CN114487962A - Magnetic resonance imaging method, apparatus, computer equipment and storage medium - Google Patents

Abstract

The present application relates to a magnetic resonance imaging method, apparatus, computer device and storage medium. The method comprises the following steps: dividing the K space into a plurality of filling areas along a first direction and a second direction; exciting a detection object for multiple times by using a scanning sequence to acquire a magnetic resonance signal; filling the magnetic resonance signals into a plurality of filling areas of the K space to obtain K space data; at least two filling areas along the first direction have the same filling mode, and the filling areas along the second direction are random filling modes; and carrying out image reconstruction according to the K space data to obtain a magnetic resonance image of the detection object. By adopting the method, the data acquisition speed can be improved, and the application range of the 3D GRASE sequence and the 3D EPI sequence is expanded.

Description

Magnetic resonance imaging method, apparatus, computer equipment and storage medium

technical field

The present application relates to the field of magnetic resonance technology, and in particular, to a magnetic resonance imaging method, device, computer equipment and storage medium.

Background technique

3D GRASE (GRAdient and Spin Echo, spin echo and gradient echo) sequence and 3D EPI (EchoPlanar Imaging, echo plane 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 3DGRASE sequence and the 3D EPI sequence into the K space, as shown in Figure 1.

Due to the SORT phase encoding method, phase steps appear in K-space along the encoding direction of the EPI factor, resulting in artifacts that are difficult to remove in the reconstructed image. Therefore, ETS (Echo TimeShift) technology is also combined to eliminate artifacts caused by phase steps.

However, with ETS technology, the variable density random undersampling method with high data acquisition speed cannot be used, and only the parallel imaging method with relatively low data acquisition speed can be used. Therefore, 3D GRASE sequence and 3D EPI sequence cannot be used for data acquisition speed. It is used in demanding applications (such as dynamic imaging, abdominal breath-hold imaging, etc.), which limits the clinical application scope of 3D GRASE sequences and 3D EPI sequences.

SUMMARY OF THE INVENTION

Based on this, it is necessary to provide a magnetic resonance imaging method, device and computer that can improve the data acquisition speed on the basis of using ETS technology, thereby expanding the clinical application scope of 3D GRASE sequence and 3D EPI sequence. equipment and storage media.

A magnetic resonance imaging method comprising:

dividing the K-space into a plurality of filling regions along the first direction and the second direction;

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

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 random filling patterns;

Image reconstruction is performed according to the K-space data, and the magnetic resonance image of the detection object is obtained.

In one embodiment, the first direction is an EPI factor encoding direction, and the second direction is a phase encoding direction.

A magnetic resonance imaging method comprising:

The detection object is placed in a static magnetic field, and the detection object is excited multiple times by a scanning sequence to obtain a magnetic resonance signal; the readout gradient of the scanning sequence includes multiple groups of alternately distributed positive readout gradients and negative readout gradients;

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 adjacently distributed along the first direction, and the magnetic resonance signals corresponding to the positive readout gradient are at least partially filled to K In the first partition of the space, the magnetic resonance signal corresponding to the negative readout gradient is 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;

Image reconstruction is performed according to the K-space data, and the magnetic resonance image of the detection object is obtained.

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.

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

In one of the embodiments, the number of filling regions in each partition is determined according to the echo chain of the magnetic resonance signal corresponding to each excitation of the scanning sequence.

A magnetic resonance imaging device comprising:

an area division module, which is used to divide the K space into a plurality of filling areas along the first direction and the second direction;

The signal acquisition module is used to excite the detection object multiple times by using the scanning sequence to acquire the magnetic resonance signal;

The signal filling module is used for filling the magnetic resonance signals into a plurality of filling regions in 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 have the same filling pattern. is a random fill pattern;

The image reconstruction module is used to reconstruct the image according to the K-space data to obtain the magnetic resonance image of the detection object.

In one embodiment, the first direction is an EPI factor encoding direction, and the second direction is a phase encoding direction.

