Magnetic resonance imaging apparatus, image generation method, and image generation program

Abstract

To reduce artifacts generated with a rapid change in a phase.SOLUTION: A magnetic resonance imaging device includes an acquisition unit and a generation unit. The acquisition unit acquires a first coil sensitivity map on a plurality of coils and a second coil sensitivity map on the plurality of coils different in the phase from the first coil sensitivity map. The generation unit generates a first image on the basis of the first coil sensitivity map and magnetic resonance data on the plurality of coils, generates a second image on the basis of the second coil sensitivity map, the first coil sensitivity map, and the first image, and generates a final image on the basis of the first image and the second image.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The embodiments disclosed in this specification and the drawings relate to a magnetic resonance imaging apparatus, an image generating method, and an image generating program. [Background technology]

[0002] In magnetic resonance imaging (MRI) devices, thinning-out acquisition is sometimes performed to shorten imaging time. In this case, a coil sensitivity map may be estimated from the thinned-out data obtained by thinning-out acquisition. When reconstruction is performed using the estimated coil sensitivity map, there may be areas in the phase of the reconstructed image that do not change smoothly.

[0003] Therefore, when an interpolation process is performed on an image reconstructed using the estimated coil sensitivity map, artifacts occur in parts of the image after the interpolation process where the phase changes significantly. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-240571 Summary of the Invention [Problem to be solved by the invention]

[0005] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to reduce artifacts that occur due to abrupt phase changes. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0006] According to an embodiment, a magnetic resonance imaging apparatus includes an acquisition unit and a generation unit. The acquisition unit acquires a first coil sensitivity map for a plurality of coils and a second coil sensitivity map for the plurality of coils, the second coil sensitivity map being out of phase with the first coil sensitivity map. The generation unit generates a first image based on the first coil sensitivity map and magnetic resonance data for the plurality of coils, generates a second image based on the second coil sensitivity map, the first coil sensitivity map, and the first image, and generates a final image based on the first image and the second image. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a block diagram showing an example of a magnetic resonance imaging apparatus according to an embodiment. [Figure 2] FIG. 2 is a flowchart showing an example of a procedure of an image generation process according to the embodiment. [Figure 3] FIG. 3 is a diagram showing an example of the relationship between various processes in the image generation process and data related to the various processes according to the embodiment. [Figure 4] FIG. 4 is a diagram showing an example of an estimated sensitivity intensity image according to the embodiment. [Figure 5] FIG. 5 is a diagram showing an example of a plurality of phase images in a first coil sensitivity map according to the embodiment. [Figure 6] FIG. 6 is a diagram showing an example of an intensity image in a plurality of coil images according to the embodiment. [Figure 7] FIG. 7 is a diagram showing an example of a phase image in a plurality of coil images according to the embodiment. [Figure 8] FIG. 8 is a diagram showing an example of a first image according to the embodiment. [Figure 9] FIG. 9 is a diagram showing an example of an intensity image in a plurality of resolved images corresponding to a plurality of coils according to the embodiment. [Figure 10] FIG. 10 is a diagram showing an example of a phase image in a plurality of resolved images corresponding to a plurality of coils according to the embodiment. [Figure 11]FIG. 11 is a diagram showing an example of a plurality of phase images in a second coil sensitivity map according to the embodiment. [Figure 12] FIG. 12 is a diagram showing an example of a plurality of phase images in a third coil sensitivity map according to the embodiment. [Figure 13] FIG. 13 is a diagram showing an example of a coil-combined second image according to the embodiment. [Figure 14] FIG. 14 is a diagram showing an example of a coil-combined third image according to the embodiment. [Figure 15] FIG. 15 is a diagram showing an example of a first interpolation image according to the embodiment. [Figure 16] FIG. 16 is a diagram showing an example of a second interpolation image according to the embodiment. [Figure 17] FIG. 17 is a diagram showing an example of a third interpolation image according to the embodiment. [Figure 18] FIG. 18 is a diagram showing an example of a final image according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, embodiments of a magnetic resonance imaging (MRI) device, an image generation method, and an image generation program will be described in detail with reference to the drawings. Note that the technical concept of the present embodiment may be applied to various modalities combined with an MRI device, such as a PET (Positron Emission Tomography)-MRI device or a SPECT (Single Photon Emission Computed Tomography)-MRI device.

[0009] (First embodiment) Fig. 1 is a diagram showing an example of an MRI apparatus 100 according to this embodiment. As shown in Fig. 1, the MRI apparatus 100 includes a static magnetic field magnet 101, a gradient magnetic field coil 103, a gradient magnetic field power supply 105, a bed 107, a bed control circuit 109, a transmission circuit 113, a transmission coil 115, a reception coil 117, a reception circuit 119, an imaging control circuit (imaging control unit) 121, a system control circuit (system control unit) 123, a memory 125, an input interface 127, a display 129, and a processing circuit 131.

[0010] The static magnetic field magnet 101 is a magnet formed in a hollow, approximately cylindrical shape. The static magnetic field magnet 101 generates a substantially uniform static magnetic field in the internal space. For example, a superconducting magnet or the like is used as the static magnetic field magnet 101.

[0011] The gradient magnetic field coil 103 is a hollow, approximately cylindrical coil and is disposed on the inner surface of the cylindrical cooling vessel. The gradient magnetic field coil 103 receives current individually from a gradient magnetic field power supply 105 to generate gradient magnetic fields whose magnetic field strength changes along the mutually orthogonal X, Y, and Z axes. The gradient magnetic fields of the X, Y, and Z axes generated by the gradient magnetic field coil 103 form, for example, a slice selection gradient magnetic field, a phase encoding gradient magnetic field, and a frequency encoding gradient magnetic field. The slice selection gradient magnetic field is used to arbitrarily determine an imaging cross section. The phase encoding gradient magnetic field is used to change the phase of a magnetic resonance signal (hereinafter referred to as an MR (Magnetic Resonance) signal) according to a spatial position. The frequency encoding gradient magnetic field is used to change the frequency of the MR signal according to a spatial position.

