JP2015054218A - Magnetic resonance imaging device and image processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a magnetic resonance imaging device for performing ROI setting suitable for analysis by automatically dividing two activation areas even in the case that there area the two activation areas respectively corresponding to two adjacent sections in a functional brain image.SOLUTION: The magnetic resonance imaging device includes imaging execution means 41b for executing imaging for acquiring a functional brain image of a subject, brain area division means 41e for dividing a brain area included in the functional brain image into a plurality of division areas according to a standard brain map in which a standard brain is divided into a plurality of division areas, activation calculation means 41f for acquiring an activation area in each division area about at least one division area among the plurality of division areas of the subject, and ROI setting means 41g for setting an area of interest for performing analysis on the basis of the activation area.

Description

  The present embodiment as one aspect of the present invention relates to a magnetic resonance imaging apparatus and an image processing apparatus that obtain an activation region.

  A magnetic resonance imaging (MRI) apparatus measures an NMR signal (echo signal) generated by a nuclear spin constituting a subject, particularly a human tissue, and forms its head, abdomen, limbs, etc. It is an apparatus for imaging two-dimensionally or three-dimensionally. In imaging, the echo signal is given different phase encoding and frequency encoding depending on the gradient magnetic field. The measured echo signal is reconstructed into an image by two-dimensional or three-dimensional Fourier transform.

  Conventional MRI apparatuses are widely used not only for morphological image diagnosis but also for functional image diagnosis. For example, the MRI apparatus can provide a brain function image obtained by imaging brain activity by an fMRI (functional MRI) method. Here, the fMRI method is a method of generating a brain function image in which an activation region of the brain is imaged by using a BOLD (broad oxygenation level dependent) effect.

  In the fMRI method, an activation region is first obtained for the entire brain region from an image including the brain obtained based on the magnetic resonance phenomenon. Then, the operator (analyzer) sets a region of interest (ROI) based on the obtained activation region, and the analysis within the ROI is performed. Alternatively, in order to perform an objective analysis, a method in which an ROI is automatically set based on the obtained activation area has been proposed.

  In addition, as a prior art of this embodiment, the technique (for example, refer patent document 1) which displays the state of the area | region in an organ is mentioned.

JP 2009-213907 A

  The brain region is classified into a plurality of sections according to a structural (anatomical) classification or a functional classification. However, when the activation area is obtained in the conventional technique, in order to target the entire brain area, two activation areas corresponding to two adjacent sections are combined to be calculated as one activation area. There is a case. In this case, since the ROI is set in the activation area calculated as one activation area, an extra activation area (an activation area of another category) is included in the ROI.

  In addition, since it is difficult for the operator to visually recognize the boundary line between two adjacent sections, the ROI is set after the operator has manually divided the activation area calculated as one activation area. It is also difficult to do.

  In order to solve the above-described problems, the magnetic resonance imaging apparatus of the present embodiment includes an imaging execution unit that executes imaging for obtaining a brain function image of a subject, and a standard in which the standard brain is divided into a plurality of divided regions. According to a brain map, a brain region dividing unit that divides a brain region included in the brain function image into a plurality of divided regions, and at least one divided region of the plurality of divided regions in the subject. An activation calculation unit that obtains an activation region every time, and a region of interest setting unit that sets a region of interest for analysis based on the activation region.

  In order to solve the above-described problem, the image processing apparatus according to the present embodiment divides a brain region included in a brain function image of a subject into a plurality of divisions according to a standard brain map in which the standard brain is divided into a plurality of division regions. Based on the activation area, brain area dividing means for dividing the area, activation calculation means for obtaining an activation area for each of the divided areas of at least one of the plurality of divided areas in the subject, A region of interest setting means for setting a region of interest for analysis.

