JP2009011720A - Medical image processor, medical image processing method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To eliminate a load on a user caused by manually dividing the medical images of the same series into the different series of groups. <P>SOLUTION: An image detecting device acquires slice position information (part specifying information) respectively from a plurality of medical image data frames received from a modality. When the slice position information is larger than a setting value, series information of the corresponding medical image data frame is changed. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a medical image processing apparatus, a medical image processing method, and a program.

  In the medical field, medical images taken of patients are digitized and handled. Specifically, digital image data (hereinafter referred to as “modality”) such as a CR (Computed Radiography) device, a CT (Computed Tomography) device, or an MR (Magnetic Resonance) device is used. (Referred to as “medical image data”). The generated medical image data is stored and managed by a system called PACS (Picture Archiving and Communication System for medical application) (see Patent Document 1).

  The medical image data has a data format conforming to the DICOM (Digital Imaging and Communication in Medicine) standard, and includes image data of a medical image and accompanying information related to the image data. DICOM is a standard for communication and storage format of medical images, and intercompatibility between different medical devices is ensured by complying with this standard.

  Here, medical image data corresponding to one medical image is referred to as a medical image data frame. The incidental information includes patient information, examination information, and series information. Patient information is data set for each patient, such as the reception number, name, patient ID, and sex of the patient to be photographed. The examination information is data indicating examination conditions such as an examination ID for identifying an examination ordered by a doctor, an examination site, an imaging direction, and a body position.

The series information is data including a series ID indicating a unit (series) of a series of medical images for each modality generated in one examination and a type of modality. For example, in a certain examination, it is assumed that 100 images of the chest are taken with a CT apparatus, and then 100 images of the abdomen are taken. In this case, the medical image data frame (100 frames) related to the medical image of the chest and the medical image data frame (100 frames) related to the medical image of the abdomen are in different series, and each series ID has a different value. For example, the series ID of the medical image data frame (100 frames) related to the medical image of the chest is “1”, and the series ID of the medical image data frame (100 frames) related to the medical image of the abdomen is “2”.
JP 2002-132557 A

  By the way, in the medical field, in order to reduce the burden on the patient who is the subject of taking a medical image, there is an opportunity to take the whole body together without taking the medical image of the chest and the medical image of the abdomen separately. There are many.

  Therefore, the medical image data frame related to the medical image of the chest and the medical image data frame related to the medical image of the abdomen are in the same series. Work has been done to divide medical image data frames into different series groups.

  Such a division work is an extra work different from the interpretation and the like, and has been a burden on the radiographer and the interpretation doctor.

  The present invention has been made in view of the above-described problems, and its purpose is to eliminate the burden on the user by manually dividing medical images of the same series into different series groups. It is.

In order to solve the above problems, the invention described in claim 1
Of the plurality of medical image data frames having image data of medical images and supplementary information related to the medical image including series information, the imaging region of the patient is specified from each medical image data frame having the same series information. Obtaining means for obtaining the part specifying information;
Based on the part specifying information acquired by the acquisition means, changing means for changing the series information of each medical image data frame having the same series information;
Is provided.

The invention according to claim 2 is the invention according to claim 1,
The changing means is
Based on the part specifying information acquired by the acquisition means, the series information of each medical image data frame having the same series information is changed to series information corresponding to each part.

The invention according to claim 3 is the invention according to claim 1 or 2,
The part specifying information is included in the incidental information.

The invention according to claim 4 is the invention according to claim 1 or 2,
Generating means for analyzing the image data and generating image signal distribution information;
Further comprising
The part specifying information is the image signal distribution information.

The invention according to claim 5 is the invention according to claim 1 or 2,
Generating means for analyzing the image data and generating a profile;
Further comprising
The part specifying information is the profile.

The medical image processing method according to claim 6 comprises:
Of the plurality of medical image data frames having image data of medical images and supplementary information related to the medical image including series information, the imaging region of the patient is specified from each medical image data frame having the same series information. An acquisition step of acquiring the part specifying information;
Based on the part specifying information acquired in the acquisition step, a change step of changing the series information of each medical image data frame in which the series information is the same,
Have

The program according to claim 7 is:
Computer
Of the plurality of medical image data frames having image data of medical images and supplementary information related to the medical image including series information, the imaging region of the patient is specified from each medical image data frame having the same series information. Acquisition means for acquiring the part specifying information of
Changing means for changing the series information of each medical image data frame having the same series information based on the part specifying information acquired by the acquiring means;
To function as.

