JP2010170311A - Medical image processing apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a medical image processing apparatus for performing an image process on a medical image using an application configured of modules suitable for various conditions of the medical image. <P>SOLUTION: The apparatus includes a relevant information storing unit 003 which stores image relevant information including at least a test device and a test portion corresponding to the medical image, a process request accepting unit 001 for accepting an image processing request, a relevant information acquiring unit 002 for acquiring the image relevant information corresponding to the medical image from the relevant information storing unit 003, a module storing unit 005 which stores a plurality of function modules, a module selecting unit 004 for selecting function modules based on the image relevant information, an image processing unit 006 for performing an image process using an application after producing the application by combining the function modules, and a display control unit 008 for displaying the medical image on a display unit 011. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a medical image processing apparatus that displays a generated medical image by performing image processing using an application that performs image processing on data captured and created with various modalities. More specifically, the present invention relates to a medical image processing apparatus that performs image processing using an application that can change some of the processing to be executed.

  2. Description of the Related Art In recent years, the types of images to be captured are increasing due to the progress of various medical image capturing apparatuses (also referred to as “modalities”) such as X-ray CT apparatuses, MRI apparatuses, and ultrasonic diagnostic apparatuses. Further, in a medical image processing apparatus for an operator such as a doctor to observe a medical image, the medical image data captured by the medical image imaging apparatus is subjected to image processing, and the medical image data subjected to this image processing is processed. The types of applications (programs) that are executed by the medical image processing apparatus to be displayed are constantly increasing.

  An application that executes image processing includes a plurality of subdivided processes. A part of an application that performs part of the processing is referred to as a functional module (also simply referred to as “module”). That is, an application is configured by combining a plurality of functional modules. For example, this functional module includes a functional module that performs image processing, a functional module that acquires functional module data for displaying an image, and the like. As processing of the entire application, a functional module that acquires data acquires medical image data from the outside, a functional module that performs image processing receives data from the functional module that acquires data, performs image processing on the data, The functional module for displaying an image receives data subjected to image processing and displays a medical image based on the data. In this way, data is exchanged between the functional modules. In recent years, unification of interfaces for transferring data between functional modules has been attempted. By unifying the interfaces of such functional modules, it is possible to supply functional modules that perform processing of a part of the application instead of the entire application. Each application can change processing performed by changing an internal function module. These functional modules have a slight difference for each supply source, and it is possible to perform more suitable processing on a medical image to be subjected to image processing due to the slight difference.

  In such a situation, it is possible to use an application configured with a function module most suitable for each image in the clinical field. However, selecting an optimal functional module from among a large number of functional module combinations and executing it as an application suitable for a medical image to be processed requires a lot of knowledge and skill. Therefore, there is a possibility that an application composed of functional modules that are not necessarily optimal is used in a fixed manner.

  Conventionally, as a technique for improving the operability of medical image processing and display, a technique for continuously displaying medical diagnosis images to be examined sequentially to be read at high speed (see, for example, Patent Document 1) or a touch panel. There has been proposed a technique (for example, see Patent Document 2) that determines the type of a touch input signal that is input using and selects a display form of a medical image corresponding to the type.

JP 2006-110202 A JP 2007-29341 A

  However, Patent Document 1 and Patent Document 2 are all premised on a single image processing or display application, and the program to be activated is not switched according to conditions such as the inspection apparatus type and the image type. . For this reason, it is difficult to perform processing using an application having a functional module suitable for the medical image to be processed.

  The present invention has been made in view of such circumstances, and provides a medical image processing apparatus that performs image processing on a medical image using an application configured with functional modules suitable for various conditions of the medical image. The purpose is that.

  To achieve the above object, a medical image processing apparatus according to claim 1 stores image-related information including at least an inspection apparatus type and an inspection site corresponding to a medical image captured by an external medical image diagnostic apparatus. Related information storage means, and module storage means for storing a plurality of functional modules, which are programs for performing different types of processing constituting a series of processing included in image processing, for each of the different types of processing, A processing request receiving means for receiving an image processing request for the specific medical image, a related information acquiring means for acquiring the image related information corresponding to the specific medical image from the related information storage means, and the acquired specific information A module selecting means for selecting a functional module based on image-related information corresponding to a medical image and the selected functional module are combined. An image processing unit that performs the series of image processing of the specific medical image, and a display control unit that causes the display unit to display the specific medical image on which the image processing has been performed. is there.