The figure which shows the structure of the MRI apparatus of this embodiment. The figure which shows the structure of the computer system with which the MRI apparatus of this embodiment is equipped. The figure which shows an example of the standard brain map based on the functional classification | category of a standard brain. The block diagram which shows the function of the MRI apparatus of this embodiment. The figure which shows an example of the standard brain map which combined the standard brain map based on the structural classification of a standard brain, and the standard brain map based on a functional classification. The figure for demonstrating the production | generation method of the division area image displayed. (A), (B) is a figure for demonstrating correction of the boundary line of a division area. The figure which shows an example of the image containing the activation area | region calculated by a prior art. The figure which shows an example of the image containing the activation area | region calculated with the MRI apparatus of this embodiment. The figure which shows the flowchart which shows the operation | movement of the MRI apparatus of this embodiment. 1 is a diagram illustrating a configuration of an image processing apparatus according to an embodiment. FIG. 2 is a block diagram illustrating functions of the image processing apparatus according to the embodiment. FIG. 4 is a flowchart illustrating the operation of the image processing apparatus according to the present embodiment.

  A magnetic resonance imaging (MRI) apparatus and an image processing apparatus of this embodiment will be described with reference to the accompanying drawings.

(MRI apparatus of this embodiment)
FIG. 1 is a diagram showing the configuration of the MRI apparatus of this embodiment.

  FIG. 1 shows an MRI apparatus 1 of the present embodiment. The MRI apparatus 1 includes a scanner device 2 and an image processing device 3. For example, the scanner device 2 is installed in an examination room, and the image processing device 3 is installed in a computer room.

  The scanner device 2 includes a static magnetic field magnet 21, a gradient magnetic field coil 22, a high frequency coil 23, and a bed device 24.

  The static magnetic field magnet 21 is, for example, a permanent magnet or a superconducting magnet, and generates a static magnetic field in an imaging region where the subject P is placed.

  The gradient coil 22 is disposed inside the static magnetic field magnet 21. The gradient magnetic field coil 22 generates a gradient magnetic field in the X-axis, Y-axis, and Z-axis directions set in the imaging region by a current supplied from the gradient magnetic field power supply 31. Further, the gradient magnetic fields of the X, Y, and Z axes generated by the gradient coil 22 correspond to, for example, the slice selection gradient magnetic field Gs, the phase encoding gradient magnetic field Ge, and the readout gradient magnetic field Gr, respectively. The slice selection gradient magnetic field Gs is used to arbitrarily determine an imaging section. The phase encoding gradient magnetic field Ge is used to change the phase of the magnetic resonance signal in accordance with the spatial position. The readout gradient magnetic field Gr is used for changing the frequency of the magnetic resonance signal in accordance with the spatial position.

  The high frequency coil 23 is disposed inside the gradient magnetic field coil 22. The transmission coil of the high-frequency coil 23 irradiates the subject P placed in the imaging region with a high-frequency pulse transmitted from the transmission unit 32. The receiving coil of the high-frequency coil 23 receives a magnetic resonance signal emitted from the subject P due to excitation of hydrogen nuclei by a high-frequency pulse. The high frequency coil 23 is attached to the head of the subject P in order to obtain a brain function image by the fMRI method.

  The couch device 24 includes a top plate 241. The top plate 241 can place the subject P at the time of imaging. The couch device 24 moves the top 241 together with the subject P into the imaging area under the control of the couch controller 35. Here, the subject P on the top plate 241 performs a task (Task) for activating the motor cortex, visual cortex, auditory cortex, speech cortex, sensory cortex, and the like during rest, (Rest) is repeatedly executed continuously. Therefore, the couch device 24 is provided with a stimulator 242 including a second display unit (not shown), a stimulus generator (not shown), and a stimulus generator console (not shown).

  The stimulus generator of the stimulator 242 is a device that generates stimuli for the subject P to perform various tasks. The console for the stimulus generator is an operator such as a doctor or engineer who sets the parameters set when designing a block paradigm such as the type of stimulus generated by the stimulus generator and the interval at which the stimulus generator generates a stimulus. Is a device for inputting. The stimulus generator console controls the generation of stimuli from the stimulus generator based on the imaging conditions (for example, repetition time) input from the computer system 36 and the input parameters.

  The second display unit of the stimulation device 242 is a monitor for the subject P to refer to, and is attached to the stimulation generator. Specifically, the second display unit is used to display a predetermined graphic or the like when a task for activating the visual cortex is executed, or to display a block paradigm screen. Or used.

