Magnetic Resonance Imaging Method, Device, Computer Device, and Storage Medium

Abstract

The present application relates to a magnetic resonance imaging method, apparatus, computer device, and storage medium. The method includes: dividing a k-space into a plurality of filling regions along a first direction and a second direction; repeatedly exciting a detection object by using a scanning sequence to obtain magnetic resonance signals; filling the magnetic resonance signals into the plurality of filling regions of the k-space to obtain k-space data; wherein at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction are in a random filling pattern; performing image reconstruction according to the k-space data to obtain a magnetic resonance image of the detection object. By using this method, the data acquisition speed can be increased, and the application ranges of 3D GRASE sequences and 3D EPI sequences can be expanded.

Description

Technical Field

[0001] The present application relates to the field of magnetic resonance technology, and particularly to a magnetic resonance imaging method, apparatus, computer device, and storage medium. Background Art

[0002] The 3D GRASE (GRAdient and Spin Echo) sequence and the 3D EPI (Echo Planar Imaging) sequence are commonly used scanning sequences in magnetic resonance. Usually, the SORT (Separate Off-Resonance and T2 effects) phase encoding method is used to fill the echo data of the 3D GRASE sequence and the 3D EPI sequence into the k-space, as Figure 1 shown.

[0003] Since the SORT phase encoding method causes a phase step along the EPI factor encoding direction in the k-space, resulting in artifacts that are difficult to eliminate in the reconstructed image. Therefore, the ETS (Echo Time Shift) technology is also combined to eliminate the artifacts caused by the phase step.

[0004] However, when using the ETS technology, the variable density random undersampling method with a high data acquisition speed cannot be used, and only the parallel imaging method with a relatively low data acquisition speed can be used. Therefore, the 3D GRASE sequence and the 3D EPI sequence cannot be used in applications with high requirements for data acquisition speed (such as dynamic imaging, abdominal breath-hold imaging, etc.), that is, the clinical application range of the 3D GRASE sequence and the 3D EPI sequence is limited. Summary of the Invention

[0005] Based on this, it is necessary to provide a magnetic resonance imaging method, apparatus, computer device, and storage medium that can improve the data acquisition speed on the basis of using the ETS technology, thereby expanding the clinical application range of the 3D GRASE sequence and the 3D EPI sequence for the above technical problems.

[0006] A magnetic resonance imaging method, the method comprising:

[0007] Dividing the k-space into a plurality of filling regions along a first direction and a second direction;

[0008] Exciting a detection object multiple times using a scanning sequence to obtain magnetic resonance signals;

[0009] Filling the magnetic resonance signals into a plurality of filling regions of the k-space to obtain k-space data; wherein, at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction are in a random filling pattern;

[0010] Perform image reconstruction based on the K-space data to obtain a magnetic resonance image of the object to be detected.

[0011] In one embodiment, the first direction is the EPI factor encoding direction, and the second direction is the phase encoding direction.

[0012] A magnetic resonance imaging method, the method comprising:

[0013] Place the object to be detected in a static magnetic field, and use a scanning sequence to excite the object to be detected multiple times to obtain magnetic resonance signals; the readout gradient of the scanning sequence includes multiple groups of alternately distributed positive readout gradients and negative readout gradients;

[0014] Fill the magnetic resonance signals into the K-space to obtain K-space data; wherein, the K-space includes a first partition and a second partition that are adjacent to each other along a first direction, at least part of the magnetic resonance signals corresponding to the positive readout gradients are filled into the first partition of the K-space, at least part of the magnetic resonance signals corresponding to the negative readout gradients are filled into the second partition of the K-space, and the first partition and the second partition have the same filling pattern;

[0015] Perform image reconstruction based on the K-space data to obtain a magnetic resonance image of the object to be detected.

[0016] In one embodiment, the first partition and / or the second partition are divided into a plurality of filling regions along a second direction, and the first direction is orthogonal to the second direction.

[0017] In one embodiment, each time the scanning sequence is excited, a plurality of magnetic resonance signals are obtained, and the plurality of magnetic resonance signals are respectively filled into different filling regions of each partition.

[0018] In one embodiment, the number of filling regions in each partition is determined according to the echo train of the magnetic resonance signals corresponding to each excitation of the scanning sequence.

[0019] A magnetic resonance imaging apparatus, the apparatus comprising:

[0020] A region division module for dividing the K-space into a plurality of filling regions along a first direction and a second direction;

[0021] A signal acquisition module for using a scanning sequence to excite the object to be detected multiple times to acquire magnetic resonance signals;

[0022] A signal filling module for filling the magnetic resonance signals into the plurality of filling regions of the K-space to obtain K-space data; wherein, at least three filling regions along the first direction have the same filling pattern, and the filling regions along the second direction are in a random filling pattern;

[0023] An image reconstruction module, configured to perform image reconstruction based on K-space data to obtain a magnetic resonance image of a detection object.

[0024] In one embodiment, the first direction is the EPI factor encoding direction, and the second direction is the phase encoding direction.

