JP2017202307A - Medical imaging diagnostic apparatus and medical information management apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the reproductivity of imaging.SOLUTION: An X-ray CT apparatus according to an embodiment includes a receiving unit and a setting unit. The receiving unit receives an operation to change information relating to a range of a part that is defined on the basis of a plurality of anatomical feature points in any one of image data of a subject and image data of a virtual patient image. The setting unit performs any one of first setting processing and second setting processing. The first setting processing changes a part of the plurality of anatomical feature points to define the range of the part, and the second setting processing sets, for a part of the plurality of anatomical feature points, a position departed therefrom by a predetermined length in a predetermine direction as an actual anatomical feature point.SELECTED DRAWING: Figure 2

Description

  Embodiments described herein relate generally to a medical image diagnostic apparatus and a medical information management apparatus.

  Conventionally, in imaging using an X-ray CT (Computed Tomography) apparatus, positioning imaging for collecting positioning images (scano images) is performed before the main imaging. In the X-ray CT apparatus, an imaging range is set on the positioning image, and various imaging conditions are input. These operations are performed manually by the operator.

JP 2007-181623 A JP 2008-012229 A Japanese Patent No. 5455903

  The problem to be solved by the present invention is to provide a medical image diagnostic apparatus and a medical information management apparatus capable of improving the reproducibility of imaging.

  The X-ray CT apparatus according to the embodiment includes a reception unit and a setting unit. The accepting unit accepts an operation for changing information related to a region range defined based on a plurality of anatomical feature points in the image data of the subject or the image data of the virtual patient image. The setting unit is configured to change a part of a plurality of anatomical feature points for defining the range of the part based on information on the range of the part after the change, or the plurality of the plurality of anatomical feature points A second setting process is performed in which a position separated by a predetermined length in a predetermined direction with respect to a part of the anatomical characteristic points is set as a substantial anatomical characteristic point.

FIG. 1 is a diagram illustrating an example of a configuration of a medical information processing system according to the first embodiment. FIG. 2 is a diagram illustrating an example of the configuration of the X-ray CT apparatus according to the first embodiment. FIG. 3 is a view for explaining three-dimensional scano image capturing by the scan control circuit according to the first embodiment. FIG. 4A is a diagram for explaining an example of a part detection process by the detection function according to the first embodiment. FIG. 4B is a diagram for explaining an example of a part detection process by the detection function according to the first embodiment. FIG. 5 is a diagram for explaining an example of a part detection process by the detection function according to the first embodiment. FIG. 6 is a diagram for explaining an example of a part detection process by the detection function according to the first embodiment. FIG. 7 is a diagram illustrating an example of a virtual patient image stored by the storage circuit according to the first embodiment. FIG. 8 is a diagram for explaining an example of collation processing by the position collation function according to the first embodiment. FIG. 9 is a diagram illustrating a scan range conversion example by coordinate conversion according to the first embodiment. FIG. 10 is a diagram illustrating an example of scan range information for each shooting plan stored in the storage circuit according to the first embodiment. FIG. 11 is a diagram for explaining the storage function process according to the first embodiment. FIG. 12 is a diagram for explaining the storage function process according to the first embodiment. FIG. 13 is a diagram for explaining the storage function processing according to the first embodiment. FIG. 14 is a diagram for explaining processing of the update function according to the first embodiment. FIG. 15 is a diagram for explaining processing of the update function according to the first embodiment. FIG. 16 is a flowchart illustrating a processing procedure performed by the X-ray CT apparatus according to the first embodiment. FIG. 17 is a flowchart illustrating a processing procedure performed by the X-ray CT apparatus according to the first embodiment. FIG. 18 is a flowchart illustrating a processing procedure performed by the X-ray CT apparatus according to the second embodiment. FIG. 19 is a diagram for explaining processing of the update function according to the second embodiment. FIG. 20 is a diagram for explaining the storage function processing according to the third embodiment. FIG. 21 is a diagram illustrating an example of a configuration of a medical information management apparatus according to another embodiment.

  Embodiments of an X-ray CT (Computed Tomography) apparatus will be described below in detail with reference to the accompanying drawings. Hereinafter, a medical information processing system including an X-ray CT apparatus will be described as an example. In the medical information processing system 100 shown in FIG. 1, only one server device and one terminal device are shown, but actually, a plurality of server devices and terminal devices can be included. The medical information processing system 100 can also include a medical image diagnostic apparatus such as an X-ray diagnostic apparatus, an MRI (Magnetic Resonance Imaging) apparatus, or an ultrasonic diagnostic apparatus.

(First embodiment)
FIG. 1 is a diagram illustrating an example of a configuration of a medical information processing system 100 according to the first embodiment. As illustrated in FIG. 1, the medical information processing system 100 according to the first embodiment includes an X-ray CT apparatus 1, a server apparatus 2, and a terminal apparatus 3. The X-ray CT apparatus 1, the server apparatus 2, and the terminal apparatus 3 are in a state in which they can communicate with each other directly or indirectly through, for example, a hospital LAN (Local Area Network) 4 installed in a hospital. It has become. For example, when a PACS (Picture Archiving and Communication System) is introduced in the medical information processing system 100, each device transmits and receives medical images and the like according to the DICOM (Digital Imaging and Communications in Medicine) standard.

Further, in the medical information processing system 100, for example, HIS (Hospital Information System), RIS (Radiology Information System), etc. are introduced to manage various information. For example, the terminal device 3 transmits an inspection order created along the above-described system to the X-ray CT apparatus 1 or the server apparatus 2. The X-ray CT apparatus 1 acquires patient information from an examination order received directly from the terminal apparatus 3 or a patient list (modality work list) for each modality created by the server apparatus 2 that has received the examination order.
X-ray CT image data for each patient is collected. Then, the X-ray CT apparatus 1 transmits the collected X-ray CT image data and image data generated by performing various image processing on the X-ray CT image data to the server apparatus 2. The server apparatus 2 stores the X-ray CT image data and image data received from the X-ray CT apparatus 1, generates image data from the X-ray CT image data, and responds to an acquisition request from the terminal apparatus 3. Data is transmitted to the terminal device 3. The terminal device 3 displays the image data received from the server device 2 on a monitor or the like. Hereinafter, each device will be described.

  The terminal device 3 is a device that is arranged in each department in the hospital and is operated by a doctor who works in each department, such as a PC (Personal Computer), a tablet PC, a PDA (Personal Digital Assistant), a mobile phone, etc. It is. For example, in the terminal device 3, medical record information such as a patient's symptom and a doctor's findings is input by a doctor. Further, the terminal device 3 receives an inspection order for ordering an inspection by the X-ray CT apparatus 1, and transmits the input inspection order to the X-ray CT apparatus 1 and the server apparatus 2. That is, the doctor in the medical department operates the terminal device 3 to read the reception information of the patient who has visited the hospital and information on the electronic medical record, examines the corresponding patient, and inputs the medical record information to the read electronic medical record. Then, a doctor in the medical department operates the terminal device 3 to transmit an examination order according to whether or not the examination by the X-ray CT apparatus 1 is necessary.

  The server apparatus 2 stores medical images (for example, X-ray CT image data and image data collected by the X-ray CT apparatus 1) collected by the medical image diagnostic apparatus, and performs various image processing on the medical images. For example, a PACS server or the like. For example, the server device 2 receives a plurality of examination orders from the terminal device 3 arranged in each medical department, creates a patient list for each medical image diagnostic device, and uses the created patient list as each medical image diagnostic device. Send to. For example, the server apparatus 2 receives an examination order for performing an examination by the X-ray CT apparatus 1 from the terminal apparatus 3 of each clinical department, creates a patient list, and creates the created patient list as an X-ray. Transmit to the CT apparatus 1. And the server apparatus 2 memorize | stores the X-ray CT image data and image data which were collected by the X-ray CT apparatus 1, and according to the acquisition request from the terminal device 3, X-ray CT image data and image data are stored in the terminal apparatus. 3 to send.

  The X-ray CT apparatus 1 collects X-ray CT image data for each patient and uses the collected X-ray CT image data and image data generated by performing various image processing on the X-ray CT image data as a server. Transmit to device 2. FIG. 2 is a diagram illustrating an example of the configuration of the X-ray CT apparatus 1 according to the first embodiment. As shown in FIG. 2, the X-ray CT apparatus 1 according to the first embodiment includes a gantry 10, a bed apparatus 20, and a console 30.

