JP7725199B2 - Image generation device, image generation method, and image generation program - Google Patents

Description

The embodiments disclosed in this specification and drawings relate to an image generation device, an image generation method, and an image generation program.

A common issue with imaging using magnetic resonance imaging (MRI) devices is image aliasing, which occurs due to an insufficient sampling rate for the received magnetic resonance (MR) signals (in other words, an insufficient field of view, which is equivalent to the reciprocal of the sampling interval). Techniques to address this issue include setting a low-pass filter that matches the sampling rate and oversampling the MR signals.

However, when the low-pass filter used in this technology is applied to MR signals in scans where the readout direction changes, such as radial scans, the amount of signal cut by the low-pass filter varies depending on the readout direction. As a result, the consistency of MR data arranged in k-space between different readout directions is lost. This causes a problem in that MR images generated in scans where the readout direction changes suffer from noise, such as line-like artifacts called streaks, resulting in reduced image quality. While sufficient oversampling is required to eliminate this degradation in image quality, there is a problem in that sufficient oversampling cannot be achieved due to performance limitations of MRI systems (e.g., upper limits on the sampling period and data volume).

Japanese Patent Application Laid-Open No. 2020-115967

One of the problems that the embodiments disclosed in this specification and drawings attempt to solve is to generate magnetic resonance images with improved image quality. However, the problems that the embodiments disclosed in this specification and drawings attempt to solve 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.

An image generating device according to an embodiment includes an acquisition unit, an unfolded data generation unit, a complementary data generation unit, and an image generation unit. The acquisition unit acquires magnetic resonance data collected in multiple readout directions, including a first readout direction and a second readout direction intersecting the first readout direction, and multiple sensitivity maps corresponding to multiple coil elements used to collect the magnetic resonance data. The unfolded data generation unit generates unfolded data in which folding is unfolded in one-dimensional image space by performing a one-dimensional Fourier transform along the readout direction for each readout direction using the magnetic resonance data and the sensitivity map for each readout direction. The complementary data generation unit generates complementary data in which data is complementary to the magnetic resonance data by performing a one-dimensional inverse Fourier transform along the readout direction on the unfolded data for each readout direction. The image generation unit generates a magnetic resonance image based on the complementary data.

FIG. 1 is a block diagram illustrating an example of an image generating apparatus according to an embodiment. FIG. 2 is a block diagram showing an example of a magnetic resonance imaging apparatus according to an embodiment. FIG. 3 is a diagram showing an example of the configuration of a receiving circuit according to the embodiment. FIG. 4 is a diagram showing an example of a trajectory in k-space relating to readout of MR signals in a main scan according to the embodiment. FIG. 5 is a flowchart showing an example of a procedure of an image generation process according to the embodiment. FIG. 6 is a diagram showing an example of MR data in the readout direction and sampling points in k-space according to the embodiment. FIG. 7 is a diagram showing an example of a one-dimensional image in a one-dimensional image space before being developed by a plurality of sensitivity maps in the readout direction ROD according to the embodiment. FIG. 8 is a diagram showing an example of unfolded data obtained by performing a folding unfolding process using a plurality of sensitivity maps according to the embodiment. 9 is a diagram showing an example of complementary data generated from the MR data shown in FIG. 6 according to the embodiment. FIG. 10 is a diagram showing an example of an MR image generated from MR data by an existing reconstruction method as a comparative example, and an MR image generated based on complementary data by image generation processing in this embodiment.

Embodiments of an image generation device, image generation method, and image generation program will be described in detail below with reference to the drawings. FIG. 1 is a block diagram showing an example of an image generation device 1. The image generation device 1 is installed, for example, in a modality equipped with the various functions of the image generation device 1, or in a server within a hospital. Note that the various functions of the image generation device 1 may also be installed in a server of a medical image management system (hereinafter referred to as PACS (Picture Archiving and Communication Systems)) or a server of a hospital information system (hereinafter referred to as HIS (Hospital Information System)).

Modality may be, for example, a magnetic resonance imaging (MRI) device, a PET (positron emission tomography)-MRI device, or a SPECT (single photon emission computed tomography)-MRI device, or other MRI-related medical imaging diagnostic device. For the sake of concreteness, the following description will be made assuming that the image generating device 1 is mounted on an MRI device. In this case, the MRI device will have various functions in the processing circuitry 15.

(Embodiment)
2 is a diagram showing an example of an MRI apparatus 100 according to this embodiment. As shown in FIG. 2 , 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 13, an input interface 127, a display 129, a communication interface 11, and a processing circuit 15. Note that the image generating device 1 may further include the input interface 127 and the display 129 in addition to the communication interface 11, the memory 13, and the processing circuit 15.

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.

The gradient coil 103 is a hollow, approximately cylindrical coil and is placed on the inner surface of the cylindrical cooling vessel. The gradient coil 103 receives individual currents from the gradient power supply 105 to generate gradient magnetic fields whose field strength varies along the mutually orthogonal X, Y, and Z axes. The X, Y, and Z axis gradient magnetic fields generated by the gradient 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 the 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 spatial position. The frequency encoding gradient magnetic field is used to change the frequency of the MR signal according to spatial position.

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.