[0012] The gradient magnetic field power supply 105 is a power supply device that supplies current to the gradient magnetic field coil 103 under the control of the imaging control circuit 121 .

[0013] The bed 107 is a device equipped with a top plate 1071 on which the subject P is placed. The bed 107 inserts the top plate 1071 on which the subject P is placed into the bore 111 under the control of a bed control circuit 109.

[0014] The bed control circuit 109 is a circuit that controls the bed 107. The bed control circuit 109 drives the bed 107 in response to instructions from the operator via the input / output interface 17, thereby moving the tabletop 1071 in the longitudinal direction, the up-down direction, and in some cases the left-right direction.

[0015] The transmission circuit 113 supplies radio frequency pulses modulated at the Larmor frequency to the transmission coil 115 under the control of the imaging control circuit 121. For example, the transmission circuit 113 has an oscillator, a phase selection unit, a frequency conversion unit, an amplitude modulation unit, an RF (Radio Frequency) amplifier, and the like. The oscillator generates an RF pulse at a resonance frequency specific to the target atomic nucleus in a static magnetic field. The phase selection unit selects the phase of the RF pulse generated by the oscillator. The frequency conversion unit converts the frequency of the RF pulse output from the phase selection unit. The amplitude modulation unit modulates the amplitude of the RF pulse output from the frequency conversion unit according to, for example, a sinc function. The RF amplifier amplifies the RF pulse output from the amplitude modulation unit and supplies it to the transmission coil 115.

[0016] The transmission coil 115 is an RF coil arranged inside the gradient magnetic field coil 103. In response to the output from the transmission circuit 113, the transmission coil 115 generates an RF pulse corresponding to a high frequency magnetic field.

[0017] The receiving coil 117 is an RF coil arranged inside the gradient magnetic field coil 103. The receiving coil 117 receives MR signals emitted from the subject P by a high frequency magnetic field. The receiving coil 117 outputs the received MR signals to a receiving circuit 119. The receiving coil 117 is, for example, a coil array having one or more, typically a plurality of coil elements (hereinafter referred to as a plurality of coils). For the sake of concreteness, the receiving coil 117 will be described below as a coil array having a plurality of coils.

[0018] 1, the transmit coil 115 and the receive coil 117 are depicted as separate RF coils, but the transmit coil 115 and the receive coil 117 may be implemented as an integrated transmit / receive coil. The transmit / receive coil corresponds to the imaging region of the subject P and is, for example, a local transmit / receive RF coil such as a head coil.

[0019] The receiving circuit 119 generates digital MR signals (hereinafter referred to as MR data) based on the MR signals output from the receiving coil 117 under the control of the imaging control circuit 121. Specifically, the receiving circuit 119 performs signal processing such as detection and filtering on the MR signals output from the receiving coil 117, and then performs analog-to-digital (A / D) conversion (hereinafter referred to as A / D conversion) on the data that has undergone this signal processing to generate MR data. The receiving circuit 119 outputs the generated MR data to the imaging control circuit 121. For example, the MR data is generated in each of a plurality of coils and output to the imaging control circuit 121 together with tags that identify each of the plurality of coils.

[0020] The imaging control circuit 121 controls the gradient magnetic field power supply 105, the transmission circuitry 113, the reception circuitry 119, etc. in accordance with the imaging protocol output from the processing circuitry 15 to perform imaging of the subject P. The imaging protocol has a pulse sequence according to the type of examination. The imaging protocol defines the magnitude of the current supplied to the gradient magnetic field coil 103 by the gradient magnetic field power supply 105, the timing at which the gradient magnetic field power supply 105 supplies the current to the gradient magnetic field coil 103, the magnitude and time width of the radio frequency pulse supplied to the transmission coil 115 by the transmission circuitry 113, the timing at which the radio frequency pulse is supplied to the transmission coil 115 by the transmission circuitry 113, the timing at which the MR signal is received by the reception coil 117, etc. The imaging control circuit 121 drives the gradient magnetic field power supply 105, the transmission circuitry 113, the reception circuitry 119, etc. to image the subject P, and then receives MR data from the reception circuitry 119 and transfers the received MR data to the processing circuitry 131.

[0021] The imaging control circuit 121 acquires MR data by, for example, a scan that executes a pulse sequence related to imaging with thinned (under-sampling) acquisition (hereinafter referred to as thinned imaging). Hereinafter, for the sake of specificity, it is assumed that the scan of the subject P is parallel imaging having an imaging protocol (hereinafter referred to as ACS protocol) that acquires MR signals related to trajectories corresponding to auto-calibrated signals (auto-calibrated signals: hereinafter referred to as ACS) in k-space. For example, the parallel imaging related to the scan in this embodiment has an imaging protocol similar to GRAPPA (generalized autocalibrating partially parallel acquisitions).

[0022] Note that the trajectory corresponding to the ACS in the parallel imaging is not limited to the vicinity of the center of the k-space as in GRAPPA, but can be set arbitrarily. Furthermore, the scan of the subject P is not limited to the parallel imaging, and may be realized by an imaging protocol similar to compressed sensing, as long as the subject P has an ACS protocol. Furthermore, the scan of the subject P may be realized by an imaging protocol that combines compressed sensing and parallel imaging, as long as the subject P has an ACS protocol.

[0023] The MR data collected by parallel imaging in each of the multiple coils includes data collected by thinning out phase encoding steps in k-space according to a reduction factor (R, also called acceleration factor) preset by a user's instruction, etc., and an ACS. The ACS includes target data at a target point associated with the position of data thinning and source data at a source point adjacent to the target point.

[0024] The imaging control circuit 121 may collect MR data related to the generation of an image showing the distribution of sensitivity of the receive coil 117 used to image the subject P by any imaging method. The image showing the sensitivity of the coil is expressed by complex number data. The collection of MR data related to the generation of the image showing the distribution of sensitivity of the receive coil 117 is executed by the imaging control circuit 121 in a pre-scan including a locator scan, for example, prior to a scan of the subject P. The imaging control circuit 121 is realized by, for example, a processor.