The gantry 10 is a device that irradiates the subject P (patient) with X-rays, detects the X-rays transmitted through the subject P, and outputs them to the console 30. The gantry 10 and the X-ray irradiation control circuit 11 generate X-rays. The apparatus 12 includes a detector 13, a data acquisition circuit (DAS) 14, a rotating frame 15, and a gantry drive circuit 16.

  The rotating frame 15 supports the X-ray generator 12 and the detector 13 so as to face each other with the subject P interposed therebetween, and is rotated at a high speed in a circular orbit around the subject P by a gantry driving circuit 16 described later. An annular frame.

  The X-ray irradiation control circuit 11 is a device that supplies a high voltage to the X-ray tube 12 a as a high voltage generator, and the X-ray tube 12 a uses the high voltage supplied from the X-ray irradiation control circuit 11 to Generate a line. The X-ray irradiation control circuit 11 adjusts the X-ray dose irradiated to the subject P by adjusting the tube voltage and tube current supplied to the X-ray tube 12a under the control of the scan control circuit 33 described later. .

  The X-ray irradiation control circuit 11 switches the wedge 12b. The X-ray irradiation control circuit 11 adjusts the X-ray irradiation range (fan angle and cone angle) by adjusting the aperture of the collimator 12c. In addition, this embodiment may be a case where an operator manually switches a plurality of types of wedges.

  The X-ray generator 12 is an apparatus that generates X-rays and irradiates the subject P with the generated X-rays, and includes an X-ray tube 12a, a wedge 12b, and a collimator 12c.

  The X-ray tube 12 a is a vacuum tube that irradiates the subject P with an X-ray beam with a high voltage supplied by a high voltage generator (not shown). The X-ray beam is applied to the subject P as the rotating frame 15 rotates. Irradiate. The X-ray tube 12a generates an X-ray beam that spreads with a fan angle and a cone angle. For example, under the control of the X-ray irradiation control circuit 11, the X-ray tube 12 a continuously exposes X-rays around the subject P for full reconstruction or exposure that can be reconfigured for half reconstruction. It is possible to continuously expose X-rays in the irradiation range (180 degrees + fan angle). Further, the X-ray irradiation control circuit 11 can control the X-ray tube 12a to intermittently emit X-rays (pulse X-rays) at a preset position (tube position). The X-ray irradiation control circuit 11 can also modulate the intensity of the X-rays emitted from the X-ray tube 12a. For example, the X-ray irradiation control circuit 11 increases the intensity of X-rays emitted from the X-ray tube 12a at a specific tube position, and exposes from the X-ray tube 12a at a range other than the specific tube position. Reduce the intensity of the emitted X-rays.

  The wedge 12b is an X-ray filter for adjusting the X-ray dose of X-rays emitted from the X-ray tube 12a. Specifically, the wedge 12b transmits the X-rays exposed from the X-ray tube 12a so that the X-rays irradiated from the X-ray tube 12a to the subject P have a predetermined distribution. Attenuating filter. For example, the wedge 12b is a filter obtained by processing aluminum so as to have a predetermined target angle or a predetermined thickness. The wedge 12b is also called a wedge filter or a bow-tie filter.

  The collimator 12 c is a slit for narrowing the X-ray irradiation range in which the X-ray dose is adjusted by the wedge 12 b under the control of the X-ray irradiation control circuit 11.

  The gantry driving circuit 16 rotates the rotary frame 15 to rotate the X-ray generator 12 and the detector 13 on a circular orbit around the subject P.

  The detector 13 is a two-dimensional array type detector (surface detector) that detects X-rays transmitted through the subject P, and a detection element array formed by arranging X-ray detection elements for a plurality of channels is the subject P. A plurality of rows are arranged along the body axis direction (Z-axis direction shown in FIG. 2). Specifically, the detector 13 in the first embodiment includes X-ray detection elements arranged in multiple rows such as 320 rows along the body axis direction of the subject P. For example, the lungs of the subject P It is possible to detect X-rays transmitted through the subject P over a wide range, such as a range including the heart and the heart.

The data collection circuit 14 is a DAS, and collects projection data from the X-ray detection data detected by the detector 13. For example, the data collection circuit 14 generates projection data by performing amplification processing, A / D conversion processing, inter-channel sensitivity correction processing, and the like on the X-ray intensity distribution data detected by the detector 13. The projected data is transmitted to the console 30 described later. For example, when X-rays are continuously emitted from the X-ray tube 12a while the rotary frame 15 is rotating, the data acquisition circuit 14 collects projection data groups for the entire circumference (for 360 degrees). Further, the data collection circuit 14 associates the tube position with each collected projection data and transmits it to the console 30 described later. The tube position is information indicating the projection direction of the projection data. Note that the sensitivity correction processing between channels may be performed by the preprocessing circuit 34 described later.

  The couch device 20 is a device on which the subject P is placed, and includes a couch driving device 21 and a top plate 22 as shown in FIG. The couch driving device 21 moves the subject P into the rotary frame 15 by moving the couchtop 22 in the Z-axis direction. The top plate 22 is a plate on which the subject P is placed.

  For example, the gantry 10 executes a helical scan that rotates the rotating frame 15 while moving the top plate 22 to scan the subject P in a spiral shape. Alternatively, the gantry 10 performs a conventional scan in which the subject P is scanned in a circular orbit by rotating the rotating frame 15 while the position of the subject P is fixed after the top plate 22 is moved. Alternatively, the gantry 10 performs a step-and-shoot method in which the position of the top plate 22 is moved at regular intervals and a conventional scan is performed in a plurality of scan areas.

  The console 30 is a device that accepts an operation of the X-ray CT apparatus 1 by an operator and reconstructs X-ray CT image data using projection data collected by the gantry 10. As shown in FIG. 2, the console 30 includes an input circuit 31, a display 32, a scan control circuit 33, a preprocessing circuit 34, a storage circuit 35, an image reconstruction circuit 36, and a processing circuit 37. .

  The input circuit 31 includes a mouse, a keyboard, a trackball, a switch, a button, a joystick, and the like that are used by the operator of the X-ray CT apparatus 1 to input various instructions and settings, and instructions and settings information received from the operator. Is transferred to the processing circuit 37. For example, the input circuit 31 receives imaging conditions for X-ray CT image data, reconstruction conditions for reconstructing X-ray CT image data, image processing conditions for X-ray CT image data, and the like from the operator. The input circuit 31 receives an operation for selecting an examination for the subject. Further, the input circuit 31 accepts a designation operation for designating a part on the image.

The display 32 is a monitor that is referred to by the operator, and displays image data generated from the X-ray CT image data to the operator under the control of the processing circuit 37, or the operator via the input circuit 31. GUI (Graphical) to accept various instructions and settings from
(User Interface). The display 32 displays a plan screen for a scan plan, a screen being scanned, and the like. Further, the display 32 displays a virtual patient image, image data, and the like including exposure information. The virtual patient image displayed on the display 32 will be described in detail later.

  The scan control circuit 33 controls the operations of the X-ray irradiation control circuit 11, the gantry driving circuit 16, the data acquisition circuit 14, and the bed driving device 21 under the control of the processing circuit 37, thereby Control the collection process. Specifically, the scan control circuit 33 controls projection data collection processing in positioning imaging for collecting positioning images (scano images) and main imaging (main scanning) for collecting images used for diagnosis. Here, in the X-ray CT apparatus 1 according to the first embodiment, a two-dimensional scanogram and a three-dimensional scanogram can be taken.

  For example, the scan control circuit 33 fixes the X-ray tube 12a at a position of 0 degree (a position in the front direction with respect to the subject) and continuously performs imaging while moving the top plate at a constant speed. Take a three-dimensional scano image. Alternatively, the scan control circuit 33 fixes the X-ray tube 12a at a 0 degree position, and intermittently repeats imaging while synchronizing the top plate movement while intermittently moving the top plate. Take a scanogram. Here, the scan control circuit 33 can capture a positioning image not only from the front direction but also from an arbitrary direction (for example, a side surface direction) with respect to the subject.

  The scan control circuit 33 captures a three-dimensional scanogram by collecting projection data for the entire circumference of the subject in the scanogram image capture. FIG. 3 is a view for explaining three-dimensional scano image shooting by the scan control circuit 33 according to the first embodiment. For example, as shown in FIG. 3, the scan control circuit 33 collects projection data for the entire circumference of the subject by a helical scan or a non-helical scan. Here, the scan control circuit 33 executes a helical scan or a non-helical scan with a lower dose than the main imaging over a wide range such as the entire chest, abdomen, the entire upper body, and the whole body of the subject. As the non-helical scan, for example, the above-described step-and-shoot scan is executed.