The bed 107 is a device equipped with a tabletop 1071 on which the subject P rests. Under the control of the bed control circuit 109, the bed 107 inserts the tabletop 1071 on which the subject P rests into the bore 111.

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 longitudinally, vertically, and, in some cases, horizontally.

Under the control of the imaging control circuit 121, the transmission circuit 113 supplies radio frequency pulses modulated at the Larmor frequency to the transmission coil 115. For example, the transmission circuit 113 includes an oscillator, phase selection unit, frequency conversion unit, amplitude modulation unit, and RF amplifier. The oscillator generates RF pulses at a resonance frequency specific to the target 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.

The transmitting coil 115 is an RF (Radio Frequency) coil placed inside the gradient magnetic field coil 103. The transmitting coil 115 generates RF pulses corresponding to a high-frequency magnetic field in response to the output from the transmitting circuit 113.

The receiving coil 117 is an RF coil placed inside the gradient magnetic field coil 103. The receiving coil 117 receives MR signals emitted from the subject P by a radio frequency magnetic field. The receiving coil 117 outputs the received MR signals to the receiving circuit 119. The receiving coil 117 is, for example, a coil array having one or more, typically multiple, coil elements. For the sake of concreteness, the receiving coil 117 will be described below as a coil array having multiple coil elements.

Note that the receive coil 117 may be composed of a single coil element. Also, while the transmit coil 115 and receive coil 117 are depicted as separate RF coils in FIG. 2, the transmit coil 115 and 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.

Under the control of the imaging control circuit 121, 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. 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 processed data to generate MR data. The receiving circuit 119 outputs the generated MR data to the imaging control circuit 121. For example, MR data is generated for each coil element and output to the imaging control circuit 121 together with a tag that identifies the coil element.

Figure 3 is a diagram showing an example of the receiving circuit 119. The receiving circuit 119 has, for example, a low-pass filter 191 and an A/D converter 193. In addition to the low-pass filter 191 and the A/D converter 193, the receiving circuit 119 may also be equipped with various circuits, such as a detector, that support the above-mentioned signal processing.

The cutoff frequency set by the setting function 153 is input to the low-pass filter 191 via the imaging control circuit 121. In other words, the passband of the low-pass filter 191 is set by the setting function 153. The cutoff frequency may also be input to the low-pass filter 191 directly from the processing circuit 15. The low-pass filter 191 filters the MR signal using the input cutoff frequency.

The sampling rate set by the setting function 153 is input to the A/D converter 193 via the imaging control circuit 121. That is, the sampling interval in the low-pass filter 191 is set by the setting function 153. The A/D converter 193 samples the MR signal that has passed through the low-pass filter 191 at a sampling timing that corresponds to the sampling rate. In this way, the A/D converter 193 generates MR data.

The imaging control circuit 121 controls the gradient magnetic field power supply 105, transmission circuit 113, reception circuit 119, etc. in accordance with the imaging protocol output from the processing circuit 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 current to the gradient magnetic field coil 103, the magnitude and duration of the radio frequency pulse supplied to the transmission coil 115 by the transmission circuit 113, the timing at which the radio frequency pulse is supplied to the transmission coil 115 by the transmission circuit 113, and the timing at which the MR signal is received by the reception coil 117. The imaging control circuit 121 drives the gradient magnetic field power supply 105, transmission circuit 113, reception circuit 119, etc. to image the subject P, and then receives MR data from the reception circuit 119 and stores the received MR data in the memory 13.

The imaging control circuit 121 collects MR data by executing a pulse sequence related to imaging. In this embodiment, the imaging performed corresponds to a scan that acquires multiple MR signals corresponding to multiple readout directions, including a first readout direction and a second readout direction that intersects the first readout direction.

Figure 4 shows an example of a trajectory kTra in k-space related to the readout of MR signals in a main scan. As shown in Figure 3, the main scan can be, for example, a two-dimensional radial acquisition R2D, a three-dimensional radial acquisition (stack-of-stars SOS, koosh-ball KB), a propeller (periodically rotated overlapping parallel lines with enhanced reconstruction) acquisition PRP, or another acquisition using two blades, such as BL2.

For the sake of concreteness, the following description will be given assuming that the main scan is a two-dimensional radial acquisition R2D. Hereinafter, two-dimensional radial acquisition R2D will be referred to simply as radial acquisition. The number of readouts in the radial acquisition performed as the main scan on subject P, i.e., the number of trajectories kTra in the readout direction, is set in advance prior to the main scan.

The imaging control circuit 121 collects MR data (hereinafter referred to as sensitivity data) related to the generation of each of the multiple sensitivity maps using any imaging technique. The multiple sensitivity maps correspond to the multiple coil elements in the receive coil 117 used to collect the MR data, and are equivalent to multiple images showing the sensitivity distribution of the coil elements. The sensitivity maps are expressed as complex data. The collection of sensitivity data is performed by the imaging control circuit 121, for example, in a pre-scan including a locator scan prior to the radial acquisition R2D as the main scan. The imaging control circuit 121 is realized, for example, by a processor.

The term "processor" refers to circuits such as a CPU, a GPU (Graphics Processing Unit), 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)).