  The medical image processing apparatus according to claim 1 automatically selects a functional module that performs processing based on image-related information corresponding to a specific medical image that has received a request for image processing, and selects the selected functional module. It is the structure which performs image processing using. As a result, when performing image processing on a specific medical image, it is possible to automatically perform image processing using an appropriate function module, and the operator can select the function module corresponding to the medical image to be processed. Can be reduced. Therefore, the medical image processing apparatus according to claim 1 can contribute to efficiency improvement by reducing the load on the operator and shortening the time of image processing. In addition, since it is not necessary for the operator to select a function module, it is possible to provide an environment in which a suitable function module can be used without special knowledge of the operator.

Block diagram of a medical image processing apparatus according to the present invention The figure which shows an example of the information of the tag of DICOM Diagram for explaining application and functional module The figure of an example of the correspondence table concerning a 1st embodiment FIG. 6 is a flowchart of image processing in the medical image processing apparatus according to the first embodiment. An example of a correspondence table according to the second embodiment The figure of an example of the correspondence table concerning a 3rd embodiment Illustration of an example of a recommendation table

[First Embodiment]
A medical image processing apparatus according to the first embodiment of the present invention will be described below. FIG. 1 is a block diagram showing functions of a medical image processing apparatus according to the present invention. However, the medical image processing apparatus according to the present embodiment does not have the recommended information management unit 012 represented by the dotted line in FIG. The recommended information management unit 012 will be described in a fourth embodiment.

  The user interface 009 has an input unit 010 and a display unit 011. The operator refers to the image or input screen displayed on the display unit 011 and performs input to the medical image processing apparatus using the input unit 010. This display unit 011 corresponds to the “display unit” in the present invention.

  The image storage unit 007 is configured by a storage medium such as a hard disk. The image storage unit 007 stores in advance image data of a medical image captured by an image diagnostic apparatus (modality) such as an ultrasonic diagnostic apparatus, an MRI apparatus, or an X-ray CT apparatus together with identification information of each medical image.

  The related information storage unit 003 is configured by a storage medium such as a hard disk. The related information storage unit 003 stores image related information related to the medical image in association with the identification information of the medical image captured by the above-described image diagnostic apparatus. This image related information is stored as supplementary information of a medical image in accordance with the DICOM standard. In other words, each image related information is stored with a tag which is identification information defined by DICOM. This tag is information as shown in FIG. FIG. 2 is a diagram showing an example of DICOM tag information. For example, as information corresponding to the tag (0008, 0016) indicated by the tag 201, information called SOP class UID indicated by the content 202 is stored. In the present embodiment, the related information storage unit 003 stores an inspection apparatus type, an inspection site, an inspection purpose, an image type, and an image size as image related information. The information described as “modality” in FIG. 2 indicates the type (inspection device type) of the inspection device that has captured the medical image. Here, the image related information stored in the related information storage unit 003 is not particularly limited, and any information may be used as long as the information is related to the medical image. This related information storage unit 003 corresponds to the “related information storage unit” in the present invention.

  The processing request reception unit 001 receives an image processing request for a medical image from the input unit 010. The image processing request from the input unit 010 includes medical image identification information. The processing request reception unit 001 outputs the acquired medical image identification information to the related information acquisition unit 002. This processing request receiving unit 001 corresponds to “processing request receiving means” in the present invention.

  The related information acquisition unit 002 has a storage area such as a hard disk or a memory. The related information acquisition unit 002 stores tag information corresponding to the image related information used in its own storage area. In the present embodiment, since the type of the inspection apparatus is used as the image-related information, tags (0008, 0060) corresponding to the modalities described in FIG. 2 are stored. The related information acquisition unit 002 receives input of medical image identification information from the processing request reception unit 001. The related information acquisition unit 002 refers to the related information storage unit 003 based on the acquired identification information of the medical image and information on the tag of the image related information. The related information acquisition unit 002 extracts and acquires image related information corresponding to the tag information from the supplementary information of the medical image corresponding to the identification information. For example, the related information acquisition unit 002 refers to the related information storage unit 003 based on the tag (0008, 0060) together with the identification information of the medical image, and acquires the type of the inspection apparatus that generated the medical image. The related information acquisition unit 002 outputs the acquired image related information and tag information to the module selection unit 004. In this embodiment, tag information is output. However, only image-related information may be output. This related information acquisition unit 002 corresponds to “related information acquisition means” in the present invention.

  The module storage unit 005 is configured by a storage medium such as a hard disk. The module storage unit 005 stores a plurality of functional modules that perform a part of the series of processes included in the image processing. The module storage unit 005 corresponds to the “module storage unit” in the present invention.