  As described above, the scan control circuit 33 collects projection data for the entire circumference of the subject, so that an image reconstruction circuit 36 described later reconstructs three-dimensional X-ray CT image data (volume data). As shown in FIG. 3, a positioning image can be generated from an arbitrary direction using the reconstructed volume data. Here, whether the positioning image is photographed two-dimensionally or three-dimensionally may be set arbitrarily by the operator, or may be preset according to the examination contents.

  Returning to FIG. 2, the preprocessing circuit 34 performs logarithmic conversion processing and correction processing such as offset correction, sensitivity correction, and beam hardening correction on the projection data generated by the data acquisition circuit 14. Generate corrected projection data. Specifically, the preprocessing circuit 34 generates corrected projection data for each of the projection data of the positioning image generated by the data acquisition circuit 14 and the projection data acquired by the main photographing, and the storage circuit 35. To store.

  The storage circuit 35 stores the projection data generated by the preprocessing circuit 34. Specifically, the storage circuit 35 stores the projection data of the positioning image generated by the preprocessing circuit 34 and the diagnostic projection data collected by the main imaging. The storage circuit 35 stores image data and a virtual patient image generated by an image reconstruction circuit 36 described later. Further, the storage circuit 35 appropriately stores a processing result by a processing circuit 37 described later. The virtual patient image and the processing result by the processing circuit 37 will be described later.

  The image reconstruction circuit 36 reconstructs X-ray CT image data using the projection data stored in the storage circuit 35. Specifically, the image reconstruction circuit 36 reconstructs X-ray CT image data from the projection data of the positioning image and the projection data of the image used for diagnosis. Here, as the reconstruction method, there are various methods, for example, back projection processing. Further, as the back projection process, for example, a back projection process by an FBP (Filtered Back Projection) method can be cited. Alternatively, the image reconstruction circuit 36 can reconstruct the X-ray CT image data using a successive approximation method. The image reconstruction circuit 36 is an example of an image reconstruction unit.

  Further, the image reconstruction circuit 36 generates image data by performing various image processing on the X-ray CT image data. Then, the image reconstruction circuit 36 stores the reconstructed X-ray CT image data and image data generated by various image processes in the storage circuit 35.

The processing circuit 37 performs overall control of the X-ray CT apparatus 1 by controlling operations of the gantry 10, the couch device 20, and the console 30. Specifically, the processing circuit 37 controls the CT scan performed on the gantry 10 by controlling the scan control circuit 33. The processing circuit 37 controls the image reconstruction circuit 36 and the image generation process in the console 30 by controlling the image reconstruction circuit 36. In addition, the processing circuit 37 controls the display 32 to display various image data stored in the storage circuit 35.

  Further, as shown in FIG. 2, the processing circuit 37 executes a detection function 37a, a position matching function 37b, a storage function 37c, and an update function 37d. Here, for example, each processing function executed by the detection function 37a, the position matching function 37b, the storage function 37c, and the update function 37d, which are components of the processing circuit 37 shown in FIG. 2, is in the form of a program that can be executed by a computer. Is recorded in the memory circuit 35. The processing circuit 37 is a processor that implements a function corresponding to each program by reading each program from the storage circuit 35 and executing the program. In other words, the processing circuit 37 in a state where each program is read has each function shown in the processing circuit 37 of FIG. The processing circuit 37 is an example of a control unit. The detection function 37a is an example of a detection unit.

  The detection function 37a detects a plurality of parts in the subject included in the three-dimensional image data. Specifically, the detection function 37 a detects a part such as an organ included in the three-dimensional X-ray CT image data (volume data) reconstructed by the image reconstruction circuit 36. For example, the detection function 37a detects a site such as an organ based on anatomical landmarks in at least one of the volume data of the positioning image and the volume data of the image used for diagnosis. Here, the anatomical feature point is a point indicating a feature of a part such as a specific bone, organ, blood vessel, nerve, or lumen. That is, the detection function 37a detects bones, organs, blood vessels, nerves, lumens, and the like included in the volume data by detecting anatomical feature points such as specific organs and bones. The detection function 37a can also detect positions of the head, neck, chest, abdomen, feet, etc. included in the volume data by detecting characteristic feature points of the human body. In addition, the site | part demonstrated by this embodiment means what included these positions in bones, organs, blood vessels, nerves, lumens, and the like. Hereinafter, an example of detection of a part by the detection function 37a will be described.

  For example, the detection function 37a extracts anatomical feature points from the voxel values included in the volume data in the volume data of the positioning image or the volume data of the image used for diagnosis. Then, the detection function 61 compares the three-dimensional position of the anatomical feature point in the information such as the textbook with the position of the feature point extracted from the volume data, thereby detecting the feature point extracted from the volume data. The inaccurate feature points are removed from the inside, and the positions of the feature points extracted from the volume data are optimized. Thereby, the detection function 61 detects each part of the subject included in the volume data. For example, the detection function 37a first extracts anatomical feature points included in the volume data using a supervised machine learning algorithm. Here, the above-described supervised machine learning algorithm is constructed using a plurality of supervised images in which correct anatomical feature points are manually arranged. For example, a decision forest is used. Is done.

  Then, the detection function 37a optimizes the extracted feature points by comparing a model indicating the three-dimensional positional relationship of anatomical feature points in the body with the extracted feature points. Here, the above-described model is constructed using the above-described teacher image, and for example, a point distribution model is used. That is, the detection function 37a includes a model in which the shape and positional relationship of the part, points unique to the part, etc. are defined based on a plurality of teacher images in which correct anatomical feature points are manually arranged, and the extracted features. By comparing the points, the inaccurate feature points are removed and the feature points are optimized.

Hereinafter, an example of the part detection process by the detection function 37a will be described with reference to FIGS. 4A, 4B, 5 and 6. FIG. 4A, 4B, 5 and 6 are diagrams for explaining an example of a part detection process by the detection function 37a according to the first embodiment. 4A and 4B, feature points are arranged two-dimensionally. Actually, feature points are arranged three-dimensionally. For example, the detection function 37a extracts voxels regarded as anatomical feature points (black dots in the figure) by applying a supervised machine learning algorithm to the volume data as shown in FIG. 4A. Then, the detection function 37a fits the position of the extracted voxel to a model in which the shape and positional relationship of the part, a point unique to the part, etc. are defined, as shown in FIG. Incorrect feature points are removed, and only voxels corresponding to more accurate feature points are extracted.

  Here, the detection function 37a gives an identification code for identifying the feature point indicating the feature of each part to the extracted feature point (voxel), and the identification code and position (coordinate) information of each feature point Is associated with the image data and stored in the storage circuit 35. For example, as shown in FIG. 4B, the detection function 37a gives identification codes such as C1, C2, and C3 to the extracted feature points (voxels). Here, the detection function 61 attaches an identification code to each data subjected to the detection process, and stores it in the storage circuit 35. Specifically, the detection function 61 is obtained from at least one projection data among the projection data of the positioning image, the projection data collected under non-contrast, and the projection data collected in a state of being imaged by the contrast agent. A part of the subject included in the reconstructed volume data is detected.

For example, as shown in FIG. 5, the detection function 37a attaches information in which the identification code is associated with the coordinates of each voxel detected from the volume data (positioning in the figure) of the positioning image to the volume data to store the storage circuit 35. To store. For example, the detection function 37a extracts the coordinates of the marker point from the volume data of the positioning image, and, as shown in FIG. 5, “identification code: C1, coordinates (x ₁ , y ₁ , z ₁ )”. , “Identification code: C2, coordinates (x ₂ , y ₂ ,
z ₂ ) ”and the like are stored in association with the volume data. Thereby, the detection function 37a can identify what kind of feature point is in which position in the volume data of the positioning image, and can detect each part such as an organ based on such information.

  Further, for example, as shown in FIG. 5, the detection function 61 attaches information in which the identification code is associated with the coordinates of each voxel detected from the volume data (scan in the figure) of the diagnostic image to the volume data. And stored in the memory circuit 35. Here, in the scan, the detection function 61 is labeled from volume data (contrast phase in the figure) contrasted with the contrast medium and volume data not contrasted by the contrast medium (non-contrast phase in the figure). The coordinates of the point can be extracted, and an identification code can be associated with the extracted coordinates.