The system control circuit 123 has hardware resources such as a processor (not shown), memory such as ROM (Read-Only Memory) and RAM (Random Access Memory), and controls the MRI apparatus 100 using its system control function. Specifically, the system control circuit 123 reads a system control program stored in memory, expands it on the memory, and controls each circuit of the MRI apparatus 100 in accordance with the expanded system control program.

For example, the system control circuit 123 reads an imaging protocol from the memory 13 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 also 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, so a description thereof will be omitted.

Memory 13 stores various programs related to system control functions executed by the system control circuit 123, various imaging protocols, imaging conditions including multiple imaging parameters that define the imaging protocols, etc. Memory 13 also stores a specific function 151, a setting function 153, an acquisition function 155, an expanded data generation function 157, a complementary data generation function 159, and an image generation function 161, which are realized by the processing circuit 15, in the form of programs executable by a computer.

The memory 13 also stores MR images generated by the image generation function 161 and prescan images generated by a prescan such as a locator scan. Prescan images include, for example, positioning images (also referred to as locator images) for setting the imaging field of view (hereinafter referred to as FOV (Field of View)) for the main scan, and sensitivity maps used to generate (reconstruct) MR images for the main scan. For example, the memory 13 stores multiple sensitivity maps corresponding to the multiple coil elements in the receive coil 117. The memory 13 also stores the FOV set in the locator image.

Memory 13 stores the sampling rate (also called the sampling frequency) or sampling interval used in A/D converter 193 for the main scan, which is performed after the pre-scan. Memory 13 also stores the cutoff frequency used in low-pass filter 191 for the main scan. Memory 13 stores MR data related to the main scan and an algorithm for reconstructing an MR image based on the MR data.

The memory 13 may also store various data received via the communication interface 11. For example, the memory 13 stores information about the examination order for subject P (such as the area to be imaged, the purpose of the examination, etc.) received from an information processing system within the medical institution, such as a Radiology Information System (RIS).

Memory 13 may be realized, for example, by semiconductor memory elements such as ROM, RAM, or flash memory, a hard disk drive (HDD), a solid state drive (SSD), or an optical disk. Memory 13 may also be realized by a drive device that reads and writes various information from and to portable storage media such as a CD (Compact Disc)-ROM drive, a DVD (Digital Versatile Disc) drive, or a flash memory.

The input interface 127 accepts various instructions (e.g., a power-on instruction) and information input from the operator. The input interface 127 may be realized, for example, by a trackball, switch buttons, 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 15 and converts input operations received from the operator into electrical signals and outputs them to the processing circuitry 15. Note that in this specification, the input interface 127 is not limited to those equipped with physical operating components such as a mouse and 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 these electrical signals to a control circuit is also included as an example of the input interface 127.

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

Under the control of the processing circuitry 15 or the system control circuitry 123, the display 129 displays various GUIs (Graphical User Interfaces), MR images generated by the processing circuitry 15, pre-scan images such as locator images, and the like. The display 129 also displays various information related to imaging parameters for the main scan and pre-scan, as well as image processing. The display 129 is realized by, for example, a CRT display, liquid crystal display, organic EL display, LED display, plasma display, or any other display, monitor, or other display device known in the art.

The communication interface 11 communicates data with, for example, an HIS or PACS. Any standard may be used for communication between the communication interface 11 and the hospital information system, such as HL7 (Heart Level 7), DICOM, or both. The communication interface 11 receives information related to the examination order for subject P (such as the area to be imaged and the purpose of the examination) received from an information processing system within the medical institution, such as an RIS. Furthermore, if the MRI apparatus 100 does not have an image generating device 1, the communication interface 11 in the image generating device 1 receives MR data from the MRI apparatus 100 or other device that images subject P during an examination of the subject P. At this time, the received MR data is stored in memory 13.

The processing circuit 15 is realized, for example, by the above-mentioned processor. The processing circuit 15 includes a specifying function 151, a setting function 153, an acquisition function 155, an expanded data generation function 157, a complementary data generation function 159, an image generation function 161, and the like. The processing circuits 15 that realize the specifying function 151, the setting function 153, the acquisition function 155, the expanded data generation function 157, the complementary data generation function 159, and the image generation function 161 respectively correspond to a specifying unit, a setting unit, an acquisition unit, an expanded data generation unit, a complementary data generation unit, and an image generation unit. Each function, such as the specifying function 151, the setting function 153, the acquisition function 155, the expanded data generation function 157, the complementary data generation function 159, and the image generation function 161, is stored in the memory 13 in the form of a computer-executable program. For example, the processing circuit 15 realizes the function corresponding to each program by reading and executing the program from the memory 13. In other words, when each program is loaded, the processing circuitry 15 has functions such as a specific function 151, a setting function 153, an acquisition function 155, an expanded data generation function 157, a complementary data generation function 159, and an image generation function 161.

In the above explanation, an example was described in which the "processor" reads and executes a program corresponding to each function from memory 13, but embodiments are 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 13. On the other hand, if the processor is an ASIC, instead of storing a program in memory 13, 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 form a single processor and realize its function. Furthermore, while the explanation was given assuming that a single memory circuit stores a program corresponding to each processing function, multiple memory circuits may be distributed and the processing circuit 15 may read the corresponding program from each individual memory circuit.