[0025] A magnetic resonance imaging device, comprising:

[0026] A signal acquisition module, configured to place a detection object in a static magnetic field and use a scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals; the readout gradient of the scanning sequence includes multiple groups of alternately distributed positive-polarity readout gradients and negative-polarity readout gradients;

[0027] A signal filling module, configured to fill the magnetic resonance signals into K-space to obtain K-space data; wherein, K-space includes a first partition and a second partition that are adjacent to each other along a first direction, the magnetic resonance signals corresponding to the positive-polarity readout gradients are at least partially filled into the first partition of K-space, the magnetic resonance signals corresponding to the negative-polarity readout gradients are at least partially filled into the second partition of K-space, and the first partition and the second partition have the same filling pattern;

[0028] An image reconstruction module, configured to perform image reconstruction based on K-space data to obtain a magnetic resonance image of a detection object.

[0029] A computer device, comprising a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0030] Divide K-space into multiple filling regions along a first direction and a second direction;

[0031] Use a scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals;

[0032] Fill the magnetic resonance signals into the multiple filling regions of K-space to obtain K-space data; wherein, at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction are in a random filling pattern;

[0033] Perform image reconstruction based on the K-space data to obtain a magnetic resonance image of the detection object; or,

[0034] Use a scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals; the readout gradient of the scanning sequence includes multiple groups of alternately distributed positive-polarity readout gradients and negative-polarity readout gradients;

[0035] Fill the magnetic resonance signals into the k-space to obtain k-space data. The k-space includes a first partition and a second partition that are adjacently distributed along a first direction. The magnetic resonance signals corresponding to the positive readout gradient are at least partially filled into the first partition of the k-space, and the magnetic resonance signals corresponding to the negative readout gradient are at least partially filled into the second partition of the k-space. The first partition and the second partition have the same filling pattern.

[0036] Perform image reconstruction based on the k-space data to obtain a magnetic resonance image of the object to be detected.

[0037] A computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, the following steps are implemented:

[0038] Divide the k-space into a plurality of filling regions along the first direction and the second direction.

[0039] Use a scanning sequence to excite the object to be detected multiple times to obtain magnetic resonance signals.

[0040] Fill the magnetic resonance signals into the plurality of filling regions of the k-space to obtain k-space data. Among them, at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction are in a random filling pattern.

[0041] Perform image reconstruction based on the k-space data to obtain a magnetic resonance image of the object to be detected.

[0042] In the above magnetic resonance imaging method, device, computer device, and storage medium, the processor divides the k-space into a plurality of filling regions along the first direction and the second direction; uses a scanning sequence to excite the object to be detected multiple times to obtain magnetic resonance signals; fills the magnetic resonance signals into the plurality of filling regions of the k-space to obtain k-space data; and performs image reconstruction based on the k-space data to obtain a magnetic resonance image of the object to be detected. Since the magnetic resonance signals collected by the positive and negative readout gradients have the same filling pattern in different partitions divided along the first direction, the ETS technology can still be used to eliminate the artifacts caused by phase steps and ensure the imaging effect. And along the second direction, the fillable positions in the middle filling region are fewer than those in the filling regions on both sides, that is, there are unfilled positions in the filling regions on both sides. Therefore, the compressed sensing algorithm can be used for image reconstruction, which improves the data acquisition speed and enables the 3D GRASE sequence and the 3D EPI sequence to be used in applications with high requirements for data acquisition speed, expanding the application scope of the 3D GRASE sequence and the 3D EPI sequence. Description of the Drawings

[0043] Figure 1 A schematic diagram of the filled k-space in the background art;

[0044] Figure 2It is an application environment diagram of a magnetic resonance imaging method in an embodiment;

[0045] Figure 3 It is a schematic flowchart of a magnetic resonance imaging method in an embodiment;

[0046] Figure 4 It is a schematic diagram of K-space in an embodiment;

[0047] Figure 5 It is a schematic flowchart of a magnetic resonance imaging method in another embodiment;

[0048] Figure 6a It is a schematic diagram of the readout gradient of a scan sequence in an embodiment;

[0049] Figure 6b For Figure 6a It is an enlarged comparison diagram of the readout gradients corresponding to different partitions of

[0050] Figure 7 It is one of the schematic flowcharts of the steps of image reconstruction based on K-space data to obtain a magnetic resonance image of a detection object in an embodiment;

[0051] Figure 8 It is another schematic flowchart of the steps of image reconstruction based on K-space data to obtain a magnetic resonance image of a detection object in an embodiment;

[0052] Figure 9 It is a schematic diagram of data interpolation processing in an embodiment;

[0053] Figure 10 It is a schematic diagram of a fully filled K-space in an embodiment;

[0054] Figure 11 It is another schematic flowchart of the steps of image reconstruction based on K-space data to obtain a magnetic resonance image of a detection object in an embodiment;

[0055] Figure 12 It is a structural block diagram of a magnetic resonance imaging device in an embodiment;

[0056] Figure 13 It is a structural block diagram of a magnetic resonance imaging device in another embodiment;

[0057] Figure 14 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0058] In order to make the objectives, technical solutions and advantages of this application clearer, the following further details this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0059] The magnetic resonance imaging method provided by this application can be applied to an application environment as Figure 2 shown. This application environment is a magnetic resonance system. The magnetic resonance system 100 includes a bed body 110, an MR scanner 120, and a processor 130. The MR scanner 120 includes a magnet, a radio frequency transmitting coil, a gradient coil, and a radio frequency receiving coil. The bed body 110 is used to carry a target object 010. The radio frequency transmitting coil is used to transmit radio frequency pulses to the target object. The gradient coil is used to generate a gradient field, which can be along the phase encoding direction, the slice selection direction, the frequency encoding direction, etc.; the radio frequency receiving coil is used to receive magnetic resonance signals. In one embodiment, the magnet of the MR scanner 120 can be a permanent magnet or a superconducting magnet, and according to different functions, the radio frequency coils that make up the radio frequency unit can be divided into a body coil and a local coil. In one embodiment, the types of the radio frequency transmitting coil and the radio frequency receiving coil can be a birdcage coil, a solenoid coil, a saddle-shaped coil, a Helmholtz coil, an array coil, a loop coil, etc. In a specific embodiment, the radio frequency transmitting coil is set as a birdcage coil, the local coil is set as an array coil, and the array coil can be set in a 4-channel mode, an 8-channel mode, or a 16-channel mode.