A magnetic resonance imaging device comprising:

The signal acquisition module is used to place the detection object in the static magnetic field, and use the scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals; the readout gradient of the scan sequence includes multiple groups of alternately distributed positive readout gradients and negative readout gradients out gradient;

The signal filling module is used to fill the magnetic resonance signal into the K space to obtain the K space data; wherein, the K space includes the first partition and the second partition adjacently distributed along the first direction, and the magnetic resonance corresponding to the positive polarity readout gradient The signal is at least partially filled in the first sub-region of the k-space, the magnetic resonance signal corresponding to the negative readout gradient is at least partially filled in the second sub-region of the k-space, and the first sub-region and the second sub-region have the same filling pattern;

The image reconstruction module is used to reconstruct the image according to the K-space data to obtain the magnetic resonance image of the detection object.

A computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

dividing the K-space into a plurality of filling regions along the first direction and the second direction;

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

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 random filling patterns;

Perform image reconstruction according to K-space data to obtain a magnetic resonance image of the detection object; or,

Using the scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals; the readout gradient of the scan sequence includes multiple groups of alternately distributed positive readout gradients and negative readout gradients;

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 adjacently distributed along the first direction, and the magnetic resonance signals corresponding to the positive readout gradient are at least partially filled to K In the first partition of the space, the magnetic resonance signal corresponding to the negative readout gradient is 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;

Image reconstruction is performed according to the K-space data, and the magnetic resonance image of the detection object is obtained.

A computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

dividing the K-space into a plurality of filling regions along the first direction and the second direction;

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

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 random filling patterns;

Image reconstruction is performed according to the K-space data, and the magnetic resonance image of the detection object is obtained.

The above magnetic resonance imaging method, device, computer equipment and storage medium, the processor divides the K space into a plurality of 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; The resonance signal is filled into a plurality of filled areas of the K-space to obtain K-space data; image reconstruction is performed according to the K-space data to obtain a magnetic resonance image of the detection object. Due to the different partitions divided along the first direction, the magnetic resonance signals acquired by the positive and negative readout gradients have the same filling pattern. Therefore, the ETS technology can still be used to eliminate the artifacts caused by the phase step and ensure the imaging effect. And along the second direction, the fillable position of the middle filled area is less than the fillable position of the filled area on both sides, that is, there are unfilled positions in the filled area on both sides. Therefore, the compressed sensing algorithm can be used for image reconstruction, which improves the data acquisition. The speed allows 3D GRASE sequences and 3D EPI sequences to be used in applications that require high data acquisition speed, expanding the application scope of 3D GRASE sequences and 3D EPI sequences.

Description of drawings

Fig. 1 is the schematic diagram of filled K space in the background technology;

2 is an application environment diagram of the magnetic resonance imaging method in one embodiment;

3 is a schematic flowchart of a magnetic resonance imaging method in one embodiment;

4 is a schematic diagram of K-space in one embodiment;

5 is a schematic flowchart of a magnetic resonance imaging method in another embodiment;

Figure 6a is a schematic diagram of the readout gradient of a scan sequence in one embodiment;

FIG. 6b is an enlarged comparison diagram of the readout gradients corresponding to different partitions of FIG. 6a;

7 is one of the schematic flowcharts of the steps of performing image reconstruction according to K-space data to obtain a magnetic resonance image of a detection object in one embodiment;

8 is a second schematic flowchart of steps of performing image reconstruction according to K-space data to obtain a magnetic resonance image of a detection object in one embodiment;

9 is a schematic diagram of data interpolation processing in one embodiment;

Figure 10 is a schematic diagram of fully filled K-space in one embodiment;

11 is a third schematic flowchart of steps of performing image reconstruction according to K-space data to obtain a magnetic resonance image of a detection object in one embodiment;

12 is a structural block diagram of a magnetic resonance imaging apparatus in one embodiment;

13 is a structural block diagram of a magnetic resonance imaging apparatus in another embodiment;

Figure 14 is a diagram of the internal structure of a computer device in one embodiment.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