The processing circuitry 15 uses the identification function 151 to identify a signal region related to the generation of multiple MR signals in the pre-scan image of the subject P. The signal region corresponds to a region in the imaging space where protons such as water molecules are present. The identification function 151 identifies the region in the pre-scan image where the subject P is imaged (hereinafter referred to as the imaging region) as the signal region. Specifically, the identification function 151 identifies the imaging region corresponding to the region of the subject P by detecting the image of the subject P in the pre-scan image or by user specification on the pre-scan image.

For example, the identification function 151 identifies the signal region by applying area detection processing to the prescan image to detect the imaging region. The area detection processing can use existing image recognition processing, such as edge detection in prescan images, so a detailed description is omitted. Furthermore, the identification function 151 identifies the signal region in the prescan image displayed on the display 129 in accordance with an area identification instruction input by the user via the input interface 127. The area identification instruction is, for example, an instruction to input a shape (e.g., a rectangle or an ellipse) for specifying a range in the prescan image.

The processing circuitry 15 sets the sampling rate using the setting function 153 according to the FOV input by the user (hereinafter referred to as the user FOV). For example, the setting function 153 sets a sampling rate corresponding to oversampling (a sampling interval corresponding to oversampling) by multiplying the reciprocal of the FOV size by a constant. The upper limit of the sampling rate (hereinafter referred to as the upper limit rate) is set in advance based on the performance limits of the MRI apparatus 100. Therefore, the setting function 153 sets the sampling rate to be equal to or lower than the upper limit rate. The setting function 153 outputs the set sampling rate to the A/D converter 193 via the imaging control circuit 121. As a result, MR data is generated by sampling MR signals at the sampling rate set according to the imaging field of view.

The processing circuitry 15 uses the setting function 153 to set a cutoff frequency for the passband of the MR signal in the low-pass filter 191 based on the identified signal region. Specifically, the setting function 153 sets the cutoff frequency using the user FOV in the main scan, which is a scan of the subject P in multiple readout directions, and the strength of the gradient magnetic field in the main scan.

The processing circuitry 15 may use the setting function 153 to set cutoff frequencies for the passbands of multiple MR signals corresponding to multiple readout directions for each readout direction, regardless of the signal region, based on the user FOV for the main scan of the subject P. The setting function 153 may also set cutoff frequencies for the passbands of multiple magnetic resonance signals corresponding to multiple readout directions by multiplying a constant by a frequency determined based on the user FOV for the main scan of the subject P and the strength of the gradient magnetic field in the main scan.

In other words, the cutoff frequency is set by the setting function 153 so that the signal amount of each of the multiple MR signals is constant regardless of the multiple readout directions. In other words, the cutoff frequency is set by the setting function 153 so that it encompasses the signal range related to the generation of MR signals. In this case, the cutoff frequency is, for example, higher than the sampling rate, i.e., sampling frequency. For these reasons, the MR signals to be sampled by the A/D converter 193 are generated by filtering the MR signals received by the receive coil 117 with the low-pass filter 191 using the cutoff frequency previously set by the setting function 153.

The processing circuitry 15 uses the acquisition function 155 to acquire from the memory 13 MR data collected in multiple readout directions, including a first readout direction and a second readout direction intersecting the first readout direction, and multiple sensitivity maps corresponding to the multiple coil elements used to collect the MR data. The acquired MR data is collected in multiple readout directions, including the first readout direction and the second readout direction intersecting the first readout direction. The multiple sensitivity maps correspond to the multiple coil elements in the receive coil 117 involved in collecting the MR data, and indicate the distribution of sensitivity of the coil elements. Note that if the MRI device 100 is not equipped with the image generating device 1, the acquisition function 155 acquires the MR data and multiple sensitivity maps from various MRI devices via the communication interface 11 and a network.

The processing circuitry 15 uses the unfolded data generation function 157 to perform a one-dimensional Fourier transform along the readout direction for each readout direction using the MR data for each of the multiple readout directions in the main scan and multiple sensitivity maps. As a result, the unfolded data generation function 157 generates unfolded data for each readout direction, with the folding unfolded in one-dimensional image space. The specific processing performed by the unfolded data generation function 157 will be described in detail in the process of generating an MR image based on MR data collected using multiple readout directions, including a first readout direction and a second readout direction intersecting the first readout direction (hereinafter referred to as image generation processing).

The processing circuitry 15 uses the complementary data generation function 159 to perform a one-dimensional inverse Fourier transform along the readout direction on the expanded data for each readout direction. As a result, the complementary data generation function 159 generates complementary data for each readout direction, with data complementary to the magnetic resonance data. The complementary data corresponds to k-space data obtained by oversampling the MR signals at a sampling rate higher than the sampling rate for the MR signals before A/D conversion in generating the MR data. In other words, the complementary data corresponds to pseudo-oversampled data. In other words, the complementary data corresponds to data obtained by interpolating new data obtained by oversampling the MR signals that are the basis of the MR data acquired by the acquisition function 155. The specific processing performed by the complementary data generation function 159 will be described in detail in the image generation processing section.