  According to the present invention, it is possible to eliminate the burden on the user by manually dividing medical images of the same series into different series groups.

[First embodiment]
Hereinafter, a first embodiment of the present invention will be described in detail with reference to FIGS.

[System configuration of medical imaging system]
FIG. 1 shows a system configuration of the medical image system 100. As shown in FIG. 1, the medical image system 100 is configured such that an RIS 10, a modality 20, an image inspection device 30, and a PACS 40 are connected via a communication network N, and each of them can perform data communication.

  The RIS 10 is configured by a computer having a control unit, a storage unit, an operation unit, a display unit, a communication unit, and the like, and performs information management such as medical appointment reservation, diagnosis result report, results management, and material inventory management in the radiology department. . The RIS 10 accepts registration of the inspection order by the operator. Then, based on the registered inspection order, inspection order information is generated and transmitted to the modality 20 and the image inspection device 30.

  The examination order information is data indicating the contents of the examination order for imaging and diagnosis, and includes patient information, examination information, and series information.

  The modality 20 is a CR device, a CT device, an MR device, a mammography device, an ultrasonic diagnostic device, or the like. The medical image data signal obtained by photographing according to the operation of the photographing engineer and the examination order information received from the RIS 10 Based on the above, medical image data, which is digital data conforming to the DICOM standard, is generated. The modality 20 transmits the generated medical image data to the imaging device 30. In the present embodiment, the modality 20 will be described as a CT apparatus.

  FIG. 2 shows the data structure of one frame of medical image data (hereinafter referred to as “medical image data frame”). The medical image data frame is composed of image data corresponding to one medical image and accompanying information related to the medical image. The incidental information includes patient information, examination information, series information, and slice position information. Here, the slice position information is information on the slice position by the CT apparatus and MR apparatus. Note that the value of the slice position information of the medical image data frame generated by a device other than the CT device or the MR device is an indefinite value.

  In one series, the modality 20 generates medical image data of several hundred medical images, for example. In other words, the modality 20 generates several hundreds of medical image data frames in one series, and transmits these medical image data frames to the imaging device 30.

  The image inspection apparatus 30 is a medical image processing apparatus for confirming or changing medical image data. The image inspection device 30 receives medical image data from the modality 20. Also, inspection order information is received from the RIS 10.

  When the received medical image data needs to be corrected, the image detection device 30 changes the incidental information or the image data, and transmits the medical image data to the PACS 40. When the received medical image data does not need to be corrected, the image detection device 30 transmits the medical image data to the PACS 40 without changing the incidental information and the image data.

  As a specific example of processing performed by the image inspection device 30, there is automatic series division processing. The series automatic division process will be described later.

  The imaging device 30 can be configured to determine whether or not the received medical image data needs to be modified, and to change the incidental information or the image information based on the examination order information received from the RIS 10 by setting. It has become.

  The PACS 40 is a medical image management apparatus that stores and manages medical image data. In the present embodiment, the PACS 40 will be described as one device. The PACS 40 receives the medical image data from the imaging device 30 and accumulates and stores the medical image data. These medical image data are transmitted to the client device in response to an acquisition request from a client device of the PACS 40 (not shown). Then, the client device displays a medical image and supplementary information based on the received medical image data.

[Functional structure of image inspection device]
FIG. 3 shows a functional configuration of the image inspection device 30. As shown in FIG. 3, the imaging device 30 includes a control unit 31, an operation unit 32, a display unit 33, a communication unit 34, a ROM (Read Only Memory) 35, a temporary memory 36, and the like. 37 is connected.

  The control unit 31 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), and the like. The control unit 31 reads various processing programs stored in the ROM 35, develops them in a work area formed in the RAM, and comprehensively controls each unit of the imaging device 30 according to the program.

  The operation unit 32 includes a keyboard having cursor keys, numeric input keys, various function keys, and the like, and a pointing device such as a mouse, and controls an instruction signal input by key operation or mouse operation on the keyboard. To 31.

  The display unit 33 is configured by an LCD (Liquid Crystal Display), and displays an input instruction, data, and the like from the operation unit 32 in accordance with an instruction of a display signal input from the control unit 31.

  The communication unit 34 includes a LAN (Local Area Network) adapter, a router, a TA (Terminal Adapter), and the like, and transmits and receives data to and from external devices such as the RIS 10, the modality 20, and the PACS 40 connected via the communication network N. I do.