[0060] The magnetic resonance system 100 further includes a controller 140 and an output device 150. Among them, the controller 140 can simultaneously monitor or control the MR scanner 110, the processor 130, and the output device 150. The controller 140 can include one or a combination of several of a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a graphics processing unit (GPU), a physics processing unit (PPU), a digital signal processor (DSP), a field-programmable gate array (FPGA), an ARM processor, etc.

[0061] The output device 150, such as a display, can display the magnetic resonance image of the region of interest. Further, the output device 150 can also display the height, weight, age, imaging site of the subject, and the working status of the MR scanner 110, etc. The type of the output device 150 can be one or a combination of several types such as a cathode ray tube (CRT) output device, a liquid crystal output device (LCD), an organic light emitting output device (OLED), a plasma output device, etc.

[0062] The magnetic resonance system 100 can be connected to a local area network (LAN), a wide area network (WAN), a public network, a private network, a proprietary network, a public switched telephone network (PSTN), the Internet, a wireless network, a virtual network, or any combination of the above networks.

[0063] In one embodiment, the processor 130 can control the MR scanner 120 to perform equally spaced or non-equally spaced sampling on the detection object (a part of the target object 010), and control the MR scanner 120 to acquire the magnetic resonance signal of the detection object, and perform Fourier transform on the magnetic resonance signal to obtain the magnetic resonance image of the detection object.

[0064] In one embodiment, as Figure 3 shown, a magnetic resonance imaging method is provided. Taking the processor in Figure 2 as an example for illustration, the method includes the following steps:

[0065] Step 201, divide the K-space into a plurality of filling regions along a first direction and a second direction.

[0066] Wherein, the first direction and the second direction are in an orthogonal relationship. The K-space is equally divided along the first direction, and along the second direction, the middle filling region can be set to be small and the filling regions on both sides can be set to be large, that is: the data matrix corresponding to the middle filling region is small, and the data matrices corresponding to the edge filling regions on both sides of the middle filling region are large. As Figure 4 shown, the K-space is divided into three partitions g1, g2, and g3 along the first direction, and into five partitions r1, r2... r5 along the second direction, obtaining a plurality of filling regions such as g1r1, g2r1, g3r1... The fillable positions in the middle filling regions g1r3, g2r3, g3r3 are fewer than those in the filling regions on both sides such as g1r1, g2r1, g3r1. That is, the filling density decreases sequentially from the middle region to the corresponding regions on both sides. Please continue to refer to Figure 4, in the figure, the black dots represent the positions where the data lines are filled, and the white dots represent the positions where the data lines are not filled. The filled areas in the three partitions g1, g2, and g3 and corresponding to the same partition in the second direction have the same filling pattern, that is, the patterns formed by the black dots are the same. For a partition corresponding to the first direction, and different filled areas along the second direction have different filling patterns, that is, the patterns formed by the black dots are randomly distributed.

[0067] In one embodiment, the first direction is the EPI factor encoding direction, corresponding to the positive and negative polarity readout gradient encoding direction, and the second direction is the phase encoding direction.

[0068] Step 202, use the scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals.

[0069] Among them, the scanning sequence can include at least one of the 3D GRASE sequence and the 3D EPI sequence, and the number of excitations can match the fillable positions in the middle filled area. As Figure 4 shown, the number of excitations is 6 times, the fillable positions in the middle filled areas g1r3, g2r3, and g3r3 are 6 respectively, the number of echoes generated by each excitation is 5, and these five echoes are filled into five filled areas such as r1 - r5 divided along the second direction in a random manner.

[0070] The processor controls the MR scanner to excite the detection object multiple times according to the scanning sequence, and controls the MR scanner to collect the magnetic resonance signals generated by the detection object. Then, the processor obtains the magnetic resonance signals from the MR scanner.

[0071] Step 203, fill the magnetic resonance signals into multiple filled areas of the K - space to obtain K - space data.

[0072] Among them, at least two filled areas along the first direction have the same filling pattern, and the filled areas along the second direction are randomly filled patterns. In the embodiments of the present invention, the filling pattern of each filled area can be the pattern formed by all the fillable positions in this filled area.

[0073] After the processor obtains the magnetic resonance signals, it fills the magnetic resonance signals into multiple filled areas of the K - space. Among them, along the first direction, the magnetic resonance signals are filled into the corresponding fillable positions in each filled area; along the second direction, the magnetic resonance signals are randomly filled in each filled area. As Figure 4 shown, the black dots represent successive excitations, and the fillable positions of the magnetic resonance signals corresponding to each excitation in the filled area g1r1 correspond to the fillable positions in the filled areas g2r1 and g3r1.