[0025] The term "processor" refers to circuits such as a CPU, a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)).

[0026] The system control circuit 123 has hardware resources such as a processor, a read-only memory (ROM), a random access memory (RAM), etc. (not shown), and uses a system control function to control the MRI apparatus 100. Specifically, the system control circuit 123 reads a system control program stored in the memory, expands it on the memory, and controls each circuit of the MRI apparatus 100 according to the expanded system control program.

[0027] For example, the system control circuit 123 reads out an imaging protocol from the memory 125 based on imaging conditions input by the operator via the input interface 127. The system control circuit 123 transmits the imaging protocol to the imaging control circuit 121 and controls imaging of the subject P. The system control circuit 123 is realized by, for example, a processor. The system control circuit 123 may be incorporated into the processing circuit 15. In this case, the system control function is executed by the processing circuit 15, and the processing circuit 15 functions as a substitute for the system control circuit 123. The processor that realizes the system control circuit 123 is similar to that described above, and therefore a description thereof will be omitted.

[0028] The memory 125 stores various programs related to the system control functions executed in the system control circuit 123, various imaging protocols, imaging conditions including a plurality of imaging parameters that define the imaging protocols, etc. The memory 125 also stores the acquisition function 33, the identification function 35, and the generation function 37 realized by the processing circuitry 15 in the form of programs executable by a computer.

[0029] The memory 125 also stores various data acquired by the acquisition function 33, various data used in the processes performed by the identification function 35 and the generation function 37, MR images generated by the generation function 37, various data generated in the process of generating the MR images, etc. The various data stored in the memory 125 will be described later. The memory 125 also stores MR data acquired by scanning the subject P and an algorithm for reconstructing an MR image based on the MR data.

[0030] The memory 125 may store various data received via a communication interface (not shown). For example, the memory 125 stores information about an examination order for the subject P (such as a region to be imaged, a purpose of the examination, etc.) received from an information processing system in a medical institution, such as a Radiology Information System (RIS).

[0031] The memory 125 is realized by, for example, a semiconductor memory element such as a ROM, a RAM, or a flash memory, a hard disk drive (HDD), a solid state drive (SSD), an optical disk, etc. The memory 125 may also be realized by a drive device that reads and writes various information from and to a portable storage medium such as a CD (Compact Disc)-ROM drive, a DVD (Digital Versatile Disc) drive, or a flash memory.

[0032] The input interface 127 accepts various instructions (e.g., a power-on instruction) and information input from an operator. The input interface 127 may be realized by, for example, a trackball, a switch button, a mouse, a keyboard, a touchpad that performs input operations by touching the operation surface, a touchscreen that integrates a display screen and a touchpad, a non-contact input circuit using an optical sensor, and a voice input circuit. The input interface 127 is connected to the processing circuitry 131 and converts input operations received from the operator into electrical signals and outputs them to the processing circuitry 131. Note that, in this specification, the input interface 127 is not limited to those having physical operation components such as a mouse and a keyboard. For example, an electrical signal processing circuit that receives electrical signals corresponding to input operations from an external input device provided separately from the MRI apparatus 100 and outputs the electrical signals to a control circuit is also included as an example of the input interface 127.

[0033] The input interface 127 inputs an FOV in response to a user instruction for the pre-scan image displayed on the display 129. Specifically, the input interface 127 inputs an FOV in response to a user instruction to set a range in a locator image displayed on the display 129. The input interface 127 also inputs various imaging parameters related to the scan in response to a user instruction based on an examination order.

[0034] The display 129, under the control of the processing circuitry 131 or the system control circuitry 123, displays various GUIs (Graphical User Interfaces), MR images generated by the processing circuitry 131, final images generated by the generation function 37, etc. The display 129 also displays various information related to imaging parameters for scans and image processing. The display 129 is realized by, for example, a CRT display, a liquid crystal display, an organic EL display, an LED display, a plasma display, or any other display or monitor known in the art.

[0035] The processing circuit 131 is realized by, for example, the above-mentioned processor. The processing circuit 131 includes an acquisition function 33, a specification function 35, a generation function 37, etc. The processing circuits 131 that realize the acquisition function 33, the specification function 35, and the generation function 37, respectively, correspond to an acquisition unit, a specification unit, and a generation unit. Each function, such as the acquisition function 33, the specification function 35, and the generation function 37, is stored in the memory 125 in the form of a program executable by a computer. For example, the processing circuit 131 realizes the function corresponding to each program by reading and executing the program from the memory 125. In other words, the processing circuit 131 in a state in which each program has been read has each function, such as the acquisition function 33, the specification function 35, and the generation function 37.

[0036] In the above description, an example has been described in which the "processor" reads and executes a program corresponding to each function from memory 125, but the embodiment is not limited to this. If the processor is, for example, a CPU, the processor realizes the function by reading and executing a program stored in memory 125. On the other hand, if the processor is an ASIC, instead of storing a program in memory 125, the function is directly incorporated into the processor circuit as a logic circuit. Note that each processor in this embodiment is not limited to being configured as a single circuit per processor, and multiple independent circuits may be combined to configure a single processor and realize its function. Furthermore, while the description has been given assuming that a single storage circuit stores a program corresponding to each processing function, multiple storage circuits may be distributed and the processing circuit 131 may read the corresponding program from each individual storage circuit.

[0037] The processing circuitry 131 acquires first coil sensitivity maps for the multiple coils using the acquisition function 33. Specifically, the acquisition function 33 estimates the sensitivity map for each of the multiple coils based on MR data acquired by each of the multiple coils in the receive coil 117. More specifically, the acquisition function 33 estimates the sensitivity map for each of the multiple coils using ESPIRiT (Uecker M, Lai P, Murphy MJ, et al.: ESPIRiT - an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med 2014; 71: 990-1001) using ACS for the MR data. As a result, the acquisition function 33 estimates sensitivity maps for the multiple coils (hereinafter referred to as estimated sensitivity maps) based on the MR data acquired in a thinned-out manner. The estimated sensitivity map includes an intensity image showing the distribution of sensitivity in the multiple coils using grayscale values ​​and a phase image corresponding to the intensity image. The method for estimating the sensitivity map is not limited to the above-mentioned ESPIRiT, and various known techniques can be applied.