  The ROM 35 is configured by a nonvolatile semiconductor memory or the like, and stores various processing programs executed by the control unit 31, various data, and the like. These various programs are stored in the form of readable program codes, and the control unit 31 sequentially executes operations according to the program codes.

  The temporary memory 36 is a memory for temporarily storing the medical image data frame received from the modality 20.

  The control unit 31 temporarily stores the medical image data frame received from the modality 20 by the communication unit 34 in the temporary memory 36. In this embodiment, several hundreds of medical image data frames are transmitted from the modality 20 per series. The control unit 31 temporarily stores all the medical image data frames in the temporary memory 36.

  The control unit 31 reads the medical image data frame stored in the temporary memory 36, and performs series automatic division processing or the like on the medical image data frame. Then, these medical image data frames are transmitted to the PACS 40.

[Series automatic division processing]
Next, an overview of series automatic division processing will be described. The automatic series division processing is to acquire part specifying information for specifying the imaging part of a patient from a plurality of medical image data frames of the same series received from the modality 20, and based on the part specifying information, the same series The plurality of medical image data frames are divided into groups of different series of medical image data frames.

  For example, a plurality of medical image data frames with a series ID of 1 are assigned to a group of medical image data frames with a series ID of 1 and a medical image data frame with a series ID of 2 based on the acquired part specifying information. Divide into groups.

  A specific example of the series automatic division processing will be described with reference to FIG. Here, for convenience, the number of medical image data frames is limited to six frames, but there are actually several frames to several hundred frames.

  The control unit 31 reads a plurality of medical image data frames D1, D2, D3, D4, D5, and D6 of the same series (whole body series) stored in the temporary memory 36. Here, since the read medical image data frames are of the same series, all the series ID values of the series information included in the incidental information are “1”.

  The slice position information of the medical image data frames D1, D2, D3, D4, D5, and D6 is “10 cm”, “15 cm”, “20 cm”, “25 cm”, “30 cm”, and “35 cm”, respectively.

  The control unit 31 reads (acquires) slice position information included in the accompanying information of each medical image data frame. Here, the slice position information is part specifying information for specifying the imaging part of the patient. Then, the control unit 31 determines whether the read slice position information is larger than the set value or less than the set value. In the present embodiment, it is assumed that the set value is “23 cm”. This set value is set in advance by a user operation or the like.

  The control unit 31 changes the value of the series ID when the slice position information is larger than the set value, and does not change the value of the series ID when the slice position information is equal to or smaller than the set value.

  That is, since the value of the slice position information of the medical image data frames D1, D2, and D3 is “23 cm” or less, the value of the series ID remains “1”. On the other hand, since the set value of the slice position information of the medical image data frames D4, D5, and D6 is larger than “23 cm”, the series ID value is changed from “1” to “2”.

  In this way, the control unit 31 converts the medical image data frames D1 to D6 whose series ID is “1” into groups (chest series) and series of medical image data D1 to D3 whose series ID is “1”. The medical image data D4 to D6 with ID “2” is divided into groups (abdominal series).

  Then, the control unit 31 transmits these medical image data frames D1 to D6 to the PACS 40 via the communication unit 34.

[Specific operation of image inspection device]
Next, the operation in the image inspection device 30 will be described. FIG. 5 is a flowchart showing automatic series division processing executed in the image inspection device 30.

  The image inspection apparatus 30 receives a plurality of medical image data frames of the same series from the modality 20 (step S1).

  The image inspection apparatus 30 sets the medical image data frame having the earliest reception time among the received medical image data frames as a processing target (analysis target) (step S2).

  Next, the imaging device 30 extracts (acquires) slice position information of the medical image data frame that is the processing target (step S3). Then, the value of the extracted slice position information is compared with the set value (step S4). If the value of the slice position information is larger as a result of the comparison (step S4; Yes), the series information of the incidental information of the medical image data frame to be processed is changed (step S5). In the example of FIG. 4, the series ID is changed from “1” to “2”.

  Then, the image inspection device 30 determines whether there is a medical image data frame to be processed next (step S6). Here, the medical image data frame to be processed next is the frame having the earliest reception time next to the medical image data frame currently processed.

  If the value of the slice position information is equal to or smaller than the set value as a result of the comparison in step S4 (step S4; No), it is determined whether there is a medical image data frame to be processed next without changing the series information (step S6).