[0074] Understandably, along the first direction, magnetic resonance signals are filled in the corresponding filling positions of each filling region. Therefore, the ETS (Echo-Time Shifting) method can still be used to eliminate artifacts caused by phase steps and ensure the imaging effect. Along the second direction, the fillable positions in the middle filling region are fewer than those in the filling regions on both sides, that is, there are unfilled positions in the filling regions on both sides. Therefore, any reconstruction algorithm such as a compressed sensing algorithm, a parallel reconstruction algorithm, or an algorithm based on a neural network can be used for image reconstruction later, which can improve the data acquisition speed, so that the 3D GRASE sequence and the 3D EPI sequence can be used in applications with high requirements for data acquisition speed.

[0075] In one embodiment, the number of filling regions of the K-space along the second direction is determined according to the echo train of the magnetic resonance signals corresponding to each excitation of the scanning sequence. As Figure 4 shown, if the echo train length is 5, the number of filling regions of the K-space along the second direction is also 5.

[0076] Step 204, perform image reconstruction based on the K-space data to obtain a magnetic resonance image of the detection object.

[0077] After obtaining the K-space data, the processor can perform image reconstruction based on the K-space data using algorithms such as Fourier transform, and thus obtain a magnetic resonance image of the detection object.

[0078] In the above magnetic resonance imaging method, the processor divides the K-space into multiple filling regions along the first direction and the second direction; uses the scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals; fills the magnetic resonance signals into the multiple filling regions of the K-space to obtain K-space data; performs image reconstruction based on the K-space data to obtain a magnetic resonance image of the detection object. Since for different partitions divided along the first direction, the magnetic resonance signals collected by the positive and negative polarity readout gradients have the same filling pattern, the ETS technology can still be used to eliminate artifacts caused by phase steps and ensure the imaging effect. And along the second direction, the fillable positions in the middle filling region are fewer than those in the filling regions on both sides, that is, there are unfilled positions in the filling regions on both sides. Therefore, a compressed sensing algorithm can be used for image reconstruction, which improves the data acquisition speed, enabling the 3D GRASE sequence and the 3D EPI sequence to be used in applications with high requirements for data acquisition speed and expanding the application scope of the 3D GRASE sequence and the 3D EPI sequence.

[0079] In one embodiment, as Figure 5 shown, a magnetic resonance imaging method is provided. Taking the method applied to the Figure 2 processor as an example for illustration, it includes the following steps:

[0080] Step 301: Place the object to be detected in a static magnetic field and use a scanning sequence to excite the object to be detected multiple times to obtain magnetic resonance signals.

[0081] Among them, the readout gradient of the scanning sequence includes multiple groups of alternately distributed positive-polarity readout gradients and negative-polarity readout gradients. As Figure 6a shown, it is a schematic diagram of the GRASE sequence according to an embodiment of the present application. Among them, RF represents a radio frequency pulse; Gz represents a slice selection direction gradient field; Gy represents a phase encoding direction gradient field; Gx represents a gradient field in the readout encoding direction. In this embodiment, multiple 180-degree refocusing pulses are applied after the 90-degree excitation pulse. During the period between the first 180-degree refocusing pulse and before the second 180-degree refocusing pulse (corresponding to partition r1), a first group of frequency encoding gradients with positive and negative polarity inversion is applied. Among them, g1 and g3 are echo signals collected by positive gradients, and g2 is an echo signal collected by a negative gradient. During the period between the second 180-degree refocusing pulse and before the third 180-degree refocusing pulse (corresponding to different partition r2), a second group of frequency encoding gradients with positive and negative polarity inversion is applied. During the period between the third 180-degree refocusing pulse and before the fourth 180-degree refocusing pulse (corresponding to partition r3), a third group of frequency encoding gradients with positive and negative polarity inversion is applied. It can be understood that there can be more 180-degree refocusing pulses, as well as frequency encoding gradients set between adjacent refocusing pulses, which can be specifically determined according to the size of the K space or the type of the sequence. Further, along the phase encoding direction, a spike / dot (blip) pulse is also applied at the moment of the positive and negative polarity inversion of the frequency encoding gradient to move the current phase encoding line in the K space to the next position. In this embodiment, between two adjacent refocusing pulses, after the collection of the echo signal g1 is completed, the first blip pulse is applied along the phase encoding direction, and then the echo signal g2 is collected; after the collection of the echo signal g2 is completed, the second blip pulse is applied along the phase encoding direction, and then the echo signal g3 is collected. More specifically, the echo signals g1 and g3 are gradient echo signals, and the echo signal g2 is a spin echo signal. In this embodiment, the echo signal g2 with higher signal intensity is filled in the central region of the K space, and the echo signals g1 and g3 with lower signal intensity are filled in the edge region of the K space, which is beneficial to obtaining a higher signal ratio and image contrast.

[0082] Figure 6b For Figure 6aMagnification comparison diagrams of readout gradients corresponding to different partitions. As can be seen from the figure, the readout gradient corresponding to partition r2 has a first echo time offset relative to the readout gradient corresponding to partition r1; the readout gradient corresponding to partition r3 has a second echo time offset relative to the readout gradient corresponding to partition r1, and the first echo time offset is different from the second echo time offset. In this embodiment, by setting like this, the combination of the GRASE sequence and the ETS method can be realized, and the stepped phase can be changed into a continuously slowly increasing oblique line, thereby eliminating the image artifacts caused by the phase change.