For example, the detection function 61 extracts the coordinates of the marker point from the volume data of the non-contrast phase from the volume data of the diagnostic image, and as shown in FIG. (X ′ ₁ , y ′ ₁ , z ′ ₁ ) ”,“ identification code: C2, coordinates (x ′ ₂ ,
y ′ ₂ , z ′ ₂ ) ”and the like are stored in association with the volume data. The detection function 61
Extracts the coordinates of the marker point from the volume data of the contrast phase from the volume data of the diagnostic image, and as shown in FIG. 5, “identification code: C1, coordinates (x ′ ₁ , y ′ ₁ ,
z ′ ₁ ) ”,“ identification code: C2, coordinates (x ′ ₂ , y ′ ₂ , z ′ ₂ ) ”and the like are stored in association with the volume data. Here, in the case where the marker points are extracted from the volume data of the contrast phase, the marker points that can be extracted by being contrasted are included. For example, the detection function 61 can extract a blood vessel or the like contrasted with a contrast agent when extracting a marker point from volume data of contrast phase. Therefore, in the case of volume data of contrast phase, the detection function 61, as shown in FIG. 6, has coordinates (x ′ ₃₁ , y ′ ₃₁ , z ′ ₃₁ ) to the coordinates of marker points such as blood vessels extracted by contrasting. Identification codes C31, C32, C33 and C34 for identifying each blood vessel are associated with the coordinates (x ′ ₃₄ , y ′ ₃₄ , z ′ ₃₄ ) and the like.

As described above, the detection function 61 can identify which position in the volume data of the positioning image or the diagnostic image is at what position, and based on such information, the organ or the like Each part of can be detected. For example, the detection function 37a detects the position of the target part using information on the anatomical positional relationship between the target part to be detected and parts around the target part. For example, when the target region is “lung”, the detection function 37a acquires coordinate information associated with an identification code indicating the characteristics of the lung, and “rib”, “clavicle”, “heart” , Coordinate information associated with an identification code indicating a region around the “lung”, such as “diaphragm”. Then, the detection function 37a uses the information on the anatomical positional relationship between the “lung” and the surrounding site and the acquired coordinate information to extract the “lung” region in the volume data.

  For example, the detection function 37a uses the positional information such as “pulmonary apex: 2 to 3 cm above the clavicle”, “lower end of the lung: height of the seventh rib”, and the coordinate information of each part in FIG. As shown in FIG. 5, a region R1 corresponding to “lung” is extracted from the volume data. That is, the detection function 37a extracts the coordinate information of the voxel of the region R1 in the volume data. The detection function 37a associates the extracted coordinate information with the part information, attaches it to the volume data, and stores it in the storage circuit 35. Similarly, as shown in FIG. 6, the detection function 37a can extract a region R2 corresponding to “heart” or the like in the volume data.

  The detection function 37a detects a position included in the volume data based on a feature point that defines the position of the head, chest, etc. in the human body. Here, the positions of the head and chest in the human body can be arbitrarily defined. For example, if the chest is defined from the seventh cervical vertebra to the lower end of the lung, the detection function 37a detects from the feature point corresponding to the seventh cervical vertebra to the feature point corresponding to the lower end of the lung as the chest. In addition, the detection function 37a can detect a site | part by various methods besides the method using the anatomical feature point mentioned above. For example, the detection function 37a can detect a part included in the volume data by a region expansion method based on a voxel value.

  The position collation function 37b collates the positions of a plurality of parts in the subject included in the three-dimensional image data and the positions of the plurality of parts in the human body included in the virtual patient data. Here, virtual patient data is information representing the standard position of each of a plurality of parts in the human body. In other words, the position matching function 37b matches the position of the subject with the position of the standard part and stores the matching result in the storage circuit 35. For example, the position matching function 37b matches a virtual patient image in which a human body part is arranged at a standard position with volume data of the subject.

  Here, first, a virtual patient image will be described. The virtual patient image is an actual X-ray image of a human body having a standard physique corresponding to multiple combinations of parameters related to physique such as age, adult / child, male / female, weight, height, etc. It is generated in advance and stored in the storage circuit 35. That is, the storage circuit 35 stores data of a plurality of virtual patient images corresponding to the combination of parameters described above. Here, anatomical feature points (feature points) are stored in association with the virtual patient image stored by the storage circuit 35. For example, the human body has many anatomical feature points that can be extracted from an image based on morphological features and the like relatively easily by image processing such as pattern recognition. The positions and arrangements of these many anatomical feature points in the body are roughly determined according to age, adult / child, male / female, physique such as weight and height.

In the virtual patient image stored by the storage circuit 35, these many anatomical feature points are detected in advance, and the position data of the detected feature points are attached to the virtual patient image data together with the identification codes of the respective feature points. Or it is stored in association. FIG. 7 is a diagram illustrating an example of a virtual patient image stored by the storage circuit 35 according to the first embodiment. For example, as shown in FIG. 7, the storage circuit 35 has an identification code “V1”, “V2”, A virtual patient image associated with “V3” or the like is stored.

  That is, the storage circuit 35 stores the coordinates of the feature points in the coordinate space in the three-dimensional human body image and the corresponding identification codes in association with each other. For example, the storage circuit 35 stores the coordinates of the corresponding feature points in association with the identification code “V1” shown in FIG. Similarly, the storage circuit 35 stores the identification code and the feature point coordinates in association with each other. In FIG. 7, only the lung, heart, liver, stomach, kidney, and the like are shown as organs, but actually, the virtual patient image includes a larger number of organs, bones, blood vessels, nerves, and the like. . In FIG. 7, only the feature points corresponding to the identification codes “V1”, “V2”, and “V3” are shown, but actually more feature points are included.

  The position matching function 37b matches the feature points in the volume data of the subject detected by the detection function 37a with the feature points in the virtual patient image described above using an identification code, and the coordinate space of the volume data Associate with the coordinate space of the virtual patient image. FIG. 8 is a diagram for explaining an example of collation processing by the position collation function 37b according to the first embodiment. Here, in FIG. 8, matching is performed using three sets of feature points assigned with identification codes indicating the same feature points between the feature points detected from the scanogram and the feature points detected from the virtual patient image. However, the embodiment is not limited to this, and matching can be performed using an arbitrary set of feature points.

  For example, as shown in FIG. 8, the position matching function 37b includes feature points indicated by identification codes “V1”, “V2”, and “V3” in the virtual patient image, and identification codes “C1”, “C2” in the scanogram. When matching the feature points indicated by “C3” and “C3”, the coordinate space between the images is associated by performing coordinate conversion so that the positional deviation between the same feature points is minimized. For example, as shown in FIG. 8, the position matching function 37b has the same anatomically characteristic points “V1 (x1, y1, z1), C1 (X1, Y1, Z1)”, “V2 (x2, y2, z2). ), C2 (X2, Y2, Z2) "," V3 (x3, y3, z3), C3 (X3, Y3, Z3) ", so as to minimize the total" LS " A coordinate transformation matrix “H” is obtained.

LS = ((X1, Y1, Z1) -H (x1, y1, z1))
+ ((X2, Y2, Z2) -H (x2, y2, z2))
+ ((X3, Y3, Z3) -H (x3, y3, z3))

  The position matching function 37b can convert the scan range specified on the virtual patient image into the scan range on the positioning image by the obtained coordinate conversion matrix “H”. For example, the position matching function 37b uses the coordinate transformation matrix “H” to change the scan range “SRV” designated on the virtual patient image to the scan range “SRC” on the positioning image, as shown in FIG. Can be converted. FIG. 9 is a diagram illustrating a scan range conversion example by coordinate conversion according to the first embodiment. For example, as shown on the virtual patient image in FIG. 9, when the operator sets the scan range “SRV” on the virtual patient image, the position matching function 37b uses the above-described coordinate transformation matrix to set the scan The range “SRV” is converted into a scan range “SRC” on the scanogram.

Thereby, for example, the scan range “SRV” set so as to include the feature point corresponding to the identification code “Vn” on the virtual patient image has the identification code “Cn” corresponding to the same feature point on the scanogram. Is converted and set to a scan range “SRC”. Note that the above-described coordinate transformation matrix “H” may be stored in the storage circuit 35 for each subject and read and used as appropriate, or calculated every time a scanogram is collected. It may be the case. As described above, according to the first embodiment, the virtual patient image is displayed for the range designation at the time of presetting, and the position / range is planned on the virtual patient image, so that the positioning image (scano image) is captured. It is possible to automatically set numerical values for the position / range on the positioning image corresponding to the planned position / range.