  The image processing apparatus 3 includes a gradient magnetic field power supply 31, a transmission unit 32, a reception unit 33, a sequence controller 34, a bed controller 35, and a computer system 36.

  The gradient magnetic field power supply 31 supplies a current to the gradient magnetic field coil 22 based on an instruction from the sequence controller 34.

  The transmission unit 32 transmits a high-frequency pulse corresponding to the Larmor frequency to the high-frequency coil 23 based on an instruction from the sequence controller 34.

  The receiving unit 33 generates raw data by digitizing the magnetic resonance signal output from the high-frequency coil 23.

  The sequence controller 34 controls the scanning of the subject P by driving the gradient magnetic field power supply 31, the transmission unit 32, and the reception unit 33 based on the sequence information transmitted from the computer system 36. When the raw data is transmitted from the receiving unit 33 as a result of scanning the subject P, the sequence controller 34 transfers the raw data to the computer system 36.

  “Sequence information” refers to the strength of the power supplied from the gradient magnetic field power supply 31 to the gradient magnetic field coil 22 and the timing of supplying the power, the strength of the high frequency pulse transmitted from the transmission unit 32 to the high frequency coil 23, and the high frequency pulse. This is information defining a procedure for performing scanning, such as a transmission timing and a timing at which the receiving unit 33 detects an NMR signal.

  The couch controller 35 moves the couchtop 241 via the couch device 24 based on the position information transmitted from the computer system 36.

  The computer system 36 performs overall control of the MRI apparatus 1, data collection, image reconstruction, and the like. The computer system 36 has a configuration of a general computer.

  FIG. 2 is a diagram showing a configuration of the computer system 36 provided in the MRI apparatus 1 of the present embodiment.

  As shown in FIG. 2, the computer system 36 includes a configuration of a general computer, that is, a control unit 41, a storage unit 42, an input unit 43, a display unit 44, and a communication unit 45. The computer system 36 includes a standard brain map DB (database) 46. Each part 41 thru | or 46 is electrically connected via bus | bath B1.

  The control unit 41 includes a CPU (central processing unit), a memory, and the like, and performs overall control of the MRI apparatus 1. The function of the control unit 41 will be described later.

  The storage unit 42 is configured by a memory, a hard disk drive (HDD), or the like, and can store raw data received from the sequence controller 34 (shown in FIG. 1) and image data generated by the computer system 36. Device.

  The input unit 43 is configured by an input device such as a mouse or a keyboard. The input unit 43 is an operation unit that is input by an operator.

  The display unit 44 includes a liquid crystal display, a CRT (cathode ray tube) display, or the like.

  The communication unit 45 is a communication interface that performs communication with a network such as a LAN (local area network) or the sequence controller 34. The communication unit 45 controls input / output of various signals exchanged with the sequence controller 34 (shown in FIG. 1). For example, the communication unit 45 transmits sequence information to the sequence controller 34 and receives raw data from the sequence controller 34.

  The raw data received by the communication unit 45 includes the slice selection gradient magnetic field Gs generated by the gradient magnetic field coil 22, the phase encoding gradient magnetic field Ge, and the readout gradient magnetic field Gr, in the SE (slice encode) direction, PE ( The information is stored in the storage unit 42 as k-space data in which spatial frequency information in the phase encode (RO) direction and the RO (read out) direction is associated.

  The standard brain map DB 46 is a storage device that includes a memory, an HDD, and the like, and can store a standard brain map (standard coordinate space) obtained by dividing the standard brain into a plurality of divided regions as three-dimensional data. As a first example, the standard brain is classified into a plurality of sections according to the structural classification (frontal lobe, cerebrum, parietal lobe, etc.), so that the standard brain map DB 46 includes a standard having a plurality of sections as a plurality of divided regions. The brain map is memorized. As a second example, the standard brain is classified into a plurality of categories according to the functional classification (primary somatosensory area, primary motor area, somatosensory association area, etc.). A standard brain map having a segment as a plurality of divided regions is stored. As a third example, the standard brain is classified into a plurality of sections according to the classification arbitrarily set by the operator in advance, so that the standard brain map DB 46 includes a standard brain map having a plurality of sections as a plurality of divided regions. Is memorized.