The processing circuitry 15 uses the image generation function 161 to acquire MR data (hereinafter referred to as prescan data) generated by a prescan of the subject P from the receiving circuitry 119, arrange the data in k-space, and generate a prescan image based on the prescan data arranged in k-space. The image generation function 161 stores the generated prescan image in the memory 13.

For example, the processing circuitry 15 uses the image generation function 161 to acquire MR data generated by a scan related to the generation of a locator image from the receiving circuitry 119, arrange the data in k-space, and generate (reconstruct) a locator image based on the MR data arranged in k-space. The image generation function 161 also acquires sensitivity data generated by a scan related to the generation of a sensitivity map from the receiving circuitry 119, arranges the data in k-space, and generates (reconstructs) a sensitivity map based on the sensitivity data arranged in k-space. Since existing reconstruction methods can be used to generate locator images, sensitivity maps, etc., a description thereof will be omitted.

The processing circuitry 15 uses the image generation function 161 to generate MR images based on the complementary data for all readout directions. The generation of MR images based on the complementary data can be achieved using a common reconstruction method. Common reconstruction methods include, for example, NUFFT (Non-Uniform Fast Fourier Transform) and gridding. Since common reconstruction methods can be achieved using existing technology, a detailed description is omitted.

The image generation process executed by the MRI apparatus 100 and image generation device 1 of this embodiment configured as described above will be described using Figures 5 to 9. Figure 5 is a flowchart showing an example of the procedure for the image generation process. First, various processes performed prior to the execution of the image generation process will be described, and then the image generation process will be described.

The imaging control circuitry 121 performs a prescan on the subject P. The processing circuitry 15 generates a prescan image based on the prescan data using the image generation function 161. The image generation function 161 stores the generated prescan image, such as a locator image and coil sensitivity map, in the memory 13. The system control circuitry 123 displays the locator image on the display 129.

The input interface 127 inputs an FOV (hereinafter referred to as the user FOV) in the locator image in response to a user instruction. The user FOV is stored in the memory 13. The processing circuitry 15 sets a sampling frequency according to the user FOV using the setting function 153, and outputs the set sampling frequency to the A/D converter 193. For example, the setting function 153 multiplies the reciprocal of the size of the user FOV by a constant to set a sampling frequency corresponding to oversampling, in other words, the sampling interval.

The processing circuitry 15 uses the identification function 151 to perform area detection processing on the locator image and identify the signal area in the locator image. Note that identification of the signal area in the locator image is not limited to area detection processing. The signal area may be identified, for example, by a user instruction via the input interface 127. At this time, the system control circuitry 123 displays the pre-scan image on the display 129. That is, the display 129 displays the locator image under the control of the system control circuitry 123. The input interface 127 receives an input instruction to identify the signal area in the displayed locator image through the user's operation. As a result, the processing circuitry 15 uses the identification function 151 to identify the signal area.

The processing circuitry 15 sets the cutoff frequency of the low-pass filter 191 to be applied to the MR signals received by the main scan using the setting function 153. Specifically, the setting function 153 sets a provisional cutoff frequency (hereinafter referred to as provisional cutoff frequency) based on the strength of the gradient magnetic field in the main scan and the user FOV. For example, the setting function 153 sets the provisional cutoff frequency using the band of the low-pass filter 191 in the following equation:
User FOV [cm] = (2 × low-pass filter bandwidth [Hz]) / readout gradient magnetic field strength [Hz/cm]
In the above equation, the readout gradient magnetic field strength corresponds to the strength of the gradient magnetic field in the main scan.

The setting function 153 then transforms the tentative cutoff frequency into image space and compares it with the identified signal region. Hereinafter, the tentative cutoff frequency transformed into image space will be referred to as the tentative cutoff position. The setting function 153 identifies the position farthest from the tentative cutoff position (hereinafter referred to as the farthest position) among the signal regions that extend beyond the passband of the low-pass filter 191 defined by the tentative cutoff position in each of the multiple readout directions in the actual scan. The setting function 153 sets the frequency corresponding to the farthest position (hereinafter referred to as the farthest frequency) as the cutoff frequency. Note that the setting function 153 may also set the frequency obtained by adding a predetermined margin frequency to the farthest frequency as the cutoff frequency.

In other words, the setting function 153 sets the cutoff frequency so as to include the signal region related to the generation of MR signals. Setting the cutoff frequency corresponds to, for example, expanding the passband of the MR signal based on the provisional cutoff frequency. Note that setting the cutoff frequency so as to include the signal region related to the generation of MR signals may also be set by a user instruction via the input interface 127.

The setting function 153 may set a cutoff frequency for each readout direction depending on the angle of the readout direction relative to the kx direction. The setting function 153 may also set the cutoff frequency by multiplying the provisional cutoff frequency by a constant corresponding to the sequence of the actual scan. In these cases, the setting function 153 sets the cutoff frequency so that the signal intensity of each of the multiple MR signals received by the actual scan is constant regardless of the multiple readout directions in the actual scan. The setting function 153 outputs the set cutoff frequency to the low-pass filter 191.

The imaging control circuit 121 performs radial acquisition as the main scan for the subject P. Specifically, the imaging control circuit 121 performs imaging along one readout direction in the main scan. As a result, the receive coil 117 receives MR signals in that readout direction. The MR signals received by the receive coil 117 are output to the receive circuit 119. At this time, the MR signals are detected by a detector.