  Here, the functional module will be described in detail. An application that performs image processing such as reconstruction of a 3D image has a series of operations in which one application receives image data of a medical image, processes the image data, and displays the processed image data. Is going. Looking more closely at the application that performs this image processing, one application performs a series of image processing by executing a plurality of processes when performing image processing on image data of a medical image. For example, as shown in FIG. 3, the processing performed by the application 340 includes a combination of a type A process indicated by 310, a type B process indicated by 320, and a type C process indicated by 330. FIG. 3 is a diagram for explaining applications and functional modules. Individual programs that perform the individual processes are called function modules. That is, in FIG. 3, the application 340 includes a functional module that performs a type of processing A, a functional module that performs a type B process, and a functional module that performs a type C process. In other words, the processing for the medical image is completed by the individual functional modules sequentially processing the image data of the medical image. As specific examples, functional modules include a functional module that acquires image data, a functional module that performs processing on the data, and a functional module that instructs display. Each functional module receives the image data, performs the processing performed by itself, and passes the processed image data to the functional module performing the next processing. As shown in FIG. 3, there are a plurality of functional modules for each different type of processing. Specifically, there are a plurality of functional modules such as module B1, module B2, and module B3 for the type of processing B. For example, if B is a function module of the type of image processing, the function module includes a function module that reconstructs a 3D image, a function module that performs CAD processing, and a function module that performs blood vessel extraction.

  As this functional module, a plurality of functional modules that perform substantially the same processing may be stored. This is because, for example, in a process of reconstructing a 3D image based on image data that is volume data, there are a plurality of processing methods in the reconstruction method, and an appropriate method is used depending on the type of volume data that is the basis. The processing method may be different. Therefore, since there are functional modules that perform different processing methods even if they are functional modules that perform substantially the same processing, the module storage unit 005 stores those functional modules that perform the same processing but have differences. Will do.

  Various kinds of image processing can be performed by an application constituted by such a combination of functional modules. Specifically, as shown in FIG. 3, the module A1 shown in 311 as a functional module that performs the process A, the module B3 shown in 321 as the functional module that performs the process B, and the functional module 331 that performs the process C Are combined (hereinafter, the combination of functional modules is represented as “A + B + C”), and the application 341 is configured by A1 + B3 + C2. And it can be set as the application which performs a different process by replacing | exchanging a specific function module with another function module. For example, when the module B3 among the functional modules of the application 341 described above is replaced with the module B2, an application composed of A1 + B2 + C2 can be obtained. This application is different from the application 341 in that the type of processing part B is different. Specifically, if there are a functional module that receives image data, a functional module that performs processing, and a functional module that supports display, an application that performs different processing by replacing the functional module that performs processing. It is possible.

  The module selection unit 004 has a storage area such as a hard disk or a memory. The module selection unit 004 stores a correspondence table in which tags, image related information, and module identification information are described as shown in FIG. FIG. 4 is a diagram illustrating an example of a correspondence table according to the present embodiment. Here, in the present embodiment, tag information is also described in the correspondence table, but the tag information may not be described in the correspondence table. In this embodiment, the module selection unit 004 stores only the correspondence table shown in FIG. In the present embodiment, the types of processing A and C shown in FIG. 3 are configured such that the module A1 and the module C1 are used in a fixed manner, respectively. In other words, in the present embodiment, only the portion that performs the type of processing B can be changed. The information that the modules A1 and C1 are used in a fixed manner is stored in advance by the module selection unit 004. Here, in this embodiment, in order to make the explanation easy to understand, only the part of processing of the type B shown by 220 in FIG. 3 can be changed, but this is a structure in which other parts can be changed or a combination thereof. May be.

  The module selection unit 004 receives input of tag information and image related information from the related information acquisition unit 002. The module selection unit 004 acquires corresponding module identification information based on the acquired tag information and image-related information. For example, when the module selection unit 004 acquires CT as image-related information and (0008, 0006) as tag information, the module selection unit 004 acquires the identification information of the module B2 as module identification information. Then, the module selection unit 004 acquires the module B2 from the module storage unit 005 based on the identification information of the module B2. Further, the module selection unit 004 acquires from the module storage unit 005 the module A1 and the module C1 that are determined to be used in a fixed manner.

  The module selection unit 004 outputs the selected function modules, module A1, module B2, and module C1, to the image processing unit 006. This module selection unit 004 corresponds to “module selection means” in the present invention.

  The image processing unit 006 receives inputs of the module A1, the module B2, and the module C1 from the module selection unit 004. The image processing unit 006 forms a combination of A1 + B2 + C1 by combining the input module A1, module B2, and module C1.

  The image processing unit 006 refers to the image storage unit 007 based on the identification information of the medical image that has received the processing request input from the input unit 010, and acquires a medical image corresponding to the identification information. The image processing unit 006 performs image processing on the acquired medical image using a combination of the generated functional modules of A1 + B2 + C1, and outputs a display request together with the medical image subjected to the processing processing to the display control unit 008. This image processing unit 006 corresponds to the “image processing means” in the present invention.