  Returning to the description of FIG. 2, the processing circuit 37 includes a storage function 37c and an update function 37d, and performs control for improving the reproducibility of photographing. Such control will be described in detail later.

  By the way, conventionally, even with the same shooting plan, reproducibility of shooting may not be maintained due to a difference in operation between operators. For example, in setting the scan range (imaging range), the operator adjusts the preset (initial display information) of the scan range displayed on the positioning image. For this reason, due to the difference in operation between operators, as a result of photographing in different scan ranges, photographing reproducibility may not be maintained even with the same photographing plan.

  Therefore, the X-ray CT apparatus 1 according to the first embodiment has a configuration described below in order to improve the reproducibility of imaging. In the following description, a case where the reproducibility regarding the scan range is improved is illustrated, but the embodiment is not limited to this. For example, the present embodiment can be applied to the setting of shooting conditions other than the scan range, when the reproducibility of shooting cannot be maintained due to the difference in operation between operators.

  For example, the storage circuit 35 stores a scan range. For example, the storage circuit 35 stores a scan range for each photographing plan.

  FIG. 10 is a diagram illustrating an example of scan range information for each shooting plan stored in the storage circuit 35 according to the first embodiment. As illustrated in FIG. 10, the storage circuit 35 stores information in which an imaging plan, an imaging region, a scan start position, and a scan end position are associated with each other. Among these, the imaging plan is a list of imaging plans registered in the X-ray CT apparatus 1. The imaging region is information representing the region of the subject to be imaged in the imaging plan, such as the lung, the large intestine, and the head. The scan start position represents the position where the scan is started, and the scan end position represents the position where the scan ends. That is, a range surrounded by the scan start position and the scan end position corresponds to the scan range. Note that the scan range information stored in the storage circuit 35 is registered in advance by an operator, for example.

  As illustrated in FIG. 10, for example, the storage circuit 35 includes an imaging plan “Lung field examination”, an imaging region “Lung”, and a scan start position “1 cm above the mark point (feature point) at the upper right lung” Information associated with the scan end position “1 cm below the marker point at the lower left lung” is stored. This information is that the imaging part of the imaging plan named “Lung Field Examination” is the lung, and the scanning range is from 1 cm above the marked point (feature point) on the upper right lung to 1 cm below the marked point on the lower left lung. Indicates to do. Similarly, the storage circuit 35 stores information on the scan range for other shooting plans.

  The storage function 37c receives an operation for changing the photographing condition from the operator, and stores the history of the received operation in the storage circuit 35. For example, when the storage function 37c receives an operation to change the scan range as an imaging condition from the operator, the storage function 37c stores the history of the received operation in the storage circuit 35.

11 to 13 are diagrams for explaining processing of the storage function 37c according to the first embodiment. FIG. 11 illustrates a scan range R11 displayed on the positioning image.
FIG. 12 illustrates the scan range R12 after the change by the operator. FIG. 13 shows an example of an operation history stored by the storage function 37c. 11 to 13, the case where “Lung field scrutiny” is selected as the imaging plan will be described.

  As illustrated in FIG. 11, for example, when a scan range is set on the positioning image, the processing circuit 37 acquires information on the scan range from the storage circuit 35. Specifically, the processing circuit 37 sets the scan start position “1 cm above the mark point (feature point) on the upper right lung” and the scan end position “lower left lung bottom” as the scan range corresponding to the imaging plan “Lung field examination”. “1 cm below the marked point” is acquired from the storage circuit 35. Then, the processing circuit 37 calculates the scan range R11 indicated by the acquired scan start position “1 cm above the mark point (feature point) at the upper right lung” and the scan end position “1 cm below the mark point at the lower left lung”. Display on the positioning image (preset). Then, the operator performs an operation of changing the position and range (size) of the scan range R11 as necessary.

  As shown in FIG. 12, for example, the operator uses the input circuit 31 to expand the scan range R11 upward by 3 cm to perform the scan range R12. At this time, when the storage function 37 c receives this operation from the operator, the storage function 37 c stores the history of the received operation in the storage circuit 35.

  As illustrated in FIG. 13, for example, the storage function 37 c stores, as an operation history, information in which date / time, patient ID, and operation content are associated with each other in the storage circuit 35 for each imaging plan. Among these, the date and time is information indicating the date and time when the operation was performed. The patient ID is identification information for identifying a patient to be imaged. The operation content is information representing the content of the operation. When the change in FIG. 12 is accepted, for example, the storage function 37c associates the date and time “4/3 14:25”, the patient ID “0101”, and the operation content “change the scan start position upward by 3 cm”. The information is stored in the storage circuit 35 for each imaging plan “Lung field examination”. Similarly, the storage function 37c stores the history of the accepted operation in the storage circuit 35 every time an operation for changing the scan range is accepted.

  As described above, when the storage function 37c receives an operation for changing the scan range, the storage function 37c stores the history of the received operation in the storage circuit 35. Note that the distance at which the scan range is changed is preferably measured by the distance on the virtual patient image because the patient's height is not constant, but is not limited thereto, and may be measured by, for example, an actual distance. .

  In the above description of the storage function 37c, the case where an operation by the operator is received on the positioning image has been described. However, the embodiment is not limited to this. For example, the storage function 37c may accept an operation by the operator on the virtual patient image. In other words, the storage function 37c accepts an operation for changing information related to a region range defined based on a plurality of anatomical feature points in the image data of the subject or the image data of the virtual patient image. It functions as a part.

  The update function 37d updates the position that defines the imaging condition based on the operation history stored in the storage circuit 35. For example, the update function 37d acquires an operation history from the storage circuit 35, specifies a feature point near the outer edge of the changed range for each acquired operation history, and more than a predetermined frequency among the specified feature points The position of the feature point specified in (2) is updated as a position that defines the outer edge of the scan range.

  14 and 15 are diagrams for explaining processing of the update function 37d according to the first embodiment. FIG. 14 illustrates scan range information updated by the update function 37d. FIG. 15 illustrates the scan range R13 that is initially displayed when the imaging plan “Lung field examination” is performed after the update by the update function 37d. 14 and 15, processing when the update function 37d acquires the operation history shown in FIG. 13 will be described.

For example, the update function 37d acquires the operation history shown in FIG. Here, the three histories of the dates “4/3 14:25”, “4/5 12:21” and “4/5 17:05” are all histories in which the scan range is changed upward. In this case, the update function 37d determines to expand the scan range upward. And update function 3
7d specifies a marker point in the vicinity of the outer edge of the changed range for each of these three histories. In these three histories, when a cervical marker point is specified near the upper side after the change, the update function 37d updates the cervical marker point as a position that defines the upper side of the scan range. For example, the update function 37d updates the scan start position of the imaging plan “Lung field scrutiny” from “1 cm above the mark point on the upper right lung” (FIG. 10) to “Neck mark point” (FIG. 14). With this update, when the imaging plan “Lung field scrutiny” is performed from the next time onward, the processing circuit 37 moves the scan start position “marking point on the neck” and the scan end position “1 cm below the mark point on the lower left lung”. The indicated scan range R13 is displayed.

  Thus, the update function 37d updates the scan range information based on the operation history stored in the storage circuit 35. In other words, the update function 37d performs the first setting process for changing a part of the plurality of anatomical feature points for defining the range of the part based on the information related to the range of the part after the change, It functions as a setting unit that performs a second setting process for setting a position separated by a predetermined length in a predetermined direction with respect to a part of the anatomical characteristic points as a substantial anatomical characteristic point.

  Note that the information on the scan range set by the update function 37d may be set directly by a marker point (anatomical feature point), or a position separated from the marker point position (coordinate) information by a predetermined distance. May be set as Further, the information on the scan range set by the update function 37d may be set relatively using a plurality of marker points. In this case, the information on the scan range set by the update function 37d includes, for example, “the intermediate position between the first marker point and the second marker point” and “the distance between the first marker point and the second marker point. It is expressed as “position to divide by percentage”.

  FIGS. 16 and 17 are flowcharts showing a processing procedure by the X-ray CT apparatus 1 according to the first embodiment. FIG. 16 illustrates processing when the storage function 37c stores an operation history in the examination, and FIG. 17 illustrates processing when the update function 37d updates the scan range.

  Step S <b> 101 is a step corresponding to the scan control circuit 33. Step S101 is a step in which the scan control circuit 33 starts photographing. When step S101 is negative, the scan control circuit 33 does not start shooting and is in a standby state.

  Step S102 is a step corresponding to the scan control circuit 33. Step S102 is a step in which the scan control circuit 33 scans the positioning image in three dimensions when step S101 is affirmed.