The low-pass filter 191 filters the detected MR signal using a set cutoff frequency. Filtering the MR signal by the low-pass filter 191 reduces unnecessary signals outside the user FOV. This improves the S/N ratio of the MR signal, etc. The filtered MR signal is output to the A/D converter 193.

The A/D converter 193 samples the MR signal output from the low-pass filter 191 using a set sampling frequency. As a result, the A/D converter 193 generates MR data. That is, the A/D converter 193 performs A/D conversion on the MR signal that has passed through the low-pass filter 191 at the sampling frequency, generating MR data. The MR data is stored in the memory 13 via the imaging control circuit 121. Once MR signal collection has been completed for all readout directions (i.e., all trajectories kTra in the readout direction) previously set for this scan, image generation processing begins.

(Image generation processing)
(Step S501)
The processing circuitry 15 uses the acquisition function 155 to acquire the MR data and the multiple sensitivity maps from the memory 13. Note that if the MRI apparatus 100 is not equipped with the image generating device 1, the acquisition function 155 acquires the MR data and the multiple sensitivity maps generated by the MRI apparatus from the MRI apparatus via the communication interface 11 and the network.

Figure 6 shows an example of MR data MRD at sampling points SP along the readout direction ROD in k-space ks. As shown in Figure 6, the MR data MRD is acquired by a main scan along the readout direction ROD.

(Step S502)
The processing circuitry 15 uses the unfolded data generation function 157 to perform a one-dimensional Fourier transform along the readout direction using multiple sensitivity maps for all coil elements and MR data for each readout direction. For example, NUFFT is used as the one-dimensional Fourier transform. As a result, the unfolded data generation function 157 generates unfolded data in which folding is unfolded in a one-dimensional image space along the readout direction. Data in which the unfolded data for all readout directions in the main scan are arranged in order of the angle indicating the readout direction is referred to as projection data or sinogram.

For example, the decompressed data generating function 157 generates decompressed data for each lead-out direction according to the following equation (1): An algorithm for executing equation (1) is stored in the memory 13.
The left side of equation (1) is the readout direction.
The right side of equation (1) represents the summation of the coil element i in the L2 norm and the readout direction.
Expanded data as variables in
The regularization term with argument
The sum of the variables is the expanded data
This shows that the equation is minimized by varying

That is, the argument that gives the minimum value on the right side of equation (1)
But the expanded data
This is equivalent to:

In the L2 norm on the right side of equation (1),
is the readout direction of the i-th coil element.
S _i denotes the sensitivity map of coil element i.
is the sensitivity map S _i of the i-th coil element and the expansion data as variables.
and the readout direction
It shows that a one-dimensional Fourier transform is performed along

The expanded data generation function 157 generates expanded data as variables so as to minimize the right side of the formula (1).
By calculating
The unfolded data generating function 157 stores the generated unfolded data together with the corresponding readout direction in the memory 13. The processing in this step is performed for all readout directions in the main scan. Note that the unfolded data generating function 157 may generate unfolded data using a regularization term related to compressed sensing (CS) or super-resolution as the regularization term in equation (1).

Figure 7 shows the one-dimensional image 1DI in one-dimensional image space before being unfolded using multiple sensitivity maps in the readout direction ROD. At this time, aliasing appears in the user FOV UF in the one-dimensional image 1DI. Figure 8 shows the unfolded data NWI after the unfolding process using multiple sensitivity maps has been performed in this step. The unfolded data NWI shown in Figure 8 is generated by one-dimensional sensitivity encoding (hereinafter referred to as SENSE (SENSitivity Encoding)) of the one-dimensional image 1DI shown in Figure 7, as shown in equation (1).

As shown in Figure 8, the field of view EFOV in the unfolded data NWI is expanded (enlarged) compared to the user FOV UF by the unfolding process. That is, in a one-dimensional image space along the readout direction, the unfolded data corresponds to one-dimensional image data contained in an expanded FOV obtained by expanding the FOV in the readout direction. The cutoff frequency is also set to include the signal region related to the generation of MR signals. Therefore, as shown in Figure 8, no data loss occurs in the folded unfolding. The expansion of the FOV in Figure 8 compared to Figure 7 corresponds to increasing the sampling rate, i.e., shortening the sampling interval (oversampling).

(Step S503)
The processing circuit 15 uses the complementary data generation function 159 to perform a one-dimensional inverse Fourier transform along the readout direction on the developed data NWI for each readout direction. As a result, the complementary data generation function 159 generates complementary data in which data is complemented for the MR data. The following equation (2) shows a mathematical formula for generating complementary data by the one-dimensional inverse Fourier transform performed in this step. The algorithm for executing equation (2) is stored in the memory 13.

The left side of equation (2) is the readout direction.
The right side of equation (2) represents the complementary data in the readout direction.
Deployment data in
In contrast, the lead-out direction
It shows that a one-dimensional inverse Fourier transform is performed along

The complementary data generating function 159 generates complementary data for each read-out direction by calculation using the formula (2).
The complementary data generating function 159 stores the generated complementary data together with the corresponding readout direction in the memory 13. The processing in this step is performed for all readout directions in the main scan.