The magnetic resonance imaging method provided in this application can be applied to the application environment shown in FIG. 2 . The application environment is a magnetic resonance system. The magnetic resonance system 100 includes a bed 110, an MR scanner 120, and a processor 130. The MR scanner 120 includes a magnet, a radio frequency transmit coil, a gradient coil, and a radio frequency receive coil. The bed body 110 is used to carry the target object 010, the radio frequency transmission coil is used to transmit radio frequency pulses to the target object, and the gradient coil is used to generate a gradient field, which can be along the phase encoding direction, the slice selection direction or the frequency encoding direction, etc.; the radio frequency The receiving coil is used to receive magnetic resonance signals. In one embodiment, the magnet of the MR scanner 120 may be a permanent magnet or a superconducting magnet, and according to different functions, the radio frequency coils constituting the radio frequency unit may be divided into body coils and local coils. In one embodiment, the types of the radio frequency transmitting coil and the radio frequency receiving coil may be birdcage coils, solenoid coils, saddle coils, Helmholtz coils, array coils, loop coils, and the like. 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.

The magnetic resonance system 100 also includes a controller 140 and an output device 150, wherein the controller 140 can monitor or control the MR scanner 110, the processor 130 and the output device 150 simultaneously. The controller 140 may include a Central Processing Unit (CPU), an Application-Specific Integrated Circuit (ASIC), an Application Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (Graphics Processing Unit, One of GPU), Physical Processor (PhysicsProcessing Unit, PPU), Digital Signal Processor (Digital Processing Processor, DSP), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA), ARM processor, etc. or several combinations.

An output device 150, such as a display, may display a magnetic resonance image of the region of interest. Further, the output device 150 may also display the subject's height, weight, age, imaging site, and the working state of the MR scanner 110, and the like. The type of the output device 150 may be one or a combination of a cathode ray tube (CRT) output device, a liquid crystal output device (LCD), an organic light emitting output device (OLED), a plasma output device, and the like.

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 private network, a public switched telephone network (PSTN), the Internet, a wireless network , a virtual network, or any combination of the above.

In one embodiment, the processor 130 may control the MR scanner 120 to perform sampling at equal intervals or unequal intervals on the detection object (part of the target object 010 ), and control the MR scanner 120 to acquire the magnetic resonance signals of the detection object, and perform sampling on the detection object (part of the target object 010 ). The magnetic resonance signal is subjected to Fourier transform to obtain a magnetic resonance image of the detection object.

In one embodiment, as shown in FIG. 3, a magnetic resonance imaging method is provided, and the method is applied to the processor in FIG. 2 as an example for description, including the following steps:

Step 201: Divide the K space into a plurality of filling regions along the first direction and the second direction.

The first direction and the second direction are in an orthogonal relationship, and the K space is divided equally along the first direction. Along the second direction, the middle filling area can be set to be small, and the filling areas on both sides are large, that is, the data corresponding to the middle filling area The matrix is small, and the data matrix corresponding to the edge padding regions on both sides of the middle padding region is large. As shown in Figure 4, K space is divided into three partitions g1, g2, g3 along the first direction, and five partitions r1, r2... Fill area. Fillable positions in the middle filling regions g1r3 , g2r3 , g3r3 are less than filling positions in the filling regions g1r1 , g2r1 , g3r1 , etc. on both sides. That is, the filling density decreases sequentially from the middle area to the corresponding two side areas. Please continue to refer to FIG. 4 , the black dots in the figure indicate that the position is filled with data lines, and the white dots indicate that the position is not filled with data lines. The filling regions in the three sub-areas of g1, g2 and g3 and corresponding to the same sub-area in the second direction have the same filling pattern, that is, the patterns formed by the black dots are the same. Corresponding to a partition in the first direction, and different filling regions along the second direction have different filling patterns, that is, the patterns formed by the black dots are randomly distributed.

In one of the embodiments, 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.

Step 202 , using the scanning sequence to excite the detection object multiple times to acquire magnetic resonance signals.

Wherein, the scanning sequence may include at least one of a 3D GRASE sequence and a 3D EPI sequence, and the number of excitations may be matched with the fillable positions of the intermediate filling region. As shown in Figure 4, the number of excitations is 6, and there are 6 filling positions in the intermediate filling areas g1r3, g2r3, and g3r3 respectively. The number of echoes generated by each excitation is 5, and the five echoes are filled to the edge in a random manner. In the five filling areas such as r1-r5 divided in the second direction.

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 magnetic resonance signals generated by the detection object. The processor then acquires magnetic resonance signals from the MR scanner.