[0083] The object to be detected is placed in a static magnetic field, and the processor controls the MR scanner to perform multiple excitations on the object to be detected according to the scanning sequence, and controls the MR scanner to collect the magnetic resonance signals generated by the object to be detected. Then, the processor obtains the magnetic resonance signals from the MR scanner.

[0084] In one of the embodiments, the scanning sequence includes at least one of a 3D GRASE sequence and a 3D EPI sequence.

[0085] Step 302, filling the magnetic resonance signals into the K-space to obtain K-space data.

[0086] Among them, the K-space includes a first partition and a second partition that are adjacent to each other along a first direction. Part or all of the magnetic resonance signals corresponding to the positive readout gradient are filled into the first partition of the K-space, and part or all of the magnetic resonance signals corresponding to the negative readout gradient are filled into the second partition of the K-space, and the first partition and the second partition have the same filling pattern; for the 3D EPI sequence, the first partition and the second partition may each include a filling area. For the 3D GRASE sequence, the first partition and the second partition may each include two, three or more filling areas, and the middle filling area is small and the filling areas on both sides are large.

[0087] In this embodiment, it can be set that each readout gradient includes a total of N (N is an integer greater than or equal to 1) alternately distributed positive readout gradients and negative readout gradients, and the K-space is equally divided into N partitions along the first direction. For a readout gradient including N alternately distributed positive readout gradients and negative readout gradients, the magnetic resonance signals corresponding to the first positive readout gradient are filled into the Nth 1 partition (N 1 ∈ N), and the magnetic resonance signals corresponding to the first negative readout gradient are filled into the Nth 2 partition (N 2 ∈ N and N 1 ≠ N 2 ), and the magnetic resonance signals corresponding to the second positive readout gradient are filled into the Nth 3 partition (N 3∈N, N 3 ≠ N1 and N 3 ≠ N 2 )。If there are more readout gradients of the positive and negative polarities, the corresponding magnetic resonance signals are filled into other different partitions among the N partitions. The magnetic resonance signal corresponding to the first positive-polarity readout gradient of each readout gradient is filled into the N 1 partition, and the magnetic resonance signal corresponding to the first negative-polarity readout gradient of each of the said readout gradients is filled into the N 2 partition, and so on. At the same time, the signals of different readout gradients are filled in different partitions along the second direction of the K-space, and are randomly filled in each partition along the second direction.

[0088] As Figure 4 shown, the magnetic resonance signal corresponding to g1 or g3 is filled into the first partition, and the magnetic resonance signal corresponding to g2 is filled into the second partition. Moreover, the filling positions of the magnetic resonance signals excited each time in the first partition correspond to those in the second partition.

[0089] It can be understood that along the first direction, the first partition and the second partition have the same filling pattern for the magnetic resonance signals collected by the corresponding positive and negative polarity readout gradients. Therefore, the ETS technology can still be used to eliminate the artifacts caused by phase steps and ensure the imaging effect. In each partition, the middle filling area is small and the two-side filling areas are large, that is, there are unfilled positions in the two-side filling areas. Therefore, the compressed sensing algorithm can be used for image reconstruction later, so that the 3D GRASE sequence and the 3D EPI sequence can be used in applications with higher requirements for data acquisition speed.

[0090] Step 303, perform image reconstruction according to the K-space data to obtain a magnetic resonance image of the detection object.

[0091] After obtaining the K-space data, the processor can perform image reconstruction according to the K-space data using algorithms such as Fourier transform to obtain a magnetic resonance image of the detection object. Optionally, the method for performing image reconstruction on the K-space data may include: using the fully sampled filling area as calibration data points. In this embodiment, the data points of the filling area included in partition r3 are used as calibration data points; synthesizing a filter using the calibration data points; applying the synthesized filter to other partitions to obtain a plurality of coupled simultaneous linear equations with a plurality of unknowns; and solving the plurality of coupled simultaneous linear equations with a plurality of unknowns to obtain a complete data set for other partitions, that is, recovering the unfilled data points in other partitions.

[0092] In the above magnetic resonance imaging method, the object to be detected is placed in a static magnetic field, and the object to be detected is excited multiple times using a scanning sequence to obtain magnetic resonance signals; the magnetic resonance signals are filled into the k-space to obtain k-space data; image reconstruction is performed based on the k-space data to obtain the magnetic resonance image of the object to be detected. Since for different partitions divided along the first direction, the magnetic resonance signals collected by the positive and negative readout gradients have the same filling pattern, the ETS technology can still be used to eliminate artifacts caused by phase steps and ensure the imaging effect; and in each partition, the filling area in the middle is small and the filling areas on both sides are large, that is, there are unfilled positions in the filling areas on both sides. Therefore, a compressed sensing algorithm can be used for image reconstruction to improve the data acquisition speed, enabling the 3D GRASE sequence and the 3D EPI sequence to be used in applications with high requirements for data acquisition speed, thus expanding the application scope of the 3D GRASE sequence and the 3D EPI sequence.

[0093] In one embodiment, the magnetic resonance signals are filled into at least three filling areas in a random filling pattern. As Figure 4 shown, the first partition corresponding to g1 includes five filling areas g1r1 to g1r5, and the second partition corresponding to g2 includes five filling areas g1r1 to g1r5. For the same partition, the magnetic resonance signals can be randomly filled in each filling area without restricting the filling positions.

[0094] In one embodiment, multiple magnetic resonance signals are obtained each time the scanning sequence is excited, and the multiple magnetic resonance signals are respectively filled into different filling areas in each partition. As Figure 4 shown, there are a total of 6 excitations, and 5 magnetic resonance signals are obtained each time an excitation is performed, and the 5 magnetic resonance signals are filled into r1 to r5.