Figure 9 is a diagram showing an example of complementary data CPD generated from the MR data MRD shown in Figure 6. As shown in Figure 9, the complementary data CPD is located at an oversampling point OSP in the readout direction ROD in the k-space ks. Compared to Figure 6, the complementary data CPD shown in Figure 9 corresponds to k-space data obtained by oversampling the MR signal at a sampling rate higher than the sampling rate for the MR signal before A/D conversion in generating the MR data MRD shown in Figure 6. In other words, the complementary data CPD corresponds to digital data obtained by sampling the MR signal at a sampling rate higher than the sampling rate used by the A/D converter 193. In other words, the complementary data CPD shown in Figure 9 corresponds to data obtained by interpolating new data obtained by oversampling the MR signal that is the basis of the MR data shown in Figure 6.

(Step S504)
The processing circuitry 15 generates MR images based on the complementary data for all readout directions in the main scan using the image generation function 161. Specifically, the MR images for the main scan are generated by applying a general reconstruction method to the complementary data arranged in the k-space ks according to the readout direction. The image generation function 161 stores the generated MR images in the memory 13. At this time, the system control circuitry 123 may display the generated MR images on the display 129. Furthermore, if the MRI apparatus 100 does not include the image generation device 1, the generated MR images are output to, for example, a PACS server or an HIS server via the communication interface 11 and a network.

The image generating device 1 according to the embodiment described above acquires MR data collected in multiple readout directions, including a first readout direction and a second readout direction intersecting the first readout direction, and multiple sensitivity maps corresponding to the multiple coil elements used to collect the MR data. A one-dimensional Fourier transform is performed along the readout direction for each readout direction using the MR data and the multiple sensitivity maps, thereby generating unfolded data in which folding is unfolded in one-dimensional image space. A one-dimensional inverse Fourier transform is performed along the readout direction on the unfolded data for each readout direction, thereby generating complementary data in which data is complemented for the MR data, and an MR image is generated based on the complementary data.

The complementary data generated by the image generating device 1 in this embodiment corresponds to k-space data obtained by oversampling the MR signal (the MR signal received by the receive coil 117 during the main scan) at a sampling rate higher than the sampling rate for the MR signal before A/D conversion in generating the MR data.

In addition, the MR data used in the image generating device 1 in this embodiment is generated by sampling magnetic resonance signals at a sampling rate set according to the user FOV, and the MR signals are generated by filtering the MR signals received by the receive coil 117 using a low-pass filter with a cutoff frequency preset by the setting function 153.

In addition, the cutoff frequency used in the MRI apparatus 100 of this embodiment is higher than the sampling rate set according to the user FOV. For example, the cutoff frequency is set by the setting function 153 so that the signal amount of each of the multiple MR signals corresponding to the multiple readout directions is constant regardless of the multiple readout directions. The cutoff frequency is also set by the setting function 153 so as to include the signal region related to the generation of the multiple MR signals corresponding to the multiple readout directions. For these reasons, the MRI apparatus 100 of this embodiment can set the cutoff frequency so as to include the signal region SA related to the generation of the MR signal. As a result, the MRI apparatus 100 can set the cutoff frequency so that the signal amount of each of the multiple MR signals corresponding to the multiple readout directions is constant regardless of the multiple readout directions.

As described above, with the image generating device 1 according to the embodiment, even if sufficient oversampling cannot be performed due to performance limitations of the MRI apparatus 100 in a scan in which the readout direction changes, it is possible to generate complementary data corresponding to oversampling that exceeds the performance limitations, thereby generating k-space data that is consistent in k-space. As a result, with this image generating device 1, it is possible to obtain high-quality images with few streaks.

Figure 10 shows an example of an MR image (1) generated by an existing reconstruction method using MR data that is not sufficiently oversampled, as a comparative example, and an MR image (2) generated based on complementary data using the image generation process of this embodiment. As shown in Figure 10, MR image (2) generated by the image generation process of this embodiment has reduced streak artifacts and improved image quality compared to MR image (1). Therefore, with the image generation device 1 of this embodiment, as shown in Figure 10, even if sufficient oversampling cannot be performed due to performance limitations of the MRI device 100, an MR image with improved image quality can be generated for the main scan.

When the technical concept of this embodiment is realized in an image generation method, the image generation method acquires MR data collected in multiple readout directions, including a first readout direction and a second readout direction intersecting the first readout direction, and multiple sensitivity maps corresponding to the multiple coil elements used to collect the MR data. Using the MR data and multiple sensitivity maps for each readout direction, the method performs a one-dimensional Fourier transform along the readout direction to generate unfolded data in which folding is unfolded in one-dimensional image space. The method performs a one-dimensional inverse Fourier transform along the readout direction on the unfolded data to generate complementary data in which data is complemented for the MR data, and generates an MR image based on the complementary data. The image generation process procedures and effects of this image generation method are similar to those described in the embodiment, and therefore will not be described here.