[0038] Next, the processing circuit 131 causes the acquisition function 33 to shift the phase of the estimated sensitivity map for the multiple coils based on the phase image in the estimated sensitivity map for the coil identified by the identification function 35 among the multiple coils (hereinafter referred to as the first identified coil). As a result, the acquisition function 33 acquires the first coil sensitivity map for the multiple coils. That is, the first coil sensitivity map includes a phase image obtained by shifting the phase of a phase image in an estimated sensitivity map for a coil other than the first identified coil so as to make the phase of the phase image in the estimated sensitivity map for the first identified coil (hereinafter referred to as the first identified phase image) uniform for the multiple coils. In other words, the intensity image showing the sensitivities of the multiple coils in grayscale values ​​in the first coil sensitivity map is the same as the intensity image in the estimated sensitivity map, but the phase image corresponding to the intensity image in the first coil sensitivity map corresponds to a phase image obtained by shifting the phase of the phase image in the estimated sensitivity map so as to make the phase in the first identified phase image uniform. Identification of the first identified coil by the identification function 35 will be described later.

[0039] The processing circuit 131 acquires, via the acquisition function 33, a second coil sensitivity map for the multiple coils, which has a different phase from the phase image in the first coil sensitivity map. Specifically, the acquisition function 33 shifts the phase of the phase image in the estimated sensitivity map for the multiple coils, using as a reference the phase image in the estimated sensitivity map for a coil (hereinafter referred to as the second specified coil) that is different from the first specified coil and that is identified by the identification function 35. In this way, the acquisition function 33 acquires a second coil sensitivity map for the multiple coils. Identification of the second specified coil by the identification function 35 will be described later. As described above, the acquisition function 31 acquires the first coil sensitivity map and the second coil sensitivity map by changing the phase in the phase image of the sensitivities of the multiple coils, using the sensitivity of one of the multiple coils as a reference. In other words, the first coil sensitivity map and the second coil sensitivity map differ in that the reference phase image is different. In other words, the first coil sensitivity map and the second coil sensitivity map have the same intensity image for each of the multiple coils, but different phase values ​​in the phase image.

[0040] Note that the processing circuit 131 may further acquire, by the acquisition function 33, an odd number of coil sensitivity maps for the multiple coils, each having a different phase from the first coil sensitivity map and the second coil sensitivity map. For example, the acquisition function 33 shifts the phase of the estimated sensitivity map for the multiple coils using as a reference a phase image in the estimated sensitivity map for the coil identified by the identification function 35 (hereinafter referred to as the third identified coil). In this way, the acquisition function 33 acquires a third coil sensitivity map for the multiple coils. Similarly, the acquisition function 33 acquires multiple coil sensitivity maps based on the coil identified by the identification function 35. For example, if the number of coils is eight, the acquisition function 33 may acquire eight coil sensitivity maps based on each of the eight coils.

[0041] The processing circuitry 131 uses the identification function 35 to identify one coil that serves as a reference for phase change based on intensity images of multiple sensitivity maps (estimated sensitivity maps) corresponding to multiple coils or intensity images reconstructed based on MR data. Specifically, the identification function 35 identifies multiple coils in multiple intensity images (hereinafter referred to as estimated sensitivity intensity images) in multiple estimated sensitivity maps corresponding to multiple coils, for example, by singular value decomposition, in order of the number of signal values ​​(hereinafter referred to as multi-signal value order). The multi-signal order corresponds to the order of highest singular value. Since known techniques such as coil compression can be applied to singular value decomposition, a description thereof will be omitted. Note that the target image of singular value decomposition may be an intensity image (contrast image) for each coil reconstructed from MR data by the generation function 37.

[0042] Specifically, the processing circuit 131 uses the identification function 35 to identify, based on the results of singular value decomposition, the coil corresponding to the estimated sensitivity intensity image having the greatest signal value among the multiple estimated sensitivity intensity images as the first identified coil. The identification function 35 then identifies, as the second identified coil, the coil corresponding to the estimated sensitivity intensity image having the second greatest signal value among the multiple estimated sensitivity intensity images. The identification function 35 then identifies, as the third identified coil, the coil corresponding to the estimated sensitivity intensity image having the third greatest signal value among the multiple estimated sensitivity intensity images. The identification function 35 then identifies coils in the same manner.

[0043] The processing circuitry 131 generates a first image based on the first coil sensitivity map and MR data for the multiple coils using the generation function 37. Specifically, the generation function 37 reconstructs an image corresponding to each of the multiple coils (hereinafter referred to as a coil image) based on the MR data for each of the multiple coils. Since the MR data is acquired by thinning-out acquisition of the subject P, the coil image is an image with aliasing. The generation function 37 generates a single first image without aliasing by complex unfolding processing based on the multiple coil images corresponding to the multiple coils and the first coil sensitivity map. Known techniques such as FISTA (Fast Unfolding Algorithm) and ISTA (Iterative Shrinkage Soft-thresholding Algorithm) can be applied to the complex unfolding processing, and therefore a description thereof will be omitted.

[0044] The processing circuit 131 generates a second image based on the second coil sensitivity map, the first coil sensitivity map, and the first image using the generation function 37. For example, the generation function 37 decomposes the first image according to the multiple coils based on the first image and the first coil sensitivity map to generate decomposed images. The decomposed images correspond to each of the multiple coils and are MR images without aliasing that reflect the sensitivity of each of the multiple coils. Since known techniques can be applied to the decomposition process for generating the decomposed images obtained by decomposing the first image, a description thereof will be omitted. The generation function 37 generates the second image by synthesizing multiple decomposed images corresponding to the multiple coils using the second coil sensitivity map (hereinafter referred to as coil synthesis).