  Step S103 is a step corresponding to the image reconstruction circuit 36. In step S103, the image reconstruction circuit 36 reconstructs volume data from projection data collected by scanning the positioning image.

  Step S104 is a step corresponding to the detection function 37a. This is a step in which the detection function 37a is realized when the processing circuit 37 calls and executes a program for processing corresponding to the detection function 37a from the storage circuit 35. Step S104 is a step in which the detection function 37a detects a plurality of parts of the subject from the volume data after reconstruction.

  Step S105 is a step corresponding to the processing circuit 37. In step S <b> 105, the processing circuit 37 displays the positioning image and the scan range preset on the display 32.

  Step S <b> 106 is a step corresponding to the input circuit 31. Step S106 is a step in which the input circuit 31 receives an operation for setting (changing) the scan range based on the positioning image.

  Step S107 is a step corresponding to the storage function 37c. This is a step in which the storage function 37c is realized by the processing circuit 37 calling and executing a processing program corresponding to the storage function 37c from the storage circuit 35. In step S107, the storage function 37c determines whether the scan range has been changed.

Step S108 is a step corresponding to the storage function 37c. This is a step in which the storage function 37c is realized by the processing circuit 37 calling and executing a processing program corresponding to the storage function 37c from the storage circuit 35. Step S108 is step S107.
Is a step in which the storage function 37c stores the history of operations in which the scan range has been changed in the storage circuit 35.

  Step S109 is a step corresponding to the scan control circuit 33. Step S109 is a step in which the scan control circuit 33 executes a diagnostic scan (main scan).

  Step S110 is a step corresponding to the image reconstruction circuit 36. In step S110, the image reconstruction circuit 36 reconstructs volume data from the projection data collected by the main scan.

  Step S <b> 111 is a step corresponding to the processing circuit 37. In step S111, the processing circuit 37 causes the display 32 to display a diagnostic image based on the reconstructed volume data.

  In FIG. 17, steps S201 to S205 are steps corresponding to the update function 37d. This is a step in which the update function 37d is realized when the processing circuit 37 calls and executes a program for the process corresponding to the update function 37d from the storage circuit 35.

  Step S201 is a step in which the update function 37d determines whether it is processing timing. Here, the processing timing may be an arbitrary timing determined by the operator. For example, the update function 37d determines that it is the processing timing when receiving an instruction from the operator to start the process of updating the scan range. Further, for example, the update function 37d periodically determines that it is a processing timing. If step S201 is negative, the update function 37d does not start processing and is in a standby state.

  Step S202 is a step in which the update function 37d acquires an operation history from the storage circuit 35 when step S201 is affirmed.

  Step S203 is a step in which the update function 37d identifies a marker point near the outer edge of the changed scan range for each operation history.

  Step S204 is a step in which the update function 37d identifies the most marked points among the identified marked points.

  In step S205, the update function 37d adjusts the preset scan range to the position of the identified marker point.

  16 and 17 are only examples. For example, the above processing procedures do not necessarily have to be executed in the order described above. For example, the above-described steps S101 to S111 may be executed by appropriately changing the order as long as the processing contents do not contradict each other.

  As described above, in the X-ray CT apparatus 1 according to the first embodiment, the storage function 37c receives an operation for changing the scan range from the operator, and stores the history of the received operation in the storage circuit 35. Store. The update function 37d updates the position that defines the scan range based on the history of operations stored in the storage circuit 35. For this reason, the X-ray CT apparatus 1 according to the first embodiment can improve the reproducibility of imaging.

For example, when the scan range stored for each imaging plan is frequently changed, the X-ray CT apparatus 1 learns the change and reflects it in the initial display (preset) of the next scan range. As described above, since the scan range is updated to an appropriate size for each shooting plan, a difference in operation among operators is less likely to be reflected in the scan range, and as a result, shooting reproducibility can be improved.

  In general, a scan range is defined for each imaging region, but depending on the facility, the scan range may be widened or narrowed. For example, in a certain facility, when the lung field is photographed, there is a case where it is always photographed including the neck. In such a case, conventionally, since the operator had to change the scan range every time, there was a risk that the reproducibility of photographing was lowered due to the difference in operation between operators. However, the X-ray CT apparatus 1 according to the first embodiment learns the change of the scan range and reflects it in the initial display of the scan range after the next time. For this reason, since the position and size of the scan range converge to a constant one, it is possible to improve the reproducibility of photographing.

  In addition, for example, the operator usually changes the scan range with a certain mark point (feature point) as a mark, such as “Let's take a picture including the cervix even if it is called lung field photography”. In this respect, since the X-ray CT apparatus 1 updates the initial display of the scan range using the feature points of the site of the subject P, the scan range can be changed to reflect the intention of change by the operator. it can.

  In the above-described embodiment, the case where the reproducibility regarding the scan range is improved has been described, but the embodiment is not limited thereto. For example, for the reconstruction range, it is also possible to learn the history of operations to change the range and reflect it in the next and subsequent shootings. That is, the imaging conditions that can be learned by the X-ray CT apparatus 1 are imaging conditions defined by at least one position of the part. For example, imaging conditions such as slice thickness may be learned.

(Second Embodiment)
In the above embodiment, the case where the position of the outer edge of the scan range is updated to the marker point has been described, but the embodiment is not limited to this. For example, the position of the outer edge of the scan range may be updated with a distance changed by the operator.

  The X-ray CT apparatus 1 according to the second embodiment has the same configuration as that of the X-ray CT apparatus 1 illustrated in FIG. 2, and a part of the processing of the update function 37d is different. Therefore, in the second embodiment, the description will focus on the points that are different from the first embodiment, and the description of the points having the same functions as the configuration described in the first embodiment will be omitted.

  The update function 37d acquires an operation history from the storage circuit 35, and specifies a feature point near the outer edge of the changed range for each acquired operation history. Then, when the feature point is specified for all operation histories, the update function 37d updates the position of the feature point specified more than a predetermined frequency among the specified feature points as a position that defines the outer edge of the scan range. . In addition, the update function 37d updates the position that defines the outer edge of the scan range with the smallest distance among the changed distances when the feature points are not specified for all operation histories.

  FIG. 18 is a flowchart illustrating a processing procedure performed by the X-ray CT apparatus 1 according to the second embodiment. FIG. 18 illustrates a process when the update function 37d according to the second embodiment updates the scan range.

In FIG. 18, steps S301 to S308 are steps corresponding to the update function 37d according to the second embodiment. This is a step in which the update function 37d is realized when the processing circuit 37 calls and executes a program for the process corresponding to the update function 37d from the storage circuit 35. Note that steps S301, S302, S305, and S306 in FIG. 18 are the same as steps S201, S202, S204, and S205 in FIG.

  Step S303 is a step in which the update function 37d specifies a marker point near the outer edge of the changed scan range for each shortest change in the operation history.

  Step S304 is a step in which the update function 37d determines whether or not the marker point has been identified for all operation histories. For example, when the update function 37d acquires three histories from the storage circuit 35, the update function 37d determines whether or not the sign points have been specified for all of the three acquired histories. Here, the update function 37d moves to step S305 when the mark point can be specified for all the three histories. On the other hand, the update function 37d proceeds to step S307 when the sign point is not specified in any of the three histories.

  Step S307 is a step in which, when Step S304 is denied, the update function 37d identifies the shortest changed distance among all operation histories. For example, if the distances changed in the three histories are 3 cm, 4 cm, and 5 cm, the update function 37d specifies the changed distance “3 cm”.

  In step S308, the update function 37d adjusts the scan range preset according to the specified distance. For example, when the scan start position of the scan range of the imaging plan “Lung field scrutiny” in FIG. 10 is updated 3 cm upward, the update function 37 d sets the scan start position “1 cm above the mark point on the upper right lung” to “ Update 4 cm above the sign point at the top of the right lung (see FIG. 19). FIG. 19 is a diagram for explaining processing of the update function 37d according to the second embodiment.

  As described above, the update function 37d updates the position of the outer edge of the scan range to the mark point if the outer edge mark point of the changed scan range is specified, and if the mark point is not specified, the update function 37d The position of the outer edge is updated with the distance changed by the operator. According to this, even if there is no appropriate mark point near the outer edge of the scan range, the scan range can be reliably updated.

  Note that the above example is only an example. For example, the update function 37d may be a case where the position of the outer edge of the scan range is updated by the distance changed by the operator without performing update by the marker point. In addition, the update is not necessarily limited to the case where the updated distance is the shortest. For example, it may be updated using the average value of the changed distance.