[0095] In one embodiment, the number of filling areas in each partition is determined according to the echo train of the magnetic resonance signals corresponding to each excitation of the scanning sequence. As Figure 4 shown, if the echo train length is 5, then each partition includes 5 filling areas.

[0096] In one embodiment, the step of performing image reconstruction based on the k-space data to obtain the magnetic resonance image of the object to be detected can be implemented in multiple ways. As Figure 7 shown, one way may include:

[0097] Step 401, based on the k-space data, iterative processing is performed using a compressed sensing algorithm to obtain the undersampled data corresponding to the unfilled positions in the k-space.

[0098] Since in each partition, the intermediate filling area is small and the filling areas on both sides are large, there are unfilled positions in the filling areas on both sides where no magnetic resonance signal is filled. Based on the filled K-space data, iterative processing is performed using the compressed sensing algorithm to obtain the undersampled data corresponding to the unfilled positions in the K-space.

[0099] Step 402: Perform image reconstruction based on the K-space data and the undersampled data to obtain the magnetic resonance image of the detection object.

[0100] The magnetic resonance system has multiple coil channels. Image reconstruction is performed based on the K-space data and the undersampled data corresponding to each coil channel to obtain the magnetic resonance image corresponding to each coil channel; then, the magnetic resonance images of multiple coil channels are combined using the channel combination algorithm to obtain the magnetic resonance image of the detection object.

[0101] It can be understood that performing image reconstruction for each coil channel and then combining the magnetic resonance images of multiple coil channels using the sum of squares algorithm can reduce the problem of different signal amplitudes caused by the different relative positions of each coil and the detection object, so the imaging effect can be improved.

[0102] Such as Figure 8 shown, another way may include:

[0103] Step 403: Based on the K-space data, perform data interpolation processing using the parallel imaging algorithm to obtain the intermediate result corresponding to the unfilled position in the K-space.

[0104] For the unfilled positions in the K-space, data interpolation processing is performed according to the magnetic resonance signals in the filled positions adjacent to the unfilled positions to obtain the intermediate result corresponding to the unfilled position. The number of filled positions adjacent to the unfilled position can be determined according to the preset reconstruction kernel. Such as Figure 9 shown, the preset reconstruction kernel is 3. For each unfilled position, data interpolation processing is performed according to the magnetic resonance signals in the 3 adjacent filled positions to obtain the intermediate result corresponding to the unfilled position. In this embodiment, the intermediate result is determined by the following method: taking Figure 9 the completely filled data line in the vertical direction in as the calibration data points; using the calibration data points to synthesize a filter; applying the synthesized filter to the data set containing the unfilled positions to obtain a plurality of coupled simultaneous linear equations with a plurality of unknowns; solving the plurality of coupled simultaneous linear equations with a plurality of unknowns to obtain a complete data set. In another embodiment, the intermediate result is determined by the following method: obtaining the calibration data points of each data set, taking Figure 9The data lines that are completely filled in the vertical direction are calibration data points; for each radio frequency receiving coil, a complete k-space data set is formed based on the k-space data of this radio frequency receiving coil and the k-space data of the radio frequency receiving coils of the remaining channels; repeat the foregoing steps until the k-space data of the radio frequency receiving coils of all channels form a complete k-space data set.

[0105] Step 404, based on the intermediate result, use the compressive sensing algorithm to perform iterative processing to obtain the undersampled data corresponding to the unfilled positions.

[0106] According to the calculated intermediate result corresponding to the unfilled position, use the compressive sensing algorithm to perform iterative processing to obtain the undersampled data corresponding to the unfilled position. As Figure 10 shown, the gray dots represent the undersampled data, and the black dots represent the k-space data.

[0107] Step 405, perform image reconstruction based on the k-space data and the undersampled data to obtain the magnetic resonance image of the detection object.

[0108] After obtaining the undersampled data, the undersampled data and the k-space data fill the entire k-space. At this time, perform image reconstruction according to the k-space data and the undersampled data to obtain the magnetic resonance image of the detection object.

[0109] As Figure 11 shown, there is another way that may include:

[0110] Step 406, calculate the sensitivity of each coil according to the data in the middle filling area of the k-space corresponding to each coil channel.

[0111] The magnetic resonance system has multiple coil channels. For each coil channel, use the data in the middle filling area of the k-space as a reference line to calculate the sensitivity of each coil. Among them, the sensitivity of each coil can characterize the relative position relationship between the coil and the detection object.

[0112] Step 407, based on the sensitivity of each coil, use the sensitivity algorithm and the compressive sensing algorithm to perform iterative processing and image reconstruction processing in sequence to obtain the magnetic resonance image of the detection object.

[0113] After obtaining the sensitivity of multiple coils, the sensitivity distribution of multiple coils can be determined. Then, use the sensitivity algorithm and the compressive sensing algorithm to perform iterative processing to obtain the undersampled data corresponding to the unfilled positions in the k-space. Furthermore, perform image reconstruction processing according to the k-space data and the undersampled data corresponding to the unfilled positions to obtain the magnetic resonance image of the detection object.

[0114] In the above steps of reconstructing an image based on K-space data to obtain a magnetic resonance image of a detection object, since there are unfilled positions in the two-sided filling regions where magnetic resonance signals are not filled, a compressed sensing algorithm can be used for image reconstruction to improve the data acquisition speed, enabling the 3D GRASE sequence and the 3D EPI sequence to be used in applications with high requirements for data acquisition speed, thus expanding the application scope of the 3D GRASE sequence and the 3D EPI sequence.

[0115] It should be understood that although Figures 2 - 11 the steps in the flowchart are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this article, the execution of these steps has no strict order restriction, and these steps can be executed in other orders. Moreover, Figures 2 - 11 at least a part of the steps in

[0116] In one embodiment, as Figure 12 shown, a magnetic resonance imaging apparatus is provided, including:

[0117] A region division module 501 for dividing the K-space into a plurality of filling regions along a first direction and a second direction;

[0118] A signal acquisition module 502 for repeatedly exciting a detection object using a scanning sequence to acquire magnetic resonance signals;

[0119] A signal filling module 503 for filling the magnetic resonance signals into the plurality of filling regions of the K-space to obtain K-space data; wherein, at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction are in a random filling pattern;

[0120] An image reconstruction module 504 for reconstructing an image based on the K-space data to obtain a magnetic resonance image of the detection object.

[0121] In one of the embodiments, the above first direction is the EPI factor encoding direction, and the above second direction is the phase encoding direction.

[0122] In one embodiment, as Figure 13 shown, a magnetic resonance imaging apparatus is provided, and the apparatus includes:

[0123] A signal acquisition module 601 is configured to place a detection object in a static magnetic field and use a scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals. The readout gradient of the scanning sequence includes multiple sets of alternately distributed positive-polarity readout gradients and negative-polarity readout gradients.

[0124] A signal filling module 602 is configured to fill the magnetic resonance signals into the K-space to obtain K-space data. The K-space includes a first partition and a second partition that are adjacent to each other along a first direction. The magnetic resonance signals corresponding to the positive-polarity readout gradients are at least partially filled into the first partition of the K-space, and the magnetic resonance signals corresponding to the negative-polarity readout gradients are at least partially filled into the second partition of the K-space, and the first partition and the second partition have the same filling pattern.

[0125] An image reconstruction module 603 is configured to perform image reconstruction based on the K-space data to obtain a magnetic resonance image of the detection object.

[0126] In one embodiment, the above-mentioned first partition and / or the second partition are divided into a plurality of filling regions along a second direction, and the above-mentioned first direction is orthogonal to the above-mentioned second direction.

[0127] In one embodiment, each excitation of the above-mentioned scanning sequence obtains a plurality of magnetic resonance signals, and the plurality of magnetic resonance signals are respectively filled into different filling regions of each partition.

[0128] In one embodiment, the number of filling regions in each partition is determined according to the echo train of the magnetic resonance signals corresponding to each excitation of the scanning sequence.

[0129] In one embodiment, the above-mentioned image reconstruction module 603 is specifically configured to perform iterative processing based on the K-space data using a compressed sensing algorithm to obtain undersampled data corresponding to unfilled positions in the K-space; perform image reconstruction based on the K-space data and the undersampled data to obtain a magnetic resonance image of the detection object.

[0130] In one embodiment, the above-mentioned image reconstruction module 603 is specifically configured to perform data interpolation processing based on the K-space data using a parallel imaging algorithm to obtain an intermediate result corresponding to an unfilled position in the K-space; perform iterative processing based on the intermediate result using a compressed sensing algorithm to obtain undersampled data corresponding to the unfilled position; perform image reconstruction based on the K-space data and the undersampled data to obtain a magnetic resonance image of the detection object.

[0131] In one embodiment, the above-mentioned image reconstruction module 603 is specifically configured to perform image reconstruction based on the K-space data and the undersampled data corresponding to each coil channel to obtain a magnetic resonance image corresponding to each coil channel; use an averaging algorithm to merge the magnetic resonance images of multiple coil channels to obtain a magnetic resonance image of the detection object.

[0132] In one embodiment, the above-mentioned image reconstruction module 603 is specifically configured to calculate the sensitivity of each coil according to the data in the middle filling area of the k-space corresponding to each coil channel; based on the sensitivity of each coil, iterative processing and image reconstruction processing are sequentially performed using the sensitivity algorithm and the compressed sensing algorithm to obtain the magnetic resonance image of the detection object.

[0133] For the specific limitations of the magnetic resonance imaging device, reference can be made to the limitations on the magnetic resonance imaging method in the above text, which will not be elaborated here. Each module in the above-mentioned magnetic resonance imaging device can be implemented in whole or in part by software, hardware, and their combinations. The above-mentioned modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0134] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 14 shown. The computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store magnetic resonance imaging data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a magnetic resonance imaging method.

[0135] Those skilled in the art can understand that Figure 14 the structure shown in

[0136] is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0137] Divide the k-space into multiple filling regions along the first direction and the second direction;

[0138] Use the scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals;

[0139] Fill magnetic resonance signals into multiple filling regions of the k-space to obtain k-space data; wherein, at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction have a random filling pattern;

[0140] Perform image reconstruction based on the k-space data to obtain a magnetic resonance image of the object to be detected.

[0141] In one embodiment, the above-mentioned first direction is the EPI factor encoding direction, and the above-mentioned second direction is the phase encoding direction.