  As a result of the determination, if there is no next medical image data frame (step S6; No), the imaging apparatus 30 ends the series automatic division processing and transmits the medical image data frame group to be processed to the PACS 40.

  As a result of the determination, if there is a next medical image data frame (step S6; Yes), the imaging apparatus 30 sets the next medical image data frame as a processing target (step S2) and continues the automatic series division processing.

  As described above, according to the first embodiment, the imaging apparatus 30 acquires slice position information (part specifying information) from a plurality of medical image data frames received from the modality 20. When the slice position information is larger than the set value, the series information of the corresponding medical image data frame is changed.

  Therefore, the modality 20 sets the setting value to the slice position that becomes the boundary between the chest and the abdomen, so that the medical image data frame related to the medical image of the chest and the medical image related to the medical image of the abdomen even when the whole body is captured. The image data frame can be a different series. Therefore, it is possible to eliminate the burden on the user such as an interpreting doctor due to the division work of the series.

  When the control unit 31 reads a medical image data frame to be subject to automatic series division processing from the temporary memory 36, the control unit 31 refers to the modality type information included in the series information of the medical image data frame, and the type is determined as CT. Only a frame that is a device or an MR device may be configured as a processing target of the series automatic division processing.

  As a result, the series automatic division processing performed by the image detection device 30 is performed only on the medical image data frame including the image data of the slice image generated by the CT device or the MR device.

[Second Embodiment]
Hereinafter, a second embodiment of the present invention will be described in detail with reference to FIGS. 1 to 3, 6 and 7. In this description, parts different from the first embodiment will be described.

[Series automatic division processing]
The series automatic division processing in the second embodiment will be described with reference to FIG.

  The control unit 31 reads a plurality of medical image data frames D101 to D199 of the same series stored in the temporary memory 36. The series ID values of the series information included in the incidental information of these medical image data frames D101 to D199 are all “1” (whole body series). Each medical image data frame corresponds to image data of slice images from the upper part of the body to the lower part of the body in the order of medical image data frames D101 to D199.

  Then, the control unit 31 performs image analysis of the image data of each medical image data frame, and specifies a part of the image data based on the image signal distribution information (histogram) of the image data. That is, the histogram of the image data becomes the part specifying information.

  Specifically, the control unit 31 performs histogram analysis, which is statistical analysis, on the image data of each medical image data frame to generate a histogram. Here, one histogram corresponds to image data of one medical image data frame.

  In this histogram, the horizontal axis represents the image signal level (corresponding to density and radiation transmittance), and the vertical axis represents the frequency corresponding to the signal level. The ROM 35 also stores a histogram pattern (hereinafter referred to as a “boundary histogram pattern”) that serves as a boundary between the “chest” and the “abdomen”.

  The control unit 31 reads the boundary histogram pattern from the ROM 35. Then, the control unit 31 compares this boundary histogram pattern with a histogram pattern generated based on the image data of the medical image data frame.

  Here, the control unit 31 compares the histogram corresponding to the medical image data frame D101 with the boundary histogram pattern in order from the histogram corresponding to the medical image data frame D199.

  As a result of the comparison, when the generated histogram pattern matches the boundary histogram pattern, the series ID of the medical image data frame corresponding to the matched histogram is changed. For subsequent medical image data frames, histogram comparison is not performed, and the series IDs of medical image data frames that are not compared are changed.

  That is, when the histogram pattern corresponding to the medical image data frame D150 matches the boundary histogram pattern, the control unit 31 does not change the series ID of the medical image data frames of the medical image data frames D101 to D149. That is, the series ID remains “1” (chest series).

  Then, the control unit 31 changes the series ID of the medical image data frames of the medical image data frames D150 to D199 to “2” (abdominal series). Here, the control unit 31 performs a data copy of the medical image data frame D150, and generates a medical image data frame D150 with a series ID “1” in addition to the medical image data frame D150 with a series ID “2”.

  Note that a known comparison method is adopted for the comparison of the histogram patterns, and the matching of the histogram patterns is not limited to perfect matching.

[Specific operation of image inspection device]
Next, the operation in the image inspection device 30 will be described. FIG. 7 is a flowchart showing automatic series division processing executed in the image inspection device 30.

  The image inspection apparatus 30 receives a plurality of medical image data frames of the same series from the modality 20 (step S101).

  Then, the image inspection apparatus 30 performs a histogram analysis on the received image data of each medical image data frame to generate a histogram (step S102).