Step 203 , filling the magnetic resonance signals into a plurality of filling regions of the K-space to obtain K-space data.

Wherein, the at least two filling regions along the first direction have the same filling pattern, and the filling region along the second direction is a random filling pattern. In this embodiment of the present invention, the filling pattern of each filling area may be a pattern formed by all filling positions of the filling area.

After acquiring the magnetic resonance signals, the processor fills the magnetic resonance signals into multiple filling regions of the K space. Wherein, along the first direction, the magnetic resonance signals are filled in the corresponding filling positions of each filling region; along the second direction, the magnetic resonance signals are randomly filled in each filling region. As shown in Fig. 4, the black circles represent sequential excitations, and the filling positions of the magnetic resonance signals corresponding to each excitation in the filling region g1r1 correspond to the filling positions in the filling regions g2r1 and g3r1.

It can be understood that along the first direction, the magnetic resonance signal is filled in the corresponding filling position of each filling area. Therefore, the ETS (Echo-Time Shifting) method can still be used to eliminate the artifacts caused by the phase step and ensure the imaging effect. . Along the second direction, the fillable positions of the middle filled area are less than the fillable positions of the filled areas on both sides, that is, there are unfilled positions in the filled areas on both sides. Therefore, the compressed sensing algorithm, the parallel reconstruction algorithm or the neural network-based algorithm can be used subsequently. It can improve the speed of data acquisition, so that 3D GRASE sequence and 3D EPI sequence can be used in applications that require high data acquisition speed.

In one of the embodiments, the number of filled regions in the K-space along the second direction is determined according to the echo train of the magnetic resonance signal corresponding to each excitation of the scanning sequence. As shown in FIG. 4 , when the echo chain length is 5, the number of filling regions in the K space along the second direction is also 5.

Step 204: Perform image reconstruction according to the K-space data to obtain a magnetic resonance image of the detection object.

After obtaining the K-space data, the processor can reconstruct the image according to the K-space data by using algorithms such as Fourier transform, so as to obtain the magnetic resonance image of the detection object.

In the above magnetic resonance imaging method, the processor divides the K space into a plurality of filling regions along the first direction and the second direction; uses the scanning sequence to excite the detection object for many times to obtain magnetic resonance signals; and fills the magnetic resonance signals into the K space. A plurality of filling areas are obtained to obtain K-space data; image reconstruction is performed according to the K-space data to obtain a magnetic resonance image of the detection object. Due to the different partitions divided along the first direction, the magnetic resonance signals acquired by the positive and negative readout gradients have the same filling pattern. Therefore, the ETS technology can still be used to eliminate the artifacts caused by the phase step and ensure the imaging effect. And along the second direction, the fillable position of the middle filled area is less than the fillable position of the filled area on both sides, that is, there are unfilled positions in the filled area on both sides. Therefore, the compressed sensing algorithm can be used for image reconstruction, which improves the data acquisition. The speed allows 3DGRASE sequences and 3D EPI sequences to be used in applications that require high data acquisition speed, expanding the application scope of 3D GRASE sequences and 3D EPI sequences.

In one embodiment, as shown in FIG. 5 , a magnetic resonance imaging method is provided, and the method is applied to the processor in FIG. 2 as an example for description, including the following steps:

In step 301, the detection object is placed in a static magnetic field, and a scanning sequence is used 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 readout gradients and negative readout gradients. As shown in FIG. 6a, it is a schematic diagram of a GRASE sequence according to an embodiment of the application, wherein RF represents radio frequency pulse; Gz represents the gradient field of slice selection direction; Gy represents the gradient field of phase encoding direction; Gx represents the gradient field of readout encoding direction. In this embodiment, a plurality of 180-degree focusing pulses are applied after the 90-degree excitation pulse, and the first 180-degree focusing pulse is applied during the period after the first 180-degree focusing pulse and before the second 180-degree focusing pulse (corresponding to the partition r1). Group of frequency coding gradients with reversed positive and negative polarities, where g1 and g3 are echo signals collected by positive gradients, and g2 is the echo signals collected by negative gradients. During the period after the second 180-degree refocusing pulse and before the third 180-degree refocusing pulse (corresponding to different partitions r2), a second set of frequency encoding gradients with reversed positive and negative polarities are applied. During the period after the third 180-degree refocusing pulse and before the fourth 180-degree refocusing pulse (corresponding to partition r3), a third set of frequency encoding gradients with reversed positive and negative polarities is applied. It can be understood that there may also be more 180-degree convergent pulses, and the frequency encoding gradient set between adjacent convergent pulses, which may be specifically determined according to the size of the K-space or the type of the sequence. Furthermore, along the phase encoding direction, a peak/blip pulse is also applied at the instant of the frequency encoding gradient transition with positive and negative polarity reversed, so as to move the current phase encoding line in the K space to the next position. In this embodiment, between two adjacent convergent pulses, after the echo signal g1 is collected, the first blip pulse is applied along the phase encoding direction, and then the echo signal g2 is collected; after the echo signal g2 is collected A second blip pulse is applied in the phase-encoding direction, followed by the acquisition of the echo signal g3. 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 strength is filled in the central area of the K space, and the echo signals g1 and g3 with lower signal strength are filled in the edge area of the K space, which is beneficial to obtain a higher signal ratio and Image contrast.

FIG. 6b is an enlarged comparison diagram of readout gradients corresponding to different partitions in FIG. 6a. It can be seen from the figure that the readout gradient of the corresponding partition r2 has a first echo time offset relative to the readout gradient of the corresponding partition r1; the readout gradient of the corresponding partition r3 has a second echo time offset relative to the readout gradient of the corresponding partition r1. and the first echo time offset is different from the second echo time offset. In this embodiment, by setting in this way, the combination of the GRASE sequence and the ETS method can be realized, and the phase of the step can be changed into a continuously slowly increasing oblique line, thereby eliminating the image artifacts caused by the phase change.

The detection object is placed in the static magnetic field, 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. The processor then acquires magnetic resonance signals from the MR scanner.

In one of the embodiments, the scan sequence includes at least one of a 3D GRASE sequence and a 3D EPI sequence.

Step 302, filling the magnetic resonance signal 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 the first direction, a part or all of the magnetic resonance signal corresponding to the positive readout gradient is filled into the first partition of the K-space, and the negative readout gradient corresponds to the first partition of the K-space. Part or all of the magnetic resonance signal is filled into the second partition of k-space, and the first and second partitions have the same filling pattern; for a 3D EPI sequence, the first and second partitions may each include a filling region. For the 3D GRASE sequence, the first partition and the second partition may respectively include two, three or more padding regions, and the middle padding region is small and the two side padding regions are large.

In this embodiment, each readout gradient can be set to include 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 along the first direction for N partitions. For a readout gradient comprising N alternately distributed positive readout gradients and negative readout gradients, the magnetic resonance signal corresponding to the first positive readout gradient is filled into the _N1th partition among the N partitions (N ₁ ∈ N), the magnetic resonance signal corresponding to the first negative readout gradient is filled into the N _2th partition (N ₂ ∈ N and N ₁ ≠N ₂ ) in the N partitions, and the second positive The magnetic resonance signal corresponding to the sexual readout gradient is filled into the N3th partition (N ₃ ∈ N, N ₃ ≠N1 and N ₃ ≠N _{2 )} in the N partitions. If there are more readout gradients with positive and negative polarities, the corresponding magnetic resonance signals are filled into other different partitions in the N partitions. The magnetic resonance signal corresponding to the first positive readout gradient of each readout gradient is filled into the _N1th partition, and the magnetic resonance signal corresponding to the first negative readout gradient of each readout gradient is filled. The resonance signals are all filled into the _N2th partition, and so on. At the same time, signals of different readout gradients are filled in different partitions along the second direction of the k-space, and randomly filled within each partition along the second direction.

As shown in FIG. 4 , 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. And, the filling position of the magnetic resonance signal of each excitation in the first subsection corresponds to the filling position in the second subsection.

It can be understood that along the first direction, the magnetic resonance signals acquired by the first partition and the second partition with the corresponding positive and negative readout gradients have the same filling pattern. Therefore, the ETS technique can still be used to eliminate the phase step caused by artifacts to ensure the imaging effect. In each partition, the filling area in the middle is small, and the filling area on both sides is large, that is, there are unfilled positions in the filling area on both sides. Therefore, the compressed sensing algorithm can be used for image reconstruction in the future, so that the 3D GRASE sequence and the 3D EPI sequence can be used for image reconstruction. It is used in applications that require high data acquisition speed.

