previous implementation information (treatment history) of the guidelines, and the updated contents of the filter event may be shared between similar patients. At this time, past MDTM activity information of similar patients of the target patient may be acquired, and the filter condition of the target patient may be updated based on this information.

  While certain embodiments of the present invention have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and the gist of the invention, and are included in the invention described in the claims and the equivalent scope thereof.

10, 10A, 10B Medical Image Processing Apparatus 11 Display Unit 12 Input Unit 22 Current Status Determination Unit 23 Association Unit 24, 24A, 24B View Generation Unit 31 Filter Unit 41 Feedback Unit 42 Activity Collection Unit

Claims (12)

Date of execution of examination conducted on subject and purpose of the examination, examination image of the subject acquired in the examination, treatment order information set for the subject, and critical path information of the subject If, acquires examination information including, on the basis of the acquired examination information of the subject, a plurality of status that constitutes the guideline showing the therapeutic procedure for the subject, at the time of examination corresponding to the examination information A current status determination unit that automatically determines the current status to which the treatment progress status belongs;
An associating unit that generates association information in which each of the plurality of inspection images is associated with each status by associating the current status with the inspection image included in the inspection information;
Medical image processing apparatus provided with The current status determination unit
The current status is determined based on the examination information of the subject using a predetermined transition condition from the status upstream of the procedure of the guideline to the status that can directly transition.
The medical image processing apparatus according to claim 1. A view generation unit which classifies a plurality of inspection images based on the association information, generates a view including the inspection images belonging to the classification for each classification, and displays the view on a display unit;
The medical image processing apparatus according to claim 1, further comprising: The view generation unit
The association information is used to classify a plurality of examination images according to the status, and a view including the examination image associated with each status is generated for each status.
The medical image processing apparatus according to claim 3. By acquiring a filter condition set in advance for each of the plurality of statuses, and applying a filter condition set for a predetermined status to the association information, an inspection image meeting the filter condition is obtained. Filter part to extract,
And further
The view generation unit
Generating a view including the inspection image extracted by the filter unit;
The medical image processing apparatus according to claim 3. The filter unit is
Among the plurality of statuses constituting the guideline, the status selected by the user via the input unit is taken as the predetermined status.
The medical image processing apparatus according to claim 5. The association information is
The information is information in which the status, the inspection image, and the acquired order information of the inspection image in the status are associated with each other.
The filter condition is
Information in which the predetermined status, the status of the association information, and the acquired order information of the inspection image in each status of the association information are associated with each other.
The medical image processing apparatus according to claim 5. The filter condition is
A plurality of statuses of the association information are associated with one predetermined status,
The medical image processing apparatus according to any one of claims 5 to 7. An activity collection unit that collects attention levels for each view of meeting participants in a team medical meeting executed by presenting a plurality of views generated by the view generation unit;
A feedback unit that updates the filter condition for the current status at the time of execution of the team medical meeting according to the degree of attention to each view;
The medical image processing apparatus according to any one of claims 5 to 8, further comprising: Computer,
Date of execution of examination conducted on subject and purpose of the examination, examination image of the subject acquired in the examination, treatment order information set for the subject, and critical path information of the subject If, acquires examination information including, from said plurality of status that constitutes the guideline showing the therapeutic procedure to the subject, wherein based on the examination information of the subject, the therapeutic progress at the time of examination corresponding to the examination information A current status determination unit that automatically determines the current status corresponding to the status,
An associating unit that associates each of the plurality of inspection images with each of the statuses by associating the current status and the inspection image included in the inspection information;
Medical image processing program to function as A current status determination unit that determines a current status to which a treatment progress status at the time of an examination corresponding to the examination information belongs from a plurality of statuses constituting a guideline indicating a treatment procedure for the subject based on examination information of the subject When,
  An associating unit that generates association information in which each of the plurality of inspection images is associated with each status by associating the current status with the inspection image included in the inspection information;
  A view generation unit that classifies a plurality of inspection images based on the association information, generates a view including the inspection images belonging to the classification for each classification, and displays the view on a display unit;
  By acquiring a filter condition set in advance for each of the plurality of statuses, and applying a filter condition set for a predetermined status to the association information, an inspection image meeting the filter condition is obtained. A filter unit to extract,
An activity collection unit that collects attention levels for each view of meeting participants in a team medical meeting executed by presenting a plurality of views generated by the view generation unit;
  A feedback unit that updates the filter condition for the current status at the time of execution of the team medical meeting according to the degree of attention to each view;
  Equipped with
  The view generation unit
  Generating a view including the inspection image extracted by the filter unit;
  Medical image processing device. Computer,
  The present status corresponding to the treatment progress state at the time of the examination corresponding to the examination information is automatically determined based on the examination information of the subject from a plurality of statuses constituting a guideline indicating the treatment procedure for the subject Current status determination unit,
  An associating unit that generates association information in which each of the plurality of inspection images is associated with each of the statuses by associating the current status with the inspection image included in the inspection information;
  A view generation unit which classifies a plurality of inspection images based on the association information, generates a view including the inspection images belonging to the classification for each classification, and displays the view on a display unit;
  By acquiring a filter condition set in advance for each of the plurality of statuses, and applying a filter condition set for a predetermined status to the association information, an inspection image meeting the filter condition is obtained. Filter part to extract,
An activity collection unit that collects attention levels for each view of meeting participants in a team medical meeting executed by presenting a plurality of views generated by the view generation unit;
  A feedback unit that updates the filter condition for the current status at the time of execution of the team medical meeting according to the degree of attention to each view
  A medical image processing program to function as
  The view generation unit
  Generating a view including the inspection image extracted by the filter unit;
  Medical image processing program.

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