  Then, the image inspection device 30 reads the boundary histogram pattern from the ROM 35 (step S103).

  The image inspection apparatus 30 sets the medical image data frame having the earliest reception time among the received medical image data frames as a processing target (analysis target) (step S104).

  Next, the imaging device 30 compares the histogram pattern corresponding to the medical image data frame to be processed with the boundary histogram pattern (step S105). As a result of the comparison, when the histogram shapes (patterns) do not match (step S106; No), the imaging apparatus 30 determines whether there is a medical image data frame to be processed next (step S107). Here, the medical image data frame to be processed next is the frame having the earliest reception time next to the medical image data frame currently processed.

  As a result of the determination, if there is no next medical image data frame (step S107; No), the image inspection apparatus 30 ends the series automatic division processing and transmits the medical image data frame group to be processed to the PACS 40.

  As a result of the determination, if there is a next medical image data frame (step S107; Yes), the imaging apparatus 30 sets the next medical image data frame as a processing target (step S104) and continues the automatic series division processing.

  As a result of the comparison in step S105, when the histogram shapes match (step S106; Yes), the series information of the incidental information of the medical image data frame to be processed is changed (step S108). In the example of FIG. 6, the series ID is changed from “1” to “2”.

  Here, the imaging device 30 performs data copy of the medical image data frame whose histogram shapes match, and returns the series information of the medical image data frame generated by the data copy to the value before the change.

  Then, the image inspection apparatus 30 determines whether there is a medical image data frame to be processed next (step S109). As a result of the determination, if there is no next medical image data frame (step S109; No), the image inspection device 30 ends the series division process and transmits the medical image data frame group to be processed to the PACS 40.

  As a result of the determination, if there is a next medical image data frame (step S109; Yes), the next medical image data frame is set as a processing target (step S110), and a series of incidental information of the medical image data frame that is the processing target. Information is changed (step S108). Then, the image inspection apparatus 30 determines whether there is a medical image data frame to be processed next (step S109).

  As described above, according to the second embodiment, the imaging device 30 performs histogram analysis on the image data of each medical image data frame received from the modality 20 to generate a histogram. Then, each of the histograms and the boundary histogram pattern are compared, and a medical image data frame including image data that is a boundary between the images of the “chest” and the “abdomen” is specified. Then, the series information of the medical image data frame to be processed is changed after the medical image data frame.

  Therefore, in the modality 20, even when the whole body is photographed collectively, the medical image data frame related to the chest medical image and the medical image data frame related to the abdominal medical image can be made into different series. Therefore, it is possible to eliminate the burden on the user such as an interpreting doctor due to the division work of the series.

  In the second embodiment, in the automatic series dividing process, it is determined whether the image data of the medical image data frame is the “chest” image or the “abdominal” image based on the boundary histogram pattern. However, the determination method is not limited to this. For example, the following determination method may be used.

  The ROM 35 stores a histogram pattern (chest histogram pattern) based on typical “chest” image data and a histogram pattern (abdominal histogram pattern) based on typical “abdominal” image data.

  The control unit 31 compares the histogram pattern and the chest histogram pattern of the medical image data frame to be processed, and the histogram pattern and the abdominal histogram pattern of the medical image data frame to be processed. Then, the control unit 31 determines whether the histogram pattern of the medical image data frame to be processed is similar in shape to the abdominal histogram pattern or the chest histogram pattern.

  When the control unit 31 determines that the histogram pattern of the medical image data frame to be processed is similar to the chest histogram pattern, the series information of the medical image data frame to be processed is not changed.

  When the control unit 31 determines that the histogram pattern of the medical image data frame to be processed is similar to the abdominal histogram pattern, the series information of the medical image data frame to be processed is changed.

  As a result, the medical image data frame whose series information is not changed becomes the chest series, and the medical image data frame whose series information is not changed becomes the abdominal series.

  In the second embodiment, the histogram of the image data is used as the part specifying information, but the profile of the image data may be used as the part specifying information.

  Here, the profile represents a change in a pixel value on an arbitrary line segment of the image by taking a position on the line segment on the horizontal axis and a pixel value on the vertical axis.

  In this case, the control unit 31 generates a profile on a predetermined line segment based on the image data of each medical image data frame. Here, one profile corresponds to image data of one medical image data frame.

  Further, the ROM 35 stores a profile pattern (boundary profile pattern) on a predetermined line segment that is a boundary between the “chest” and the “abdomen”.