[0045] The processing circuitry 131 generates a final image based on the first image and the second image using the generation function 37. For example, the generation function 37 performs an interpolation process on the first image to generate a first interpolated image. The generation function 37 performs an interpolation process on the second image to generate a second interpolated image. The interpolation process is, for example, a process (Zoom) that achieves high resolution using complex interpolation or the like, and corresponds to, for example, super-resolution processing. Known techniques can be applied to the super-resolution processing, such as linear interpolation of pixel values ​​of adjacent pixels or zero-filling in k-space, so a description thereof will be omitted.

[0046] The processing circuit 131 generates a final image based on the first interpolated image and the second interpolated image using the generation function 37. Specifically, the processing circuit 131 generates the final image by performing statistical processing on the first interpolated image and the second interpolated image using the generation function 37. More specifically, the generation function 37 generates the final image by calculating the average of two pixel values ​​of two pixels at corresponding positions in the first interpolated image and the second interpolated image, or by selecting the maximum value or median value of the two pixel values, as the statistical processing.

[0047] Furthermore, if acquisition function 33 further acquires an odd number of coil sensitivity maps for multiple coils that are out of phase with the first and second coil sensitivity maps, processing circuit 131 causes generation function 37 to generate an odd number of images based on the odd number of coil sensitivity maps, the first coil sensitivity map, and the first image. Next, generation function 37 generates a final image based on the first image, the second image, and the odd number of images by selecting the median value of the odd number of pixel values ​​of corresponding odd number of pixels in the first image, the second image, and the odd number of images.

[0048] The image generation process executed by the MRI apparatus 100 of this embodiment configured as described above will be described with reference to Figures 2 to 18. The image generation process is a process for reducing artifacts that occur due to abrupt phase changes and generating, for example, a super-resolution image as a final image. For the sake of concreteness, it is assumed below that the number of coils in the receiver coils 117 is eight, and that the number of coils identified by the identification function 35 is three.

[0049] Fig. 2 is a flowchart showing an example of the procedure of the image generation process, and Fig. 3 is a diagram showing an example of the relationship between various processes in the image generation process and data related to the various processes.

[0050] (Image generation processing) (Step S201) The imaging control circuit 121 executes thinning-out imaging of the subject P (Pr1). As a result, the processing circuit 131, using the acquisition function 33, acquires MR data DA1 related to each of the plurality of coils.

[0051] (Step S202) The processing circuit 131 estimates an estimated sensitivity map for each of the multiple coils using, for example, ESPIRiT, based on the thinned-out MR data DA1 acquired by the acquisition function 33 (Pr2). As a result, the acquisition function 33 generates multiple estimated sensitivity maps DA2 corresponding to the multiple coils. At this time, the identification function 35 identifies three coils in order of multiple signals, i.e., a first identified coil, a second identified coil, and a third identified coil, by singular value decomposition of the estimated sensitivity intensity image in the estimated sensitivity map DA2. The identification function 35 may also identify the three coils in order of multiple signals by singular value decomposition of the coil image DA4. At this time, step S204 is executed before step S203.

[0052] 4 is a diagram showing an example of the estimated sensitivity intensity image ESI. The identification function 35 performs singular value decomposition on each estimated sensitivity intensity image ESI, and identifies the first specified coil, the second specified coil, and the third specified coil in the order of the multiple signals based on the result of the singular value decomposition.

[0053] (Step S203) The processing circuit 131 generates a first coil sensitivity map DA3 based on the multiple estimated sensitivity maps DA2, using the estimated sensitivity map corresponding to a specific coil as a reference, using the acquisition function 33. Specifically, the acquisition function 33 shifts the phases of the phase images for the multiple coils based on the phase image of the estimated sensitivity map corresponding to the first specific coil (hereinafter referred to as the first phase image) (Pr3). As a result, the acquisition function 33 generates the first coil sensitivity map DA3.

[0054] 5 is a diagram showing an example of multiple phase images PI11 in the first coil sensitivity map DA3. As shown in FIG. 5, the first phase image PI11 has a uniform value due to the phase shift. In other words, the phase shift corresponds to shifting the phases in the multiple phase images in the estimated sensitivity map so as to make the first phase image PI11 corresponding to the identified first specified coil uniform.

[0055] (Step S204) The processing circuit 131 reconstructs, using the generation function 37, multiple coil images DA4 corresponding to the multiple coils based on the MR data DA1 (Pr4). FIG. 6 is a diagram showing an example of an intensity image CIM in the multiple coil images DA4. As shown in FIG. 6, the intensity image in the multiple coil images DA4 has aliasing artifacts due to thinned imaging. FIG. 7 is a diagram showing an example of a phase image CIP in the multiple coil images DA4. The multiple coil images DA4 shown in FIGS. 6 and 7 are used to generate a first image DA5. Note that the processing in this step can be performed at any stage after step S201.

[0056] (Step S205) The processing circuit 131 generates a first image DA5 based on a plurality of coil images DA4 and a first coil sensitivity map DA3 using the generation function 37. Specifically, the generation function 37 executes a complex expansion process such as FISTA using the plurality of coil images DA4 and the first coil sensitivity map DA3 (Pr5). As a result, the generation function 37 generates a first image (DA5). FIG. 8 is a diagram showing an example of the first image DA5. As shown in FIG. 8, aliasing has been eliminated in the first image DA5.

[0057] (Step S206) The processing circuit 131 uses the generation function 37 to decompose the first image DA5 using the first coil sensitivity map DA3 (Pr6). As a result, the generation function 37 generates multiple decomposed images DA6 corresponding to the multiple coils. FIG. 9 is a diagram showing an example of an intensity image DIM in the multiple decomposed images DA6 corresponding to the multiple coils. The intensity image DIM shown in FIG. 9 has reduced aliasing artifacts compared to the intensity image CIM shown in FIG. 6. FIG. 10 is a diagram showing an example of a phase image DIP in the multiple decomposed images DA6 corresponding to the multiple coils. The multiple decomposed images DA6 shown in FIGS. 9 and 10 are used to generate a second image.