  The display control unit 008 receives a medical image and a display request from the display control unit 008. Then, the display control unit 008 displays a medical image on the display unit 011 based on the display request. This display control unit 008 corresponds to “display control means” in the present invention.

  Next, an image processing operation in the medical image processing apparatus according to the present embodiment will be described with reference to FIG. Here, FIG. 5 is a flowchart of image processing in the medical image processing apparatus according to the present embodiment.

  Step S001: The processing request reception unit 001 receives a request for image processing of a medical image including identification information of the medical image input by the operator using the input unit 010. The processing request reception unit 001 outputs the received medical image identification information and image processing request to the related information acquisition unit 002.

  Step S002: The related information acquisition unit 002 receives input of medical image identification information and an image processing request from the processing request receiving unit 001. The related information acquisition unit 002 searches the related information storage unit 003 based on the input identification information of the medical image and the information of the DICOM tag used to select the function module stored by itself, and issues an image processing request. Image related information that matches the tag information is extracted and acquired from the image related information of the received medical image. The related information acquisition unit 002 outputs the tag information and the acquired image related information to the module selection unit 004.

  Step S003: The module selection unit 004 receives input of tag information and image related information from the related information acquisition unit 002. The module selection unit 004 refers to the correspondence table stored in advance based on the input tag information and image related information, and extracts module identification information corresponding to the image related information.

  Step S004: The module selection unit 004 refers to the module storage unit 005 based on the extracted module identification information, and extracts and acquires a functional module corresponding to the identification information. Further, the module selection unit 004 acquires a corresponding functional module based on module identification information used in a fixed manner that is stored in advance. Then, the module selection unit 004 outputs the acquired functional module to the image processing unit 006.

  Step S005: The image processing unit 006 receives an input of a functional module from the module selection unit 004.

  Step S006: The image processing unit 006 refers to the image storage unit 007 on the basis of the identification information of the medical image to be subjected to image processing input from the operator, and extracts and acquires the image data of the medical image.

  Step S007: The image processing unit 006 performs image processing on the medical image requested for image processing by combining the input functional modules with the acquired image data of the medical image. The image processing unit 006 outputs a medical image display command together with the image data of the medical image subjected to the processing to the display control unit 008.

  Step S008: The display control unit 008 receives input of the image data of the medical image and the display command of the medical image from the image processing unit 006. The display control unit 008 displays a medical image on the display unit 011 based on the display command.

  Here, for convenience of explanation, step S005 and step S006 have been described as performing step S006 after performing step S005, but the order of these steps may be reversed or performed in parallel.

  As described above, the medical image processing apparatus according to the present embodiment automatically selects a functional module based on image-related information corresponding to a medical image for which image processing has been requested, and the selected functional module. Are combined to perform image processing of the medical image. As a result, it is possible to automatically select an appropriate functional module for a medical image for which image processing has been requested. The trouble of searching for a suitable function module can be saved. As a result, it is possible to improve the efficiency of image processing for medical images.

[Second Embodiment]
A medical image processing apparatus according to the second embodiment of the present invention will be described below. The medical image processing apparatus according to the present embodiment has a configuration in which a score is assigned to a function module to be selected based on each image related information, and a function module having the highest total score is selected. This is different from the embodiment. Therefore, the selection of functional modules will be mainly described below. A block diagram showing functions in the medical image processing apparatus according to the present embodiment is also shown in FIG. In the following description, functional units having the same reference numerals as those in the first embodiment are assumed to have the same functions unless otherwise specified.

  The module selection unit 004 according to the present embodiment stores a correspondence table described in FIG. Here, FIG. 6 is an example of a correspondence table according to the present embodiment. The correspondence table in FIG. 6 is different from the correspondence table in FIG. 4 used in the first embodiment, and a score (score) is assigned to each module identification information corresponding to the image related information. This score is a number representing how suitable the functional module is for the image related information, and the higher the score, the more suitable it is. That is, the functional modules stored in the module storage unit 005 are not limited to one functional module that can process image data having certain image-related information, and a plurality of functional modules can perform processing. There is. In this case, there is a functional module that is more suitable for performing processing according to the content of the image related information. Therefore, by assigning a high score to a function module that is suitable for processing for each image related information, the degree of suitability of the function module for the image related information is expressed. For example, as shown in FIG. 6, both the image related information 601 and the image related information 602 are MRI. There are two modules, module B1 represented by module identification information 603 and module B2 represented by module identification information 604, as functional modules capable of executing image processing on the MRI image data. The score of each functional module is given a score 605, 10 points for module B1, and 20 points for module B2 as score 606. That is, both the module B1 and the module B2 can perform image processing on MRI image data, but the module B2 is a more suitable functional module for processing MRI image data. The correspondence table is shown. In the following, when expressing the number of points attached to the module identification information, the number of points attached in parentheses after the module identification information is described as “module B1 (10)”. Here, in this embodiment, in order to simplify the explanation, the type of the inspection apparatus and the inspection site are used as the image related information. However, this may be performed using other image related information such as the image size. The image-related information used may be combined in any way.