[0142] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0143] Divide the k-space into multiple filling regions along the first direction and the second direction;

[0144] Use a scanning sequence to excite the object to be detected multiple times to obtain magnetic resonance signals;

[0145] Fill magnetic resonance signals into multiple filling regions of the k-space to obtain k-space data; wherein, at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction have a random filling pattern;

[0146] Perform image reconstruction based on the k-space data to obtain a magnetic resonance image of the object to be detected.

[0147] In one embodiment, the above-mentioned first direction is the EPI factor encoding direction, and the above-mentioned second direction is the phase encoding direction.

[0148] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above various methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0149] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0150] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A magnetic resonance imaging method, characterized in that, the method comprises: dividing the K-space into a plurality of filling regions along a first direction and a second direction; using a scanning sequence to excite a detection object multiple times to obtain magnetic resonance signals, the magnetic resonance signals including gradient echo signals and spin echo signals acquired each time of excitation; filling the magnetic resonance signals into the plurality of filling regions of the K-space to obtain K-space data; wherein, at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction are in a random filling pattern; along the first direction, the central region of the K-space fills the spin echo signals; two filling regions having the same filling pattern fill the gradient echo signals and are located in the edge regions of the K-space; along the second direction, multiple echo signals acquired in the same excitation are respectively filled in different filling regions, and there is a time offset between the readout gradients corresponding to different echo signals; performing image reconstruction according to the K-space data to obtain a magnetic resonance image of the detection object.

2. The method according to claim 1, characterized in that, the first direction is the EPI factor encoding direction, and the second direction is the phase encoding direction.

3. A magnetic resonance imaging method, characterized in that, the method comprises: placing a detection object in a static magnetic field and using a scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals; the readout gradients of the scanning sequence include multiple groups of alternately distributed positive-polarity readout gradients and negative-polarity readout gradients, and the magnetic resonance signals include gradient echo signals and spin echo signals acquired each time of acquisition; filling the magnetic resonance signals into the K-space to obtain K-space data; wherein, the K-space includes a first partition and a second partition that are adjacent to each other along a first direction, at least part of the magnetic resonance signals corresponding to the positive-polarity readout gradients are filled into the first partition of the K-space, at least part of the magnetic resonance signals corresponding to the negative-polarity readout gradients are filled into the second partition of the K-space, and the first partition and the second partition have the same filling pattern; the first partition fills the gradient echo signals, and there is a time offset between the positive-polarity readout gradients corresponding to the multiple gradient echo signals; the second partition fills the spin echo signals, and there is a time offset between the negative-polarity readout gradients corresponding to the multiple spin echo signals; performing image reconstruction according to the K-space data to obtain a magnetic resonance image of the detection object.

4. The method according to claim 3, characterized in that, the first partition and / or the second partition are divided into a plurality of filling regions along a second direction, and the first direction is orthogonal to the second direction.

5. The method according to claim 3, characterized in that, the scanning sequence obtains multiple magnetic resonance signals each time of excitation, and the multiple magnetic resonance signals are respectively filled into different filling regions of each partition.

6. The method according to claim 5, characterized in that, the number of filling regions in each partition is determined according to the echo train of the magnetic resonance signals corresponding to each time of excitation of the scanning sequence.

7. A magnetic resonance imaging apparatus, characterized in that, the apparatus comprises: a region division module configured to divide the k-space into a plurality of filling regions along a first direction and a second direction; a signal acquisition module configured to repeatedly excite a detection object by using a scanning sequence to acquire magnetic resonance signals, where the magnetic resonance signals include gradient echo signals and spin echo signals acquired each time; a signal filling module configured to fill the magnetic resonance signals into the plurality of filling regions of the k-space to obtain k-space data; wherein, at least two filling regions along the first direction have the same filling pattern, and the filling regions along the second direction are in a random filling pattern; along the first direction, the central region of the k-space fills the spin echo signals; two filling regions having the same filling pattern fill the gradient echo signals and are located in the edge regions of the k-space; along the second direction, a plurality of echo signals acquired in the same excitation are respectively filled in different filling regions, and there is a time shift between the readout gradients corresponding to different echo signals; an image reconstruction module configured to perform image reconstruction according to the k-space data to obtain a magnetic resonance image of the detection object.

8. A magnetic resonance imaging apparatus, characterized in that, the apparatus comprises: a signal acquisition module configured to place a detection object in a static magnetic field and repeatedly excite the detection object by using a scanning sequence to obtain magnetic resonance signals; the readout gradients of the scanning sequence include multiple sets of alternately distributed positive-polarity readout gradients and negative-polarity readout gradients, and the magnetic resonance signals include gradient echo signals and spin echo signals acquired each time; a signal filling module configured to fill the magnetic resonance signals into the k-space to obtain k-space data; wherein, the k-space includes a first partition and a second partition that are adjacent to each other along a first direction, at least part of the magnetic resonance signals corresponding to the positive-polarity readout gradients are filled into the first partition of the k-space, at least part of the magnetic resonance signals corresponding to the negative-polarity readout gradients are filled into the second partition of the k-space, and the first partition and the second partition have the same filling pattern; the first partition fills the gradient echo signals, and there is a time shift between the positive-polarity readout gradients corresponding to the multiple gradient echo signals; the second partition fills the spin echo signals, and there is a time shift between the negative-polarity readout gradients corresponding to the multiple spin echo signals; an image reconstruction module configured to perform image reconstruction according to the k-space data to obtain a magnetic resonance image of the detection object.

9. A computer device comprising a memory and a processor, where the memory stores a computer program, characterized in that, when the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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