[0058] (Step S207) The processing circuit 131 uses the generation function 37 to generate a second coil sensitivity map DA7, which has a different phase from the first coil sensitivity map DA3, based on the first coil sensitivity map DA3. Specifically, the generation function 37 shifts the phases of the phase images for the multiple coils in the first coil sensitivity map DA3 using a phase image (hereinafter referred to as the second phase image) PI22 corresponding to the second specific coil as a reference (Pr7). As a result, the acquisition function 33 generates the second coil sensitivity map DA7.

[0059] Fig. 11 is a diagram showing an example of a plurality of phase images PI2 in the second coil sensitivity map DA7. As shown in Fig. 11, the second phase image PI22 shown in Fig. 5 has a uniform value due to the phase shift. In other words, the phase shift corresponds to shifting the phases of the plurality of phase images in the first coil sensitivity map DA3 so as to make the second phase image PI22 in the first coil sensitivity map DA3 uniform.

[0060] The processing circuit 131 uses the generation function 37 to generate a third coil sensitivity map DA8, which has a different phase from the first coil sensitivity map DA3 and the second coil sensitivity map DA7, based on the second coil sensitivity map DA7. Specifically, the generation function 37 shifts the phases of the phase images for the multiple coils in the second coil sensitivity map DA7 using a phase image PI33 corresponding to a third specific coil (hereinafter referred to as the third phase image) as a reference (Pr8). As a result, the acquisition function 33 generates the third coil sensitivity map DA8.

[0061] Fig. 12 is a diagram showing an example of a plurality of phase images PI3 in the third coil sensitivity map DA8. As shown in Fig. 12, the third phase image PI33 shown in Fig. 11 has a uniform value due to the phase shift. In other words, the phase shift corresponds to shifting the phases of the plurality of phase images in the second coil sensitivity map DA7 so as to make the third phase image PI33 in the second coil sensitivity map DA7 uniform.

[0062] (Step S208) The processing circuit 131 generates a second image DA9 based on the decomposed image DA6 and the second coil sensitivity map DA7 (Pr9) using the generation function 37. Specifically, the generation function 37 performs coil synthesis on the decomposed image DA6 using the second coil sensitivity map DA7 to generate the second image DA9.

[0063] Fig. 13 is a diagram showing an example of a coil-combined second image DA9. The difference between the second image DA9 shown in Fig. 13 and the first image DA5 shown in Fig. 8 is that the phase image PI9 in the second image DA9 and the phase image PI5 in the first image DA5 differ due to the influence of the phase shift.

[0064] The processing circuit 131 generates a third image DA10 (Pr10) based on the decomposed image DA6 and the third coil sensitivity map DA8 using the generation function 37. Specifically, the generation function 37 performs coil synthesis on the decomposed image DA6 using the third coil sensitivity map DA8 to generate the third image DA10.

[0065] Fig. 14 is a diagram showing an example of a coil-combined third image DA10. The difference between the third image DA10 shown in Fig. 14, the first image DA5 shown in Fig. 8, and the second image DA9 shown in Fig. 13 is that the phase image PI10 in the third image DA10, the phase image PI9 in the second image DA9, and the phase image PI5 in the first image DA5 are different due to the influence of the phase shift.

[0066] (Step S209) The processing circuit 131 executes interpolation processing Pr11 on the first image DA5 using the generation function 37 to generate a first interpolated image DA11. The generation of the first interpolated image can be performed at any stage after the generation of the first image DA5.

[0067] Fig. 15 is a diagram showing an example of the first interpolated image DA11. As shown in Fig. 15, an artifact A occurs in the magnitude image MI11 of the first interpolated image DA11. As shown in Fig. 15, the position where the artifact A occurs corresponds to the position where an abrupt phase change occurs in the phase image PI11 of the first interpolated image DA11 (hereinafter referred to as the abrupt phase change position).

[0068] The processing circuit 131 uses the generation function 37 to perform interpolation processing Pr12 on the second image DA9 to generate a second interpolated image DA12. The generation of the second interpolated image can be performed at any stage after the generation of the second image DA9.

[0069] Fig. 16 is a diagram showing an example of the second interpolated image DA12. As shown in Fig. 16, an artifact A occurs in the magnitude image MI12 of the second interpolated image DA12. As shown in Fig. 16, the position where the artifact A occurs corresponds to the position where a steep phase change occurs in the phase image PI12 of the second interpolated image DA12.

[0070] The processing circuit 131 uses the generation function 37 to perform interpolation processing Pr13 on the third image DA10 to generate a third interpolated image DA13. The generation of the third interpolated image can be performed at any stage after the generation of the third image DA10.

[0071] Fig. 17 is a diagram showing an example of the third interpolated image DA13. As shown in Fig. 17, an artifact A occurs in the magnitude image MI13 of the third interpolated image DA13. As shown in Fig. 17, the position where the artifact A occurs corresponds to the position where a steep phase change occurs in the phase image PI13 of the third interpolated image DA13.

[0072] 15 to 17, the position where artifact A occurs varies depending on the effect of the phase shift. Also, as shown in Fig. 15 to 17, the pixel value of artifact A is darker, i.e., smaller, than the pixel values ​​around artifact A.

[0073] (Step S210) The processing circuit 131 causes the generation function 37 to perform statistical processing on the first interpolated image DA11, the second interpolated image DA12, and the third interpolated image DA13 (Pr14). As a result, the generation function 37 generates a final image DA14. Specifically, the generation function 37 selects the maximum or median of three pixel values ​​at the same position in the intensity image MI11 in the first interpolated image DA11, the intensity image MI12 in the second interpolated image DA12, and the intensity image MI13 in the third interpolated image DA13. The generation function 37 selects the pixel value for all pixels in the intensity images and generates the final image DA14 using the selected pixel value. By selecting pixel values ​​in this way, pixel values ​​corresponding to artifact A are not selected.