  The standard brain map DB 46 has been described as storing one standard brain map according to one classification method. However, in one classification method, a plurality of standard brain maps differing by race and age (age) are used. May be stored.

  FIG. 3 is a diagram illustrating an example of a standard brain map based on the functional classification of the standard brain.

  FIG. 3 shows a two-dimensional Broadmann standard brain map in which the standard brain is functionally classified. In the standard brain map of Broadman, the standard brain is classified into “1” to “52” categories (Broadmann Area) according to the functional classification. In the standard brain map of functional classification, the classified classification is set as a divided area.

  FIG. 4 is a block diagram showing functions of the MRI apparatus 1 of the present embodiment.

  When the control unit 41 executes the program, the MRI apparatus 1 of the present embodiment, as shown in FIG. 3, includes an operation support unit 41a, an imaging execution unit 41b, a raw data reception unit 41c, an image processing unit 41d, a brain region It functions as a dividing unit 41e, an activation calculating unit 41f, an ROI setting unit 41g, and an analyzing unit 41h. Note that all or part of the means 41a to 41h may be provided as hardware in the MRI apparatus 1.

  The operation support means 41 a is a user interface that uses a lot of graphics for displaying information to the operator on the display unit 44 and can perform most basic operations by the input unit 43.

  The imaging execution unit 41b has a function of transmitting a top movement request input from the input unit 43 via the operation support unit 41a to the bed controller 35 (shown in FIG. 1) via the sequence controller 34. Based on the top plate movement request, the top plate 241 (shown in FIG. 1) is driven.

  In addition, the imaging execution unit 41b generates sequence information based on the imaging conditions input from the input unit 43 via the operation support unit 41a and the parameters set when designing the block paradigm. The sequence information is transmitted to the sequence controller 34, and a scan of the subject P (shown in FIG. 1) is executed.

  Further, the imaging execution means 41b has a function of transmitting a stimulus generation control signal to the bed controller 35 (shown in FIG. 1) via the sequence controller 34. Based on the stimulus generation control signal, a stimulus is generated in the stimulator 242 (shown in FIG. 1). Furthermore, the imaging execution means 41 b has a function of transmitting a screen display request to the bed controller 35 via the sequence controller 34. Based on the screen display request, the designated screen is displayed on the second display unit (not shown) of the stimulator 242.

  The raw data receiving unit 41 c has a function of receiving raw data from the sequence controller 34. The raw data is associated with spatial frequency information in the SE, PE, and RO directions by the slice selection gradient magnetic field Gs, the phase encoding gradient magnetic field Ge, and the readout gradient magnetic field Gr generated by the gradient coil 22. The stored k-space data is stored in the storage unit 42.

  The image processing unit 41d obtains an image set by performing post-processing, that is, reconstruction such as Fourier transform, on the raw data stored as k-space data by the storage unit 42. Based on the image set, the BOLD ( A brain function image (two-dimensional data or three-dimensional data) representing a change in the MRI signal is generated as image data by using a blood oxygenation level dependent effect. Further, the image processing unit 41d displays the brain function image on the display unit 44 or stores the brain function image in the storage unit 42 via the operation support unit 41a.

  The brain region dividing unit 41e is configured to determine a brain region (two-dimensional data or three-dimensional data) included in the brain function image of the subject P stored in the storage unit 42 in accordance with the standard brain map stored in the standard brain map DB 46. It has a function of dividing into a plurality of divided regions. In addition, the brain region dividing unit 41e displays an image (divided region image) indicating a plurality of divided regions in the brain function image on the display unit 44 or stores it in the storage unit 42 via the operation support unit 41a. . From the displayed divided region image, the operator can visually recognize how the brain of the subject P is divided according to the standard brain map.

  The standard brain map used by the brain region dividing unit 41e is set according to an operation to the input unit 43 performed by the operator through the operation support unit 41a from a plurality of standard brain maps stored in the standard brain map DB 46. Moreover, one or a plurality of standard brain maps may be used. When a plurality of standard brain maps are set, the brain region dividing unit 41e generates a new standard brain map by combining the plurality of set standard brain maps. Then, the brain region dividing unit 41e divides the brain region into a plurality of divided regions according to the new standard brain map.

  FIG. 5 is a diagram illustrating an example of a standard brain map in which a standard brain map based on the structural classification of the standard brain and a standard brain map based on the functional classification are combined.

  FIG. 5 shows a two-dimensional view of a standard brain map in which the standard brain is structurally classified (upper left in FIG. 5) and a standard brain map in which the standard brain is functionally classified (upper right in FIG. 5, similar to FIG. 3). Shown in FIG. 5 two-dimensionally shows a standard brain map (lower side in FIG. 5) in which the standard brain is structurally and functionally classified. A standard brain map in which the standard brain is structurally and functionally classified is generated as a new standard brain map.

  Returning to the description of FIG. 4, the brain region dividing unit 41 e converts the coordinate space (standard coordinate space) in the standard brain map into a coordinate space (observation coordinate space) for the brain (individual brain) of the subject P. Therefore, the brain region dividing unit 41e performs coordinate transformation on each of the plurality of divided regions of the standard brain map, and assigns them to the brain region of the subject P (shown in FIG. 1), whereby the brain of the subject P Is divided into a plurality of divided regions.

  FIG. 6 is a diagram for explaining a method of generating a displayed divided region image.

  As shown in FIG. 6, the coordinate space (standard coordinate space) in the standard brain map is coordinate-converted into the coordinate space (observation coordinate space) of the brain function image (individual brain) of the subject P. Therefore, coordinate transformation is performed on each of the plurality of divided regions of the standard brain map, and these are assigned to the brain region of the subject P, whereby the brain of the subject P is divided into the plurality of divided regions. The divided area image shows boundaries of a plurality of divided areas included in the brain of the subject P.

  Returning to the description of FIG. 4, the brain region dividing unit 41 e determines the boundary lines of the plurality of divided regions divided according to the standard brain map in accordance with an operation to the input unit 43 performed by the operator via the operation support unit 41 a. It is also possible to modify (delete, add, and change).

  7A and 7B are diagrams for explaining the correction of the boundary lines of the divided areas.

  For example, the motor language area corresponds to two categories “44” and “45” according to Broadmann shown in FIG. When the two sections “44” and “45” are each divided into two divided areas, there are cases where it is desired to make the two divided areas into one divided area. In such a case, as shown in FIG. 7B, the boundary line between the two divided regions is deleted by the operator's operation on the input unit 43 performed through the operation support means 41a. The number of divided areas can be corrected to be one divided area “44 + 45”.

  Similarly, a boundary line may be added in one divided area by an operation to the input unit 43 (shown in FIG. 4) performed by the operator via the operation support means 41a (shown in FIG. 4). In addition, the boundary line can be changed by the operator's operation on the input unit 43 (shown in FIG. 4) performed via the operation support means 41a (shown in FIG. 4). When the boundary line is corrected, the operator's operation on the input unit 43 performed through the operation support means 41a is accepted, and the divided region image is appropriately updated and displayed on the display unit 44 (shown in FIG. 4).

  Returning to the description of FIG. 4, the activation calculating unit 41 f has an activation region (for each divided region) for at least one divided region among a plurality of divided regions included in the divided region image generated by the brain region dividing unit 41 e. It has a function of calculating the activation site. In addition, the activation calculation unit 41 f displays an image including the activation region on the display unit 44 or stores the image in the storage unit 42 via the operation support unit 41 a.

  FIG. 8 is a diagram illustrating an example of an image including an activation region calculated by the conventional technique. FIG. 9 is a diagram illustrating an example of an image including an activation region calculated by the MRI apparatus 1 of the present embodiment.

  As shown in FIG. 8, in the conventional case where the activation area is obtained from the entire brain area included in the brain function image, the two activation areas f1 and f2 respectively corresponding to the two adjacent sections are joined together. It may be calculated as an individual activation area. However, as shown in FIG. 9, if the activation area calculation method for each divided area based on the classification by the activation calculation unit 41 f (illustrated in FIG. 4) is not calculated as one activation area, activation is performed. Only the activation area f1 of the desired divided area distinguished from the area f2 is calculated. In addition, it is not necessary to calculate the activation area for all the divided areas, and the activation area is limited to a part of the divided areas selected by the operation of the input unit 43 performed by the operator via the operation support means 41a. It may be sought. As a result, it is also possible to perform analysis, which will be described later, by narrowing down to a divided region in which the operator is interested.

  Returning to the description of FIG. 4, the ROI setting unit 41g has a function of setting an ROI for performing analysis based on the activation area for each divided area calculated by the activation calculation unit 41f. The ROI setting unit 41g displays an image including the ROI on the display unit 44 or stores the image in the storage unit 42 via the operation support unit 41a.

  The ROI setting unit 41g sets the ROI based on the operation of the operator performed while viewing the image (shown in FIG. 9) including the displayed activation area calculated and displayed by the activation calculation unit 41f. Alternatively, the ROI setting unit 41g can automatically set the ROI in the activation region by surrounding the region where the statistical value (p value) of the signal value of the divided region has a value equal to or greater than the threshold value. Since the statistic is “0” at the boundary between two adjacent divided areas, an appropriate ROI is set without straddling two adjacent divided areas even when the ROI is automatically set. .

  The analysis unit 41h has a function of analyzing the ROI set by the ROI setting unit 41g. The analysis unit 41h performs ROI analysis of variance, t-test, and the like. According to the analysis means 41h, it is possible to perform analysis with an ROI suitable for analysis without making the operator aware of the division of the activation area where a plurality of activation areas can be recognized as one activation area.

  Subsequently, the operation of the MRI apparatus 1 of the present embodiment will be described with reference to FIGS. 4 and 10.

  FIG. 10 is a flowchart illustrating the operation of the MRI apparatus 1 of the present embodiment.

  The MRI apparatus 1 drives the top plate 241 (shown in FIG. 1) on which the subject P (shown in FIG. 1) is mounted, generates sequence information, and executes the scan of the subject P, thereby performing fMRI. The imaging by the method is executed (step ST1). Then, the MRI apparatus 1 generates a brain function image as image data by performing post-processing, that is, reconstruction such as Fourier transform, on the raw data as k-space data (step ST2).

  The MRI apparatus 1 sets one or a plurality of standard brain maps from a plurality of standard brain maps stored in the standard brain map DB 46 (step ST3). The MRI apparatus 1 uses the subject P (shown in FIG. 1) generated in step ST2 in accordance with one standard brain map set in step ST3 or a standard brain map generated by combining a plurality of standard brain maps. ) Is divided into a plurality of divided areas (step ST4).

  The MRI apparatus 1 determines whether or not to modify (delete, add, change) the boundary lines of the plurality of divided areas divided in step ST4 (step ST5). If YES in step ST5, that is, if it is determined that the boundary lines of the plurality of divided areas are to be corrected, the MRI apparatus 1 divides at least one divided area among the plurality of divided areas after the boundary line correction. An activation area is calculated for each area (step ST6).

  On the other hand, if the determination in step ST5 is NO, that is, if it is determined that the boundary lines of the plurality of divided regions are not to be corrected, the MRI apparatus 1 determines at least one of the plurality of divided regions after the division in step ST4. For the area, an activation area is calculated for each divided area (step ST7).

  The MRI apparatus 1 sets the ROI based on the activation area for each divided area calculated in step ST6 or ST7 (step ST8). Then, the MRI apparatus 1 analyzes the ROI set in step ST8 (step ST9).

  According to the MRI apparatus 1 of the present embodiment, even if there are two activation areas corresponding to two adjacent sections in the brain function image, the two activation areas are automatically divided. Thus, ROI settings suitable for analysis can be performed. This eliminates the need for the operator to manually divide the two activation areas, thereby reducing the operator's workload.