(Third embodiment)
In the above-described embodiment, the case where the imaging condition defined by the position is learned has been described. However, the relationship between the inspection order and the imaging plan may be further learned.

  The X-ray CT apparatus 1 according to the third embodiment has the same configuration as the X-ray CT apparatus 1 illustrated in FIG. 2, and part of the processing of the storage function 37 c and the update function 37 d is different. Therefore, in the third embodiment, description will be made mainly on points different from the first embodiment, and description of points having the same functions as those of the configuration described in the first embodiment will be omitted.

The storage function 37c stores the selected history in the storage circuit 35 each time an imaging plan is selected according to the inspection order. For example, when the X-ray CT apparatus 1 receives an inspection order, the storage function 37c acquires the content of the received inspection order. Then, when an imaging plan is selected as an imaging plan for a patient included in the examination order, the storage function 37c associates the contents of the examination order with the imaging plan and stores them in the storage circuit 35.

  FIG. 20 is a diagram for explaining processing of the storage function 37c according to the third embodiment. FIG. 20 shows an example of the history of the imaging plan selected according to the inspection order.

  As illustrated in FIG. 20, for example, the storage function 37 c stores, as a history, information in which the date / time, the patient ID, the contents of the examination order, and the imaging plan are associated with each other in the storage circuit 35. Among these, the date and time is information indicating the date and time when the examination order is received. The contents of the inspection order are information obtained by extracting keywords included in the inspection order. For example, in the storage function 37c, the date and time “4/3 14:25”, the patient ID “0101”, the content of the examination order “colon cancer, detailed examination”, and the imaging plan “colon cancer detailed examination” are associated with each other. Information is stored in the memory circuit 35.

  The update function 37d updates the information of the imaging plan presented when the inspection order is received based on the inspection order and the imaging plan included in the history stored in the storage circuit 35.

For example, the update function 37d extracts keywords for each shooting plan from the history shown in FIG. Here, the date and time “4/3 14:25”, “4/5 12:21”, and “4/5”
The three histories “17:05” are all histories of the imaging plan “colon cancer detailed examination”. The update function 37d extracts a common keyword from the contents of the inspection order for these three histories. In this case, “colon cancer” is extracted from each of the three histories as a common keyword. Therefore, if the keyword “colon cancer” is included in the examination order, the update function 37d associates the keyword “colon cancer” with the imaging plan “colon cancer detailed examination” and records / updates this information.

  Thereby, for example, every time the X-ray CT apparatus 1 receives an inspection order, the X-ray CT apparatus 1 extracts a keyword from the received inspection order. Then, if the extracted keyword is associated with the imaging plan, the X-ray CT apparatus 1 presents the imaging plan to the operator. According to this, the operator can select a desired shooting plan without searching for a desired shooting plan from a plurality of shooting plans. Furthermore, since the scan range is set within an appropriate range in the imaging plan, the operator can take an image of the patient without taking time and effort.

  In the example of FIG. 20, the case where one shooting plan is linked to the keyword of the inspection order has been described, but a plurality of shooting plans may be linked.

For example, the update function 37d extracts “colon cancer” as a keyword that is frequently included in the examination order. Then, the update function 37d searches the history including the extracted keyword “colon cancer” in the contents of the examination order. For example, when the imaging plans “colon cancer detailed examination” and “colorectal cancer simple imaging” are extracted by this search, the update function 37d uses two imaging plans “colon cancer detailed examination” for the keyword “colorectal cancer”. And “Colon cancer simple radiography”.
Thereby, for example, when the keyword “colon cancer” is extracted from the received examination order, the X-ray CT apparatus 1 uses two imaging plans “colon cancer detailed examination” and “colorectal cancer simple imaging” as an imaging plan. Can be presented to the operator.

  In addition, when presenting a plurality of imaging plans as candidates, the X-ray CT apparatus 1 may present the priorities with priorities. In this case, for example, the X-ray CT apparatus 1 may present the imaging plans included in the history in descending order, or may present the dates and times recorded in the history in order from the latest imaging plan.

(Other embodiments)
In addition to the above-described embodiment, various other forms may be implemented.

(Learning units)
In the above embodiment, the case has been described where the shooting conditions are learned for each shooting plan in the facility, but the embodiment is not limited thereto. For example, learning can be performed in arbitrary units.

  For example, when learning is performed in units of operators, the storage circuit 35 stores scan range information for each operator. In addition, the storage function 37 c adds identification information for identifying the operator, and stores an operation history in the storage circuit 35. The update function 37d updates the scan range information for each operator using identification information for identifying the operator. According to this, the X-ray CT apparatus 1 can perform learning in units of operators.

(Sharing of learning results)
Moreover, although said embodiment demonstrated the case where a learning result (learned information) was hold | maintained inside the X-ray CT apparatus 1, embodiment is not limited to this. For example, the learning result can be shared between different devices and even between facilities.

  The storage function 37c acquires an operation history stored in another device different from the own device. For example, the storage function 37c acquires a history of operations recorded in the other device from other devices inside and outside the facility connected via a wired or wireless network. Then, the storage function 37c stores the acquired operation history in the storage circuit 35 of the own device. The storage function 37c is not limited to the network connection, and may acquire the operation history by, for example, reading from a portable storage medium in which the operation history is recorded.

  The storage function 37c updates the position that defines the imaging condition based on the history of operations of the own device and other devices stored in the storage circuit 35. For example, the scan range is updated using a history with a common shooting plan even if the operation history is for another device.

  Note that information that can be shared is not limited to an operation history. For example, the X-ray CT apparatus 1 may share the scan range information updated by the update function 37d with other apparatuses inside and outside the facility.

(Change preset settings)
In the above embodiment, a case has been described in which the operation history is collected, and the setting of the initial display (preset) of the scan range is updated by learning the collected operation history. However, the embodiment is limited to this. It is not a thing.

  For example, the storage function 37c displays a preset scan range on the positioning image or the virtual patient image. Then, the storage function 37c receives an operation for changing the scan range on the positioning image or the virtual patient image. In other words, the storage function 37c as the accepting unit changes information related to the range of the part defined based on a plurality of anatomical feature points in the image data of the subject or the image data of the virtual patient image. Accept the operation.

  Then, the update function 37d updates the preset setting of the scan range based on the scan range changed by the operator. That is, the update function 37d updates the scan range information as described with reference to FIGS. 14 and 15, for example. In other words, the update function 37d as the setting unit performs first setting processing for changing some of a plurality of anatomical feature points for defining the region range based on the information related to the changed region range. Alternatively, a second setting process is performed for setting, as a substantial anatomical feature point, a position separated by a predetermined length in a predetermined direction with respect to some of the plurality of anatomical feature points.

  As described above, the X-ray CT apparatus 1 can directly change the preset setting of the scan range on the positioning image or the virtual patient image.

(Application to 2D photography)
Moreover, although said embodiment demonstrated the case where three-dimensional positioning imaging | photography and main imaging | photography were performed, embodiment is not limited to this. For example, the embodiment can be applied to a case where two-dimensional positioning imaging and main imaging are performed and a two-dimensional image (or positioning image) is collected.

(Medical image diagnostic equipment)
Moreover, although said embodiment demonstrated the case where the function which concerns on embodiment was applied to the X-ray CT apparatus 1, embodiment is not limited to this. For example, the functions according to the above-described embodiments may be applied to other medical image diagnostic apparatuses such as an X-ray diagnostic apparatus and an MRI (Magnetic Resonance Imaging) apparatus in addition to the X-ray CT apparatus 1.

  For example, in the MRI apparatus, the next scan range may be set on an image captured by an actual scan (main scan) in one sequence. In this case, a function applied to the MRI apparatus (a function corresponding to the storage function 37c) can accept an operation for changing a scan range on an image captured by actual scanning.

(Medical information management device)
Moreover, although said embodiment demonstrated the case where the function which concerns on embodiment was provided in the X-ray CT apparatus 1, it is not limited to this. For example, the detection function 37a, the position matching function 37b, the storage function 37c, and the update function 37d illustrated in FIG. 2 may be provided in the medical information management apparatus connected to the X-ray CT apparatus 1.

  FIG. 21 is a diagram illustrating an example of a configuration of a medical information management apparatus according to another embodiment. FIG. 21 illustrates a case where the medical information management apparatus 200 is provided in the medical information processing system 100 illustrated in FIG.