[0074] Fig. 18 is a diagram showing an example of a final image DA14. As shown in Fig. 18, in the final image DA14, the artifact A in the magnitude image MI11 shown in Fig. 15, the artifact A in the magnitude image MI12 shown in Fig. 16, and the artifact A in the magnitude image MI13 shown in Fig. 17 have been removed.

[0075] The system control circuit 123 displays the generated final image DA14 on the display 129. The system control circuit 123 also stores the generated final image DA14 in the memory 125. This completes the image generation process.

[0076] The MRI apparatus 100 according to the embodiment described above acquires a first coil sensitivity map DA3 relating to the multiple coils and a second coil sensitivity map DA7 relating to the multiple coils and having a different phase from the first coil sensitivity map DA3, generates a first image DA5 based on the first coil sensitivity map DA3 and MR data DA1 relating to the multiple coils, generates a second image DA9 based on the second coil sensitivity map DA7, the first coil sensitivity map DA3, and the first image DA5, and generates a final image DA14 based on the first image DA5 and the second image DA9.

[0077] Specifically, the MRI apparatus 100 performs an interpolation process Pr11 on the first image DA5 to generate a first interpolated image DA11, performs an interpolation process Pr12 on the second image DA9 to generate a second interpolated image DA12, and generates a final image DA14 based on the first interpolated image DA11 and the second interpolated image DA12. More specifically, the MRI apparatus 100 performs a statistical process Pr14 on the first interpolated image DA11 and the second interpolated image DA12 to generate the final image DA14. For example, the MRI apparatus 100 performs the statistical process Pr14 by calculating the average of two pixel values ​​at two pixels at corresponding positions in the first interpolated image DA11 and the second interpolated image DA12, or by selecting the maximum or median of the two pixel values, thereby generating the final image DA14.

[0078] In addition, the MRI apparatus 100 further acquires an odd number of coil sensitivity maps (e.g., a third coil sensitivity map DA8) for multiple coils that are out of phase with the first coil sensitivity map DA3 and the second coil sensitivity map DA7, generates an odd number of images (e.g., a third image DA10) based on the odd number of coil sensitivity maps, the first coil sensitivity map DA3, and the first image DA5, and generates a final image DA14 based on the first image DA5, the second image DA9, and the odd number of images by selecting the median of the odd number of pixel values ​​at the corresponding odd number of pixels for the first image DA5, the second image DA9, and the odd number of images.

[0079] Furthermore, the MRI apparatus 100 estimates estimated sensitivity maps DA2 for the plurality of coils based on the MR data DA1 acquired in a thinned-out manner, and acquires a first coil sensitivity map DA3 based on the estimated estimated sensitivity maps DA2.

[0080] For these reasons, the MRI apparatus 100 according to the embodiment can shift the phase in the sensitivity map to move the position where artifact A occurs in multiple phase images after coil synthesis according to different phase shifts. Therefore, the MRI apparatus 100 can generate the final image DA14 while avoiding the position where the phase changes abruptly, which is the position where artifact A occurs.

[0081] From the above, according to the present MRI apparatus 100, it is possible to reduce the artifact A or effectively remove the artifact A, thereby generating, for example, a final image DA14 with increased resolution. Therefore, according to the present MRI apparatus 100, it is possible to improve the image quality of the final image DA14, and to improve the efficiency of examination and diagnosis for the subject P. Note that, as a modification of this embodiment, the processing by the specific function 85 may be omitted. Even in this case, it is possible to achieve the same effect as in the embodiment.

[0082] The MRI apparatus 100 also acquires a first coil sensitivity map DA3 and a second coil sensitivity map DA7 by changing the phase in the sensitivity phase image of the multiple coils based on the sensitivity of one of the multiple coils as a reference. At this time, the MRI apparatus 100 identifies one coil that serves as a reference for the phase change based on the intensity images of the multiple estimated sensitivity maps corresponding to the multiple coils or the intensity image of the coil image reconstructed based on the MR data.

[0083] For these reasons, the MRI apparatus 100 according to the embodiment does not need to generate a coil sensitivity map by performing phase shifts on all coils. Instead, the final image DA14 can be generated using, for example, the first image DA5, the second image DA9, the third image DA10, etc., in descending order of the effect of the phase shift. This allows the MRI apparatus 100 to efficiently move the position of abrupt phase changes while reducing the calculation cost of the image generation process. Therefore, the MRI apparatus 100 can reduce various expenses related to calculation costs and shorten calculation time. Therefore, the MRI apparatus 100 can further improve the efficiency of examinations and diagnoses for the subject P while improving the image quality of the final image DA14.

[0084] When the technical idea of ​​the embodiments is realized by an image generation method, the image generation method acquires a first coil sensitivity map DA3 related to multiple coils and a second coil sensitivity map DA7 related to the multiple coils and having a different phase from the first coil sensitivity map DA3, generates a first image DA5 based on the first coil sensitivity map DA3 and MR data DA1 related to the multiple coils, generates a second image DA9 based on the second coil sensitivity map DA7, the first coil sensitivity map DA3, and the first image DA5, and generates a final image DA14 based on the first image DA5 and the second image DA9. The steps and effects of the image generation process related to this image generation method are the same as those described in the embodiments, so description thereof will be omitted.

[0085] When the technical idea of ​​the embodiment is realized by an image generation program, the image generation program causes a computer to acquire a first coil sensitivity map DA3 related to multiple coils and a second coil sensitivity map DA7 related to multiple coils and having a different phase from the first coil sensitivity map DA3, generate a first image DA5 based on the first coil sensitivity map DA3 and MR data DA1 related to the multiple coils, generate a second image DA9 based on the second coil sensitivity map DA7, the first coil sensitivity map DA3, and the first image DA5, and generate a final image DA14 based on the first image DA5 and the second image DA9.

[0086] For example, the image generation process can be realized by installing an image generation program in a computer in a modality such as the MRI apparatus 100 or a PACS server, and expanding the program in memory. In this case, the program that can cause the computer to execute the method can also be stored and distributed on a storage medium such as a magnetic disk (hard disk, etc.), an optical disk (CD-ROM, DVD, etc.), or a semiconductor memory. The procedure and effect of the image generation process using the image generation program are the same as those in the embodiment, so a description thereof will be omitted.