When the technical concept of this embodiment is realized by an image generation program, the image generation program causes a computer to acquire MR data collected in multiple readout directions, including a first readout direction and a second readout direction intersecting the first readout direction, and multiple sensitivity maps corresponding to the multiple coil elements used to collect the MR data, perform a one-dimensional Fourier transform along the readout direction for each readout direction using the MR data and the multiple sensitivity maps to generate unfolded data in which folding is unfolded in one-dimensional image space, perform a one-dimensional inverse Fourier transform along the readout direction on the unfolded data for each readout direction to generate complementary data in which data is complemented for the MR data, and generate an MR image based on the complementary data.

For example, image generation processing can be achieved by installing an image generation program on 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 enables a computer to execute the method can also be stored and distributed on a storage medium such as a magnetic disk (such as a hard disk), an optical disk (such as a CD-ROM or DVD), or semiconductor memory. The procedure and effects of image generation processing using the image generation program are the same as those in this embodiment, so a description thereof will be omitted.

At least one of the embodiments described above makes it possible to generate magnetic resonance images with improved image quality. That is, at least one of the embodiments makes it possible to generate consistent data (complementary data) in k-space even when sufficient oversampling cannot be performed in a scan in which the readout direction changes, thereby making it possible to obtain high-quality MR images with fewer streaks.

While several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments may be embodied in a variety of other forms, and various omissions, substitutions, modifications, and combinations of embodiments may be made without departing from the spirit of the invention. These embodiments and their variations are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as set forth in the claims.

1 Image generating device 11 Communication interface 13 Memory 15 Processing circuit 100 Magnetic resonance imaging device 101 Static magnetic field magnet 103 Gradient magnetic field coil 105 Gradient magnetic field power supply 107 Bed 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 127 Input interface 129 Display 151 Specific function 153 Setting function 155 Acquisition function 157 Expanded data generating function 159 Complementary data generating function 161 Image generating function 191 Low-pass filter 193 A/D converter

Claims (8)

an acquisition unit that acquires magnetic resonance data acquired in a plurality of readout directions including a first readout direction and a second readout direction intersecting the first readout direction, and a plurality of sensitivity maps corresponding to a plurality of coil elements used to acquire the magnetic resonance data;
a decompressed data generating unit that generates, for each readout direction, decompressed data in which folding is decompressed in a one-dimensional image space using the magnetic resonance data and the sensitivity map for each readout direction;
a complementary data generating unit that generates complementary data for each of the readout directions by performing a one- dimensional Fourier transform along the readout direction on each of the expanded data, the complementary data being complementary to the magnetic resonance data;
an image generating unit that generates a magnetic resonance image based on the complementary data;
An image generating device comprising: the complementary data corresponds to k-space data obtained by oversampling the magnetic resonance signals at a sampling rate higher than the sampling rate for the magnetic resonance signals prior to analog-to-digital conversion in generating the magnetic resonance data;
The image generating device of claim 1 . the magnetic resonance data is generated by sampling magnetic resonance signals at a sampling rate set according to an imaging field of view;
the magnetic resonance signals are generated by filtering the magnetic resonance signals received by the coil elements with a low-pass filter using a preset cutoff frequency;
the cutoff frequency is higher than the sampling rate;
3. The image generating device according to claim 1 or 2. the cutoff frequency is set to include a signal region related to the generation of a plurality of magnetic resonance signals corresponding to a plurality of readout directions;
The image generating device according to claim 3 . The decompressed data generation unit
calculating, for each readout direction, a product of estimated expanded data obtained by one-dimensional inverse Fourier transform along a readout direction of estimated magnetic resonance data estimated when the magnetic resonance data is collected at a sampling rate higher than a sampling rate for collecting the magnetic resonance data, and the sensitivity map;
performing a one-dimensional Fourier transform of the product along the readout direction;
generating, for each readout direction, the unfolded data in which folding is unfolded in a one-dimensional image space by performing optimization so as to reduce a difference between the result of the one-dimensional Fourier transform and the magnetic resonance data;
The image generating device of claim 1 . The decompressed data generation unit
generating the unfolded data for each of the readout directions by optimizing the sum of the L2 norm of the difference and a regularization term;
The image generating device according to claim 5 . acquiring magnetic resonance data collected in a plurality of readout directions including a first readout direction and a second readout direction intersecting the first readout direction, and a plurality of sensitivity maps corresponding to a plurality of coil elements used to collect the magnetic resonance data;
generating, for each readout direction, unfolded data in which folding is unfolded in a one-dimensional image space using the magnetic resonance data and the sensitivity map for each readout direction;
performing a one- dimensional Fourier transform along the readout direction on each of the expanded data for each of the readout directions, thereby generating complementary data in which data is complemented for the magnetic resonance data for each of the readout directions;
generating a magnetic resonance image based on each of the complementary data;
An image generating method comprising: On the computer,
acquiring magnetic resonance data collected in a plurality of readout directions including a first readout direction and a second readout direction intersecting the first readout direction, and a plurality of sensitivity maps corresponding to a plurality of coil elements used to collect the magnetic resonance data;
generating, for each readout direction, unfolded data in which folding is unfolded in a one-dimensional image space using the magnetic resonance data and the sensitivity map for each readout direction;
performing a one- dimensional Fourier transform along the readout direction on each of the expanded data for each of the readout directions, thereby generating complementary data in which data is complemented for the magnetic resonance data for each of the readout directions;
generating a magnetic resonance image based on the complementary data;
An image generation program that achieves this.