  The module selection unit 004 receives input of tag information and image related information from the related information acquisition unit 002. In the present embodiment, since the type of the inspection apparatus and the inspection site are used as the image related information for selecting the functional module, the module selection unit 004 receives the information on the type of the inspection apparatus and the information on the inspection site from the related information acquisition unit 002. Receive input. In the following description, the case where the module selection unit 004 receives information “MRI” as the type of the inspection apparatus and “abdomen” as the inspection part will be described.

  The module selection unit 004 refers to the correspondence table shown in FIG. 6 stored by itself based on the MRI and the abdomen that are the input image-related information. And the module selection part 004 acquires module B1 (10) and module B2 (20) as module identification information corresponding to MRI. Moreover, the module selection part 004 acquires module B1 (10) and module B2 (15) as module identification information corresponding to an abdomen. And the module selection part 004 totals the score corresponding to the acquired module identification information for every module identification information, respectively. Here, the score of module B1 is 20, and the score of module B2 is 35 points. Then, the module selection unit 004 selects the module identification information having the highest score. Here, since module B2 has a higher total score than module B1, module selection unit 004 selects module B2. Here, in this embodiment, the case where two pieces of module identification information are extracted has been described. However, more module identification information may actually be extracted, and in that case, the module selection unit 004 may also be extracted. The function module is selected by selecting the module identification information having the highest total score.

  Also in this embodiment, as in the first embodiment, the module selection unit 004 stores a module A1 and a module C1 in advance as module identification information to be used in a fixed manner. Here, as in the first embodiment, in order to make the explanation easy to understand, only the part of the type B processing can be changed, but this may be a structure in which other parts can be changed or a combination thereof. .

  Therefore, the module selection unit 004 searches the module storage unit 005 based on the module A1 and the module C1 that are the module identification information stored in advance and the module B2 that is the selected module identification information. B2 and module C1 are acquired.

  The module selection unit 004 outputs the acquired module A1, module B2, and module C1 to the image processing unit 006.

  As described above, the medical image processing apparatus according to the present embodiment is configured to select the functional module having the highest total number of points given among them when a plurality of functional modules are selected. . As a result, even when a plurality of functional modules can process image data of a certain medical image, a more suitable functional module can be selected as a functional module that processes the image data. .

[Third Embodiment]
A medical image processing apparatus according to the third embodiment of the present invention will be described below. The medical image processing apparatus according to this embodiment is configured to select a function module designated by the operator from among function modules to be selected based on each image-related information, as in the first and second embodiments. Is different. Therefore, in the following, selection of functional modules in the case of a medical image processing apparatus based on the second embodiment will be mainly described. A block diagram showing functions in the medical image processing apparatus according to the present embodiment is also shown in FIG. In the following description, functional units denoted by the same reference numerals as those in the second embodiment have the same functions unless otherwise specified.

  The module selection unit 004 according to the present embodiment stores a correspondence table described in FIG. Here, FIG. 7 is a diagram of an example of a correspondence table according to the present embodiment. The correspondence table in FIG. 7 differs from the correspondence table in FIG. 6 used in the second embodiment in that operator identification information is attached to each module identification information corresponding to image-related information. This operator identification information indicates which functional module the operator corresponding to the identification information requires to use for specific image related information. Since image processing applications are highly specialized, there are cases in which functional modules desired to be used differ depending on the past experience of each operator even in the same facility. Therefore, by attaching the user identification information to the correspondence between the image related information desired by the operator and the module identification information, the functional module desired by the operator for the specific image related information can be obtained. Can be judged.

  For example, as shown in FIG. 7, both the image related information 701 and the image related information 702 are MRI. There are two function modules that can execute image processing on the MRI image data: module B1 represented by module identification information 703 and module B2 represented by module identification information 704. Then, XXX is assigned to the set of MRI and module B1 as 705, and YYY is assigned to the set of MRI and module B2 as operator ID as 706. Thereby, the operator whose operator ID is XXX specifies that the module B1 is used for the MRI image data, and the operator ID indicates that the module B2 is used for the MRI image data. It can be determined that the operator who is YYY has designated. Here, in this embodiment, in order to simplify the explanation, the type of the inspection apparatus and the inspection site are used as the image related information. However, this may be performed using other image related information such as the image size. The image-related information used may be combined in any way.

  The identification information of the operator may be automatically described in the correspondence table based on the history of use of the function module by the operator, or may be described in the correspondence table in response to an input from the operator. In the present embodiment, it is assumed that the input from each operator is received in advance and described in the correspondence table. Furthermore, the operator information in the correspondence table may be managed in a fixed manner, or may be configured to be automatically updated.

  The module selection unit 004 acquires operator identification information from the input unit 010. Here, the configuration in which the module selection unit 004 acquires the operator identification information from another function unit (for example, the processing request reception unit 001) may be used. Further, the module selection unit 004 acquires tag information and image related information from the related information acquisition unit 002. In the following description, it is assumed that the module selection unit 004 receives “XXX” as the operator identification information and “MRI” and “abdomen” information as the image-related information.

  The module selection unit 004 refers to the correspondence table based on the information of the operator ID “XXX”, the type of inspection apparatus “MRI”, and the inspection site “abdomen”. The module selection unit 004 first extracts a module B1 that is module identification information in which the image-related information is “MRI” and the operator ID “XXX” is attached. Further, the module selection unit 004 first extracts a module B1 which is module identification information in which the image-related information is “abdomen” and the operator ID “XXX” is attached. In this case, since all the operators with the operator ID “XXX” designate the module B1, the module selection unit 004 extracts the identification information of the module B1.

  Also in this embodiment, as in the second embodiment, the module selection unit 004 stores a module A1 and a module C1 in advance as module identification information to be used in a fixed manner. Here, as in the first embodiment, in order to make the explanation easy to understand, only the part of the type B processing can be changed, but this may be a structure in which other parts can be changed or a combination thereof. .

  Therefore, the module selection unit 004 searches the module storage unit 005 based on the modules A1 and C1 which are identification information stored in advance and the module B2 which is the selected module identification information, and performs module A1, module B2 And module C1.

  The module selection unit 004 outputs the acquired module A1, module B2, and module C1 to the image processing unit 006.

  In the above description, the case where the operator designates the same functional module has been described. However, the designation of the operator may be different. For example, when “MRI” and “head” are input as the image-related information, the operator whose operator ID is XXX is module B1 for “MRI” and module B2 for “head”. The specified function module is different. In this case, similarly to the second embodiment, the module selection unit 004 calculates the total number of points assigned to the selected module identification information, and selects the module identification information having the highest score. In the case of “MRI” and “head” described above, since the total score of module B1 is 25 and the total score of module B2 is 30, the module selection unit 004 acquires the identification information of module B2. Also, when there is no designation by the operator, the module selection unit 004 similarly calculates the total score and selects the one with the highest score.

  As described above, the medical image processing apparatus according to the present embodiment is configured to preferentially use the functional module specified by the operator. This makes it possible to automatically select a function module suitable for each operator, and to improve the convenience of image processing for each operator's medical image.

  In the above description, information for uniquely identifying one person is used as information for identifying an operator. However, a group including a plurality of operators may be created and the identification information of the group may be used.

  As the operator identification information in the above description, a code for identifying a medical department may be used. Further, as the identification information of the operator group, an identification number defined outside the medical facility such as an identification number of a community constructed on a network called SNS (Social Networking Service) may be used.

[Fourth Embodiment]
A medical image processing apparatus according to the fourth embodiment of the present invention will be described below. The medical image processing apparatus according to the present embodiment is configured to take statistics about which functional modules each operator recommends, and to preferentially use functional modules recommended by more operators. This is different from the first to third embodiments. Therefore, in the following, the function module recommendation method and the function module selection will be mainly described. A block diagram showing functions in the medical image processing apparatus according to the present embodiment is also shown in FIG. In the following description, functional units having the same reference numerals as those in the first embodiment are assumed to have the same functions unless otherwise specified.

  The medical image processing apparatus according to this embodiment is obtained by adding a recommended information management unit 012 represented by a dotted line in FIG. 1 to the medical image processing apparatus according to the first embodiment. The recommended information management unit 012 corresponds to “recommended information management means” in the present invention.

  The operator inputs a recommended combination of specific image-related information and a specific function module to the recommended information management unit 012 using the input unit 010 based on information obtained from his / her own experience and technical data. To do. The recommended combination is input by referring to the input screen displayed on the display unit 011 based on the format stored in advance by the display control unit 008. As this input screen, for example, a plurality of combinations of image-related information and module identification information are displayed so as to be selectable, and a recommendation button is arranged for each combination. Then, when the operator presses the recommendation button corresponding to the recommended combination, the recommended information for the combination is transmitted to the recommended information management unit 012.