[0087] According to at least one of the embodiments described above, it is possible to reduce artifacts that occur due to abrupt phase changes.

[0088] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0089] 33 Acquisition Function 35 Specific Functions 37 Generation function 100 Magnetic resonance imaging device 101 Static Magnetic Field Magnet 103 Gradient magnetic field coil 105 Gradient magnetic field power supply 107 Sleeper 109 Bed control circuit 111 Bore 113 Transmitting circuit 115 Transmitting Coil 117 Receiving Coil 119 Receiving circuit 121 Imaging control circuit 123 System Control Circuit 125 memory 127 Input Interface 129 Display 131 Processing circuit

Claims

1. an acquisition unit that acquires a first coil sensitivity map for a plurality of coils and a second coil sensitivity map for the plurality of coils, the second coil sensitivity map being out of phase with the first coil sensitivity map; a generator that generates a first image including the first coil sensitivity map and magnetic resonance data related to the plurality of coils, generates a second image including the second coil sensitivity map, the first coil sensitivity map, and the first image, and generates a final image including the first image and the second image; Equipped with The generation unit performing an interpolation process on the first image to generate a first interpolated image; performing an interpolation process on the second image to generate a second interpolated image; generating the final image including the first interpolated image and the second interpolated image; Magnetic resonance imaging device.

2. the generation unit performs statistical processing on the first interpolated image and the second interpolated image to generate the final image.

2. The magnetic resonance imaging apparatus according to claim 1.

3. the generation unit generates the final image by calculating an average of two pixel values ​​of two pixels at corresponding positions in the first interpolated image and the second interpolated image, or by selecting a maximum value or a median value of the two pixel values, as the statistical processing.

3. The magnetic resonance imaging apparatus according to claim 2.

4. the acquisition unit further acquires an odd number of coil sensitivity maps for the plurality of coils, the maps being out of phase with the first coil sensitivity map and the second coil sensitivity map; The generation unit generating an odd number of images based on the odd number of coil sensitivity maps, the first coil sensitivity map, and the first image; generating the final image based on the first image, the second image, and the odd number of images by selecting a median value among odd number of pixel values ​​of corresponding odd number of pixels for the first image, the second image, and the odd number of images; 2. The magnetic resonance imaging apparatus according to claim 1.

5. the acquisition unit estimates sensitivity maps for a plurality of coils based on the thinned-out collected magnetic resonance data, and acquires the first coil sensitivity map based on the estimated sensitivity maps.

5. A magnetic resonance imaging apparatus according to claim 1.

6. An acquisition unit that acquires a first coil sensitivity map for a plurality of coils and a second coil sensitivity map for the plurality of coils, the second coil sensitivity map having a different phase from the first coil sensitivity map; a generator that generates a first image including the first coil sensitivity map and magnetic resonance data related to the plurality of coils, generates a second image including the second coil sensitivity map, the first coil sensitivity map, and the first image, and generates a final image including the first image and the second image; Equipped with the acquisition unit acquires the first coil sensitivity map and the second coil sensitivity map by changing the phase in a phase image of the sensitivities of the plurality of coils based on the sensitivity of one of the plurality of coils. Magnetic resonance imaging device.

7. an identification unit that identifies the one coil that serves as a reference for the phase change based on intensity images of a plurality of sensitivity maps corresponding to the plurality of coils or an intensity image reconstructed based on the magnetic resonance data; 7. The magnetic resonance imaging apparatus according to claim 6.

8. obtaining a first coil sensitivity map for a plurality of coils and a second coil sensitivity map for the plurality of coils, the second coil sensitivity map being out of phase with the first coil sensitivity map; generating a first image including the first coil sensitivity map and the magnetic resonance data for the plurality of coils; generating a second image including the second coil sensitivity map, the first coil sensitivity map, and the first image; generating a final image including the first image and the second image; Equipped with generating the final image performing an interpolation process on the first image to generate a first interpolated image; performing an interpolation process on the second image to generate a second interpolated image; generating the final image including the first interpolated image and the second interpolated image; Image generation method.

9. A first coil sensitivity map for a plurality of coils and a second coil sensitivity map for the plurality of coils, the second coil sensitivity map being out of phase with the first coil sensitivity map, are obtained; generating a first image including the first coil sensitivity map and the magnetic resonance data for the plurality of coils; generating a second image including the second coil sensitivity map, the first coil sensitivity map, and the first image; generating a final image including the first image and the second image; Equipped with and acquiring the first coil sensitivity map and the second coil sensitivity map by changing the phase in a phase image of the sensitivities of the plurality of coils based on the sensitivity of one coil of the plurality of coils. Image generation method.

10. On the computer, obtaining a first coil sensitivity map for a plurality of coils and a second coil sensitivity map for the plurality of coils, the second coil sensitivity map being out of phase with the first coil sensitivity map; generating a first image including the first coil sensitivity map and the magnetic resonance data for the plurality of coils; generating a second image including the second coil sensitivity map, the first coil sensitivity map, and the first image; generating a final image including the first image and the second image; Realize this, generating the final image performing an interpolation process on the first image to generate a first interpolated image; performing an interpolation process on the second image to generate a second interpolated image; generating the final image including the first interpolated image and the second interpolated image; Image generation program.

11. A computer comprising: obtaining a first coil sensitivity map for a plurality of coils and a second coil sensitivity map for the plurality of coils, the second coil sensitivity map being out of phase with the first coil sensitivity map; generating a first image including the first coil sensitivity map and the magnetic resonance data for the plurality of coils; generating a second image including the second coil sensitivity map, the first coil sensitivity map, and the first image; generating a final image including the first image and the second image; Realize this, and acquiring the first coil sensitivity map and the second coil sensitivity map by changing the phase in a phase image of the sensitivities of the plurality of coils based on the sensitivity of one coil of the plurality of coils. Image generation program.

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