(Image processing apparatus of this embodiment)
FIG. 11 is a diagram illustrating a configuration of the image processing apparatus according to the present embodiment.

  FIG. 11 shows an image processing apparatus (workstation) 5 of the present embodiment. The image processing apparatus 5 includes a configuration of a general computer, that is, a control unit 51, a storage unit 52, an input unit 53, a display unit 54, and a communication unit 55. Further, the image processing device 5 includes a standard brain map DB 56. Each part 51 thru | or 56 is electrically connected via bus | bath B2.

  The control unit 51 includes a CPU, a memory, and the like, and performs overall control of the image processing apparatus 5. The function of the control unit 51 will be described later.

  The storage unit 52 includes a memory, an HDD, and the like, and is a brain function generated by an MRI apparatus, a nuclear medicine diagnosis apparatus, and an image generation apparatus (not shown) such as a near-infrared spectroscopy (NIRS). This is a storage device capable of storing image data of images and image data generated by the image processing device 5.

  The input unit 53 is configured by an input device such as a mouse or a keyboard. The input unit 53 is an operation unit that is input by an operator.

  The display unit 54 is configured by a liquid crystal display, a CRT display, or the like.

  The communication unit 55 is a communication interface that performs communication with a network such as a LAN. The communication unit 55 controls input / output of various signals exchanged with an external device (illustrated in FIG. 12) such as an image server. For example, the communication unit 55 receives a brain function image from the image server as image data.

  The standard brain map DB 56 is a storage device that is configured by a memory, an HDD, or the like and can store a standard brain map (three-dimensional data). The standard brain map stored in the standard brain map DB 56 is the same as that described in the standard brain map DB 46 (shown in FIG. 2).

  FIG. 12 is a block diagram illustrating functions of the image processing apparatus 5 according to the present embodiment.

  When the control unit 51 executes the program, the image processing apparatus 5 according to the present embodiment, as shown in FIG. 12, includes an operation support unit 51a, a brain region division unit 51e, an activation calculation unit 51f, an ROI setting unit 51g, and an analysis. It functions as the means 51h and the image data receiving means 51i. All or part of the means 51a, 51e to 51i may be provided as hardware in the image processing apparatus 5.

  The operation support means 51a has the same function as the operation support means 41a (shown in FIG. 4). In other words, the operation support means 51a is a user interface that can use most graphics for displaying information to the operator on the display unit 54 and can perform most basic operations by the input unit 53.

  The image data receiving means 51i receives the brain function image from the external device E such as an image generation device (not shown) that generates a brain function image of the subject or an image server (not shown) that stores the brain function image. As a receiving function. Further, the image data receiving unit 51 i stores the brain function image in the storage unit 52.

  The brain region dividing unit 51e has the same function as the brain region dividing unit 41e (shown in FIG. 4). The brain region dividing means 51e selects a plurality of brain regions (two-dimensional data or three-dimensional data) included in the brain function image of the subject stored in the storage unit 52 in accordance with the standard brain map stored in the standard brain map DB 56. Divide into the divided areas.

  The activation calculating unit 51f has the same function as the activation calculating unit 41f (shown in FIG. 4). The activation calculating unit 51f calculates an activation region for each divided region for at least one divided region among a plurality of divided regions included in the divided region image generated by the brain region dividing unit 51e.

  The ROI setting unit 51g has the same function as the ROI setting unit 41g (shown in FIG. 4). The ROI setting unit 51g sets an ROI for performing analysis based on the activation area for each divided area calculated by the activation calculation unit 51f.

  The analysis unit 51h has the same function as the analysis unit 41h (illustrated in FIG. 4). The analysis unit 51h analyzes the ROI set by the ROI setting unit 51g.

  Subsequently, the operation of the image processing apparatus 5 of the present embodiment will be described with reference to FIGS. 11 and 13.

  FIG. 13 is a flowchart illustrating the operation of the image processing apparatus 5 according to the present embodiment.