Step 303: Perform image reconstruction according to the K-space data to obtain a magnetic resonance image of the detection object.

After obtaining the K-space data, the processor can reconstruct the image according to the K-space data by using algorithms such as Fourier transform, so as to obtain the magnetic resonance image of the detection object. Optionally, the method for performing image reconstruction with K-space data may include: taking a fully sampled filling area as a calibration data point, in this embodiment, using the data point of the filling area included in the partition r3 as a calibration data point; using the calibration data point; data point synthesis filter; apply synthesis filter to other partitions to obtain multiple coupled simultaneous linear equations with multiple unknowns; and solve multiple coupled simultaneous linear equations with multiple unknowns to obtain other partitions Complete datasets, i.e. recovering data points that are not populated by other partitions.

In the above magnetic resonance imaging method, the detection object is placed in a static magnetic field, and a scanning sequence is used to excite the detection object multiple times to obtain magnetic resonance signals; the magnetic resonance signals are filled into K space to obtain K space data; The image is reconstructed to obtain the magnetic resonance image of the detection object. Due to the different partitions divided along the first direction, the magnetic resonance signals acquired by the positive and negative readout gradients have the same filling pattern. Therefore, the ETS technology can still be used to eliminate the artifacts caused by the phase step and ensure the imaging effect; In each partition, the filling area in the middle is small, and the filling area on both sides is large, that is, there are unfilled positions in the filling area on both sides. Therefore, the compressed sensing algorithm can be used for image reconstruction to improve the data acquisition speed, so that the 3D GRASE sequence and 3D EPI can be used for image reconstruction. Sequences can be used in applications that require high data acquisition speed, expanding the application range of 3DGRASE sequences and 3D EPI sequences.

In one of the embodiments, the magnetic resonance signal filling at least three filling regions is a random filling pattern. As shown in FIG. 4 , the first partition corresponding to g1 includes five filling regions g1r1 to g1r5 , and the second partition corresponding to g2 includes five filling regions g1r1 to g1r5 . For the same partition, the magnetic resonance signals can be randomly filled in each filling area, and the filling position is not defined.

In one embodiment, the scanning sequence obtains a plurality of magnetic resonance signals per excitation, and the plurality of magnetic resonance signals are respectively filled into different filling regions in each partition. As shown in Fig. 4, there are 6 excitations in total, 5 magnetic resonance signals are obtained for each excitation, and 5 magnetic resonance signals are filled into r1 to r5.

In one of the embodiments, the number of filling regions in each partition is determined according to the echo chain of the magnetic resonance signal corresponding to each excitation of the scanning sequence. As shown in FIG. 4 , the echo chain length is 5, and each partition includes 5 padding areas.

In one embodiment, the above-mentioned step of performing image reconstruction according to K-space data to obtain the magnetic resonance image of the detection object can be carried out in a variety of ways, as shown in FIG. 7 , one of the ways can include:

Step 401 , based on the K-space data, using a compressed sensing algorithm to perform iterative processing to obtain undersampled data corresponding to the unfilled positions in the K-space.

Since in each partition, the filling area in the middle is small and the filling area on both sides is large, there are unfilled positions that are not filled with magnetic resonance signals in the filling areas on both sides. Based on the filled K-space data, the compressed sensing algorithm is used for iterative processing to obtain the under-sampled data corresponding to the unfilled positions in the K-space.

Step 402: Perform image reconstruction according to the K-space data and the under-sampling data to obtain a magnetic resonance image of the detection object.

The magnetic resonance system has multiple coil channels, and image reconstruction is performed according to the K-space data and undersampling data corresponding to each coil channel to obtain the magnetic resonance image corresponding to each coil channel; The resonance images are merged to obtain a magnetic resonance image of the detection object.

It is understandable that image reconstruction is performed for each coil channel, and then the MR images of multiple coil channels are merged using the square sum algorithm, which can reduce the difference in signal amplitude caused by the