  The recommended information management unit 012 has a storage area such as a hard disk or a memory. In the storage area of the recommended information management unit 012, a recommendation degree table as shown in FIG. 8 is stored. Here, FIG. 8 is an example of a recommendation degree table. As shown in FIG. 8, in the recommendation level table, a recommendation level is assigned to each combination of image-related information and module identification information. Here, in the present embodiment, the information described in the recommendation degree table is described as a combination of image-related information and module identification information. However, other information may be added, for example, a recommender of a functional module. The identification information may be included.

  The recommended information management unit 012 receives input of information on a combination of recommended image related information and module identification information from the input unit 010. When receiving the input of the combination, the recommended information management unit 012 adds 1 to the recommended degree of the corresponding combination. As described above, the recommended combination increases in the value of the recommendation level, so that the higher the recommendation level, the more recommended the combination is recommended. For example, in FIG. 8, in module B1, the recommendation degree 801 for the MRI image data is 71 and the recommendation degree 802 for the CT image data is 53. Therefore, it is recommended that the module B1 process the MRI image data. Has been.

  Here, in the present embodiment, the number of recommended degrees is simply incremented. However, this may be another method. For example, a ratio in image-related information having the same tag may be obtained. When the ratio is obtained in this way, the closer to 100, the more recommended. Further, in the present embodiment, the recommendation degree is increased by 1 for all the operator's recommendations, but each operator's recommendation input may be weighted by increasing the rate of increase by the operator. In this way, for example, the recommendation of the group leader can be reflected in the recommendation degree more greatly. Furthermore, information on these degrees of recommendation may be collected once and the operator may periodically update the data, or the data may be automatically updated.

  The recommended information management unit 012 receives an input of a combination of the image related information extracted by the module selection unit 004 and the module identification information. In the following, it is assumed that “MRI” and “abdomen” are used as the image related information, and that the module selection unit 004 extracts the modules B1 and B2 based on “MRI” and “abdomen”. explain. When the recommended information management unit 012 receives the above-described input from the module selection unit 004, the recommended information management unit 012 refers to the recommendation level table based on the input combination, and the recommended level of the combination of each input image related information and each functional module Are extracted and output to the module selection unit 004. Here, the recommended information management unit 012 has a recommendation level of 71 (module B1, abdomen) for the combination of “MRI” and “module B1” (hereinafter, the combination is displayed as (module B1, MRI)). 82 is output to the module selection unit 004 as the recommendation level, 54 as the recommendation level of (module B2, MRI), and 56 as the recommendation level of (module B2, abdomen).

  The module selection unit 004 refers to a correspondence table stored by itself based on “MRI” and “abdomen” that are image-related information, and extracts module identification information to be selected. Here, the module selection unit 004 extracts the module B1 and the module B2. Then, the module selection unit 004 outputs “MRI” and “abdomen” as the used image-related information, and the modules B1 and B2 as the extracted module identification information to the recommended information management unit 012.

  The module selection unit 004 receives an input of the recommendation level of each functional module for each image related information from the recommended information management unit 012. The module selection unit 004 totals the input recommendation degrees for each module identification information. In the present embodiment, the total recommended level of module B1 is 153, the total recommended level of module B2 is 110, and the total recommended level of module B1 is higher. Therefore, the module selection unit 004 extracts the module identification information having the highest recommendation score. In the present embodiment, the module selection unit 004 extracts the module B1 as module identification information.

  Also in this embodiment, as in the first embodiment, the module selection unit 004 stores a module A1 and a module C1 in advance as module identification information of a functional module used in a fixed manner. Here, as in the first embodiment, in order to make the explanation easy to understand, only the part of the type B processing can be changed, but this may be a structure in which other parts can be changed or a combination thereof. .

  Therefore, the module selection unit 004 searches the module storage unit 005 based on the modules A1 and C1 which are identification information stored in advance and the module B1 which is identification information of the selected module. B1 and module C1 are acquired.

  The module selection unit 004 outputs the acquired module A1, module B1, and module C1 to the image processing unit 006.

  In the above description, the configuration in which the recommended information management unit 012 is added to the medical image processing apparatus of the first embodiment has been described, but this may be combined with the second embodiment and the third embodiment. In that case, it is necessary to determine in advance which point should be used preferentially. For example, when combined with the second embodiment, when the recommendation level is given priority over the score score, the function module to be selected is first determined using the recommendation level, and the function module to be selected still cannot be determined The function module to be selected is determined based on the total score (for example, when the recommendation level is the same value).

  As described above, the medical image processing apparatus according to the present embodiment takes statistics of combinations of image-related information and functional modules recommended by the operator, and selects functional modules to be used based on the statistical results. It is the structure to perform. This makes it possible to automatically select function modules that incorporate the opinions of the operator over a wide range, and to select appropriate function modules that reflect more diverse opinions.

  Furthermore, in the medical image processing apparatus described in the first to fourth embodiments, part or all of the image related information may be acquired from another system connected via a network.

  For example, as a system connected via a network, there is a hospital information system (HIS) and a radiation department management system (RIS: Radiology Information System). These systems manage basic patient information such as patient designation, age, sex, and allergy information, and manage examination requests issued by doctors. This inspection request includes information such as the type of inspection apparatus and the inspection site. The radiation department management system manages inspection requests for radiation-related inspections and inspection execution records. Information such as the type of inspection apparatus and the inspection site is included in the inspection request and inspection execution record. In this case, the related information storage unit 003 is arranged in these systems.

  The related information acquisition unit 002 acquires image-related information used from the above-described hospital information system, radiation department system, or the like via the network, for example, information such as the type of examination apparatus. The image-related information may be acquired according to a method (protocol, transmission method, etc.) defined for each system, but it is preferable to use a protocol for medical information exchange called HL7. The related information acquisition unit 002 may acquire all necessary image related information from one system such as a hospital information system or a radiation department system, or may acquire from a plurality of systems. Also in such a configuration, the related information acquisition unit 002 may use the above-described data acquisition from the DICOM data.

  Since DICOM data emphasizes interoperability with other medical facilities, it is difficult to manage unique information and temporary information defined for each facility. On the other hand, when acquiring image-related information via a network, hospital-specific information is used in hospital information systems and radiology department systems (for example, graphs showing that specific medical images can be applied to specific types of case study purposes) In addition, since temporary information is relatively easy, it is easy to use such information as image-related information.

001 Processing Request Accepting Unit 002 Related Information Acquisition Unit 003 Related Information Storage Unit 004 Module Selection Unit 005 Module Storage Unit 006 Image Processing Unit 007 Image Storage Unit 008 Display Control Unit 009 User Interface 010 Input Unit 011 Display Unit 012 Recommended Information Management Unit

Claims (9)

Related information storage means for storing image related information including at least an inspection apparatus type and an inspection site corresponding to a medical image captured by an external medical image diagnostic apparatus;
Module storage means for storing a plurality of functional modules, each of which is a program for performing different types of processing constituting a series of processing included in image processing, for each of the different types of processing;
A processing request receiving means for receiving an image processing request for the specific medical image;
Related information acquisition means for acquiring the image related information corresponding to the specific medical image from the related information storage means;
Module selection means for selecting a functional module based on image-related information corresponding to the acquired specific medical image;
Image processing means for performing the series of image processing of the specific medical image by combining the selected functional modules;
Display control means for causing the display means to display the specific medical image on which the image processing has been performed;
A medical image processing apparatus comprising: The module selection means stores a module selection table in which the image related information and identification information of the functional module corresponding to the image related information are stored, and the image related information corresponding to the specific medical image The medical image processing apparatus according to claim 1, wherein the functional module is selected by referring to the module selection table based on the function. The related information storage means stores the image related information corresponding to tag information that is information for identifying data defined by DICOM,
The medical image processing apparatus according to claim 1, wherein the related information acquisition unit acquires the image related information based on the tag information. The module selection unit stores in advance information on the function module corresponding to the identification information of the operator and the image-related information, and the identification information of the operator who made the image processing request for the specific medical image and the specific information Selecting the functional module based on the image-related information corresponding to a medical image;
The medical image processing apparatus according to claim 1, wherein the medical image processing apparatus is a medical image processing apparatus. The module selection means stores in advance information on a group including identification information of a plurality of operators, and information on functional modules corresponding to image-related information for each group, and requests image processing of the specific medical image. The function module is selected based on the identification information of the operator who performed the image-related information corresponding to the specific medical image,
The medical image processing apparatus according to claim 1, wherein the medical image processing apparatus is a medical image processing apparatus. The module selection means stores a score in advance for each combination of the image related information and the functional module, and selects the functional module based on the image related information and the score corresponding to the specific medical image. Do
The medical image processing apparatus according to claim 1, wherein the medical image processing apparatus is a medical image processing apparatus.   When the module selection means receives a plurality of the image related information, the module selection means adds up the points corresponding to the combination of the plurality of image related information and the function module for each functional module. The medical image processing apparatus according to claim 6, wherein the score is a combination score of the functional modules. In response to designation from the operator for the specific combination of the image-related information and the specific functional module, the information processing device further comprises recommended information management means for obtaining a recommendation level of the combination of the image-related information and the functional module,
The module selection means selects the functional module based on the image related information corresponding to the specific medical image and the recommendation level.
The medical image processing apparatus according to claim 1, wherein the medical image processing apparatus is a medical image processing apparatus.   The medical image processing apparatus according to claim 1, wherein the image-related information includes an image type, an image size, and an inspection purpose.

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