  The image processing device 5 communicates from an external device E (shown in FIG. 12) such as an image generation device (not shown) that generates a brain function image of a subject or an image server (not shown) that stores the brain function image. The brain function image is received as image data via 55 (step ST12). Then, the image processing apparatus 5 sets one or a plurality of standard brain maps from the plurality of standard brain maps stored in the standard brain map DB 56 (step ST13). The image processing apparatus 5 performs the brain function image of the subject received in step ST12 according to one standard brain map set in step ST13 or a standard brain map generated by combining a plurality of standard brain maps. The brain region is divided into a plurality of divided regions (step ST14).

  The image processing apparatus 5 determines whether or not to modify (delete, add, change) the boundary lines of the plurality of divided areas divided in step ST14 (step ST15). If YES in step ST15, that is, if it is determined that the boundary lines of the plurality of divided areas are to be corrected, the image processing device 5 determines the at least one divided area among the plurality of divided areas after the boundary line correction. An activation area is calculated for each divided area (step ST16).

  On the other hand, if the determination in step ST15 is NO, that is, if it is determined that the boundary lines of the plurality of divided areas are not to be corrected, the image processing device 5 determines that at least one of the plurality of divided areas after the division in step ST14. For the divided areas, an activation area is calculated for each divided area (step ST17).

  The image processing apparatus 5 sets the ROI based on the activation area for each divided area calculated in step ST16 or ST17 (step ST18). Then, the image processing device 5 analyzes the ROI set in step ST18 (step ST19).

  According to the image processing apparatus 5 of the present embodiment, even if there are two activation areas corresponding to two adjacent sections in the brain function image, the two activation areas are automatically selected. It is possible to divide and set ROI suitable for analysis. This eliminates the need for the operator to manually divide the two activation areas, thereby reducing the operator's workload.

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

DESCRIPTION OF SYMBOLS 1 MRI apparatus 5 Image processing apparatus 41a, 51a Operation support means 41b Imaging execution means 41c Raw data reception means 41d Image processing means 41e, 51e Brain region division means 41f, 51f Activation calculation means 41g, 51g ROI setting means 41h, 51h Analysis means 51i Image data receiving means

Claims (9)

Imaging execution means for executing imaging for obtaining a brain function image of the subject;
In accordance with a standard brain map in which the standard brain is divided into a plurality of divided regions, a brain region dividing means for dividing the brain region included in the brain functional image into a plurality of divided regions;
Activation calculation means for obtaining an activation area for each of the divided areas of at least one of the plurality of divided areas in the subject;
A region of interest setting means for setting a region of interest for performing analysis based on the activation region;
A magnetic resonance imaging apparatus.   The magnetic resonance imaging apparatus according to claim 1, wherein the brain region dividing unit assigns the standard brain map to the brain region of the subject by coordinate transformation.   The magnetic resonance imaging apparatus according to claim 1, wherein the brain region dividing unit divides the brain region of the subject according to a standard brain map generated by combining a plurality of different standard brain maps.   The brain region dividing unit according to any one of claims 1 to 3, wherein the brain region dividing unit divides the brain region of the subject according to a standard brain map designated via an input unit from a plurality of different standard brain maps. Magnetic resonance imaging device.   The brain region dividing means changes, adds, or deletes boundary lines of a plurality of divided regions divided according to the standard brain map according to an instruction via an input unit. The magnetic resonance imaging apparatus described.   The magnetic resonance imaging apparatus according to claim 1, wherein the activation calculation unit sets the at least one divided region in accordance with an instruction via an input unit.   7. The region of interest setting unit according to claim 1, wherein the region of interest setting unit automatically sets the region of interest by extracting a region having a value equal to or greater than a certain threshold value from the at least one divided region. The magnetic resonance imaging apparatus described.   The magnetic resonance imaging apparatus according to claim 1, further comprising display means for displaying at least one of the brain region, the activation region, and the region of interest on a display unit. A brain region dividing means for dividing the brain region included in the brain function image of the subject into a plurality of divided regions according to a standard brain map in which the standard brain is divided into a plurality of divided regions;
Activation calculation means for obtaining an activation area for each of the divided areas of at least one of the plurality of divided areas in the subject;
A region of interest setting means for setting a region of interest for performing analysis based on the activation region;
An image processing apparatus.

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