  The control unit 31 reads the boundary profile pattern from the ROM 35. Then, the control unit 31 compares the boundary profile pattern with a profile generated based on the image data of the medical image data frame.

[Modification 1]
In addition, the configuration of the medical image system 100 in the above-described embodiment may be configured by adding the distribution server 50, and the PACS 40 may have the function of the series automatic division processing performed by the imaging device 30.

  A specific example will be described with reference to FIG. As shown in FIG. 8, the medical image system 100 is configured such that the RIS 10, the modality 20, the imaging device 30, the PACS 40, and the distribution server 50 are connected via a communication network N, and each can perform data communication. Has been.

  The distribution server 50 is a device that distributes medical image data to an electronic medical chart terminal or the like having an electronic medical chart function (not shown). Upon receiving a medical image browsing request from an electronic medical record terminal or the like, the distribution server 50 transmits a medical image data acquisition request to the PACS 40. The PACS 40 transmits medical image data to the distribution server 50 in response to this acquisition request. The distribution server 50 distributes the acquired medical image data to an electronic medical record terminal or the like.

  When the PACS 40 transmits medical image data to the distribution server 50, based on the slice position information included in the supplementary information of the medical image data, the PACS 40 converts a plurality of medical image data frames of the same series into the medical image data frames of another series. Divide into groups. Then, these medical image data frames are transmitted to the distribution server 50.

[Modification 2]
In the above-described embodiment, in the automatic series division processing, the imaging apparatus 30 uses two groups of medical image data frames with different series information from a group of medical image data frames with the same series information (whole body series). Although the series is divided into (chest series and abdominal series), the series may be divided into three or more groups having different series information.

[Modification 3]
In the first embodiment, the imaging apparatus 30 performs the automatic series division process based on the slice position information, and in the second embodiment based on the histogram or profile. The series automatic division processing may be performed.

  For example, the imaging device 30 first performs rough part prediction of the image data of the medical image data frame based on the slice position information, and then determines the part of the image data of the medical image data frame based on the histogram. Identify and split the series.

1 is a system configuration diagram of a medical image system. It is a data block diagram of a medical image data frame. It is a block diagram of an image inspection apparatus. It is a data image figure of isolation | separation into another series based on slice position information. 5 is a flowchart of processing executed by the image inspection device in the first embodiment. It is a data image figure of isolation | separation into another series based on a histogram. It is a flowchart of the process which an image inspection apparatus performs in 2nd Embodiment. 1 is a system configuration diagram of a medical image system including a distribution server.

Explanation of symbols

10 RIS
20 modality 30 imaging device 31 control unit 32 operation unit 33 display unit 34 communication unit 35 ROM
36 Temporary memory 37 Bus 40 PACS
50 Distribution Server 100 Medical Image System N Communication Network

Claims (7)

Of the plurality of medical image data frames having image data of medical images and supplementary information related to the medical image including series information, the imaging region of the patient is specified from each medical image data frame having the same series information. Obtaining means for obtaining the part specifying information;
Based on the part specifying information acquired by the acquisition means, changing means for changing the series information of each medical image data frame having the same series information;
A medical image processing apparatus comprising: The changing means is
Based on the part specifying information acquired by the acquisition unit, the series information of each medical image data frame having the same series information is changed to series information corresponding to each part.
The medical image processing apparatus according to claim 1. The part specifying information is included in the incidental information.
The medical image processing apparatus according to claim 1 or 2. Generating means for analyzing the image data and generating image signal distribution information;
Further comprising
The part specifying information is the image signal distribution information.
The medical image processing apparatus according to claim 1 or 2. Generating means for analyzing the image data and generating a profile;
Further comprising
The part specifying information is the profile.
The medical image processing apparatus according to claim 1 or 2. Of the plurality of medical image data frames having image data of medical images and supplementary information related to the medical image including series information, the imaging region of the patient is specified from each medical image data frame having the same series information. An acquisition step of acquiring the part specifying information;
Based on the part specifying information acquired in the acquisition step, a change step of changing the series information of each medical image data frame in which the series information is the same,
A medical image processing method. Computer
Of the plurality of medical image data frames having image data of medical images and supplementary information related to the medical image including series information, the imaging region of the patient is specified from each medical image data frame having the same series information. Acquisition means for acquiring the part specifying information of
Changing means for changing the series information of each medical image data frame having the same series information based on the part specifying information acquired by the acquiring means;
Program to function as.

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