  The medical information management apparatus 200 is a computer that performs imaging condition setting and interpretation performed by a plurality of medical image diagnostic apparatuses such as the X-ray CT apparatus 1, the X-ray diagnostic apparatus, and the MRI apparatus. Here, the medical information management apparatus 200 illustrated in FIG. 21 controls the X-ray CT apparatus 1 to cause the X-ray CT apparatus 1 to perform positioning imaging and main imaging. Further, the medical information management apparatus 200 can receive the operation history collected by the X-ray CT apparatus 1 and display it on the display 202 or perform various processes. The medical information management apparatus 200 may be provided in each facility such as a hospital or may be provided outside the facility.

  As illustrated in FIG. 21, the medical information management apparatus 200 includes an input circuit 201, a display 202, a storage circuit 210, and a processing circuit 220. The input circuit 201, the display 202, and the storage circuit 210 have basically the same configuration as the input circuit 31, the display 32, and the storage circuit 35 illustrated in FIG.

  The processing circuit 220 is a processor that controls imaging performed by a plurality of medical image diagnostic apparatuses. For example, the processing circuit 220 controls the CT scan performed on the gantry 10 by controlling the scan control circuit 33 of the X-ray CT apparatus 1. The processing circuit 220 controls image reconstruction processing and image generation processing in the console 30 by controlling the image reconstruction circuit 36 of the X-ray CT apparatus 1. The processing circuit 220 controls the display 202 to display various image data stored in the storage circuit 210.

  Further, as illustrated in FIG. 21, the processing circuit 220 executes a detection function 221, a position matching function 222, a storage function 223, and an update function 224. Here, for example, the detection function 221, the position collation function 222, the storage function 223, and the update function 224 shown in FIG. 21 are the detection function 37a, the position collation function 37b, the storage function 37c, and the update function 37d shown in FIG. Basically the same processing is executed.

  That is, the storage function 223 as an accepting unit is an operation for changing information related to a range of a part defined based on a plurality of anatomical feature points in the image data of the subject or the image data of the virtual patient image. Accept. The update function 224 as the setting unit is a first setting process for changing a part of a plurality of anatomical feature points for defining the range of the part based on the information related to the range of the part after the change, or A second setting process is performed for setting, as a substantial anatomical feature point, a position separated by a predetermined length in a predetermined direction with respect to some of the plurality of anatomical feature points. Thereby, the medical information management apparatus 200 can improve the reproducibility of imaging.

  Note that the content described with reference to FIG. 21 is merely an example, and is not limited to the illustrated example. For example, in the medical information management apparatus 200, the storage function 223 stores the selected history in a predetermined storage unit each time an imaging plan is selected according to an examination order. Then, the update function 224 updates information on the imaging plan presented when the inspection order is received based on the inspection order and the imaging plan included in the history stored in the storage circuit 210.

  For example, the medical information management apparatus 200 may include the preprocessing circuit 34 and the image reconstruction circuit 36 illustrated in FIG. In this case, the medical information management apparatus 200 receives projection data collected by positioning imaging and projection data collected by main imaging from the X-ray CT apparatus 1. Then, the medical information management apparatus 200 reconstructs a positioning image or a diagnostic image from the received projection data.

  In FIG. 2, the single processing circuit 37 has been described as realizing the processing functions performed by the detection function 37a, the position matching function 37b, the storage function 37c, and the update function 37d. A processing circuit may be configured by combining the processors, and the functions may be realized by each processor executing a program.

The term “processor” used in the above description is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an application specific integrated circuit (ASIC), a programmable logic device (for example, Simple Programmable Logic Device (SPLD), Complex Programmable Logic Device (CPLD), and Field Programmable Gate Array (Field Programmable)
Gate Array (FPGA). The processor implements a function by reading and executing a program stored in the storage circuit. Instead of storing the program in the storage circuit, the program may be directly incorporated in the processor circuit. In this case, the processor realizes the function by reading and executing the program incorporated in the circuit. Note that each processor of the present embodiment is not limited to being configured as a single circuit for each processor, but may be configured as a single processor by combining a plurality of independent circuits to realize the function. Good. Further, a plurality of components in FIG. 2 may be integrated into one processor to realize the function.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or a part of the distribution / integration is functionally or physically distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured. Further, all or a part of each processing function performed in each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware by wired logic.

  In addition, among the processes described in the above embodiment, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually All or a part of the above can be automatically performed by a known method. In addition, the processing procedure, control procedure, specific name, and information including various data and parameters shown in the above-described document and drawings can be arbitrarily changed unless otherwise specified.

  In addition, the imaging method described in the above embodiment can be realized by executing a prepared imaging program on a computer such as a personal computer or a workstation. This imaging method can be distributed via a network such as the Internet. This imaging method can also be executed by being recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, and a DVD, and being read from the recording medium by the computer.

  According to at least one embodiment described above, the reproducibility of photographing can be improved.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

1 X-ray CT apparatus 36 Image reconstruction circuit 37 Processing circuit 37c Storage function 37d Update function

Claims (11)

A receiving unit that receives an operation to change information on a range of a part defined based on a plurality of anatomical feature points in image data of a subject or image data of a virtual patient image;
A first setting process for changing a part of a plurality of anatomical feature points for defining the range of the part based on information on the range of the part after the change, or the plurality of anatomical characteristics A setting unit for performing a second setting process of setting a position separated by a predetermined length in a predetermined direction as a substantial anatomical feature point with respect to a part of the point;
A medical image diagnostic apparatus comprising: The setting unit is configured to define an anatomical feature point in the vicinity of the outer edge of the changed range of the part based on information related to the changed range of the part. Set as anatomical feature points,
The medical image diagnostic apparatus according to claim 1. In positioning imaging, an image reconstruction unit for reconstructing three-dimensional positioning image data from projection data collected by detecting X-rays transmitted through the subject;
A detection unit for detecting each of a plurality of parts in the subject included in the three-dimensional positioning image data,
The reception unit stores a history of the operation in a predetermined storage unit,
The medical image diagnostic apparatus according to claim 1, wherein the setting unit performs the first setting process or the second setting process based on a history of operations stored in the storage unit. The setting unit acquires a history of the operation from the storage unit, specifies a feature point near the outer edge of the range after the change for each acquired operation history, and more than a predetermined frequency among the specified feature points Updating the position of the identified feature point as a position defining the outer edge of the range;
The medical image diagnostic apparatus according to claim 3. The setting unit acquires a history of the operation from the storage unit, specifies a distance at which the changed range is changed for each acquired operation history, and sets a minimum distance among the specified distances. Update the position defining the outer edge,
The medical image diagnostic apparatus according to claim 3. The setting unit acquires the operation history from the storage unit, specifies a feature point near the outer edge of the changed range for each acquired operation history, and specifies a feature point for all operation history In the case where the feature point is specified, the position of the feature point specified at a predetermined frequency or more is updated as a position that defines the outer edge of the range, and if the feature point is not specified for all operation histories, the change is made. Updating the position defining the outer edge of the range with the smallest of the distances provided,
The medical image diagnostic apparatus according to claim 3. The reception unit further stores the selected history in the storage unit each time an imaging plan is selected according to an inspection order,
The setting unit further updates information of the imaging plan to be presented when the inspection order is received based on the inspection order and the imaging plan included in the history stored in the storage unit.
The medical image diagnostic apparatus according to claim 3. The reception unit further acquires a history of the operation stored in another device different from the own device, stores the acquired operation history in the storage unit of the own device,
The setting unit further performs the first setting process or the second setting process based on a history of operations of the own device and the other device stored in the storage unit.
The medical image diagnostic apparatus according to claim 3. The reception unit stores, as the history, the distance at which the range is changed on the virtual patient image in the storage unit.
The medical image diagnostic apparatus according to any one of claims 4 to 8. A storage unit that stores the selected history in a predetermined storage unit each time an imaging plan is selected according to an inspection order;
A medical image diagnostic apparatus, comprising: an update unit that updates information of an imaging plan to be presented when the inspection order is received based on the inspection order and the imaging plan included in the history stored in the storage unit. A receiving unit that receives an operation to change information on a range of a part defined based on a plurality of anatomical feature points in image data of a subject or image data of a virtual patient image;
A first setting process for changing a part of a plurality of anatomical feature points for defining the range of the part based on information on the range of the part after the change, or the plurality of anatomical characteristics A setting unit for performing a second setting process of setting a position separated by a predetermined length in a predetermined direction as a substantial anatomical feature point with respect to a part of the point;
A medical information management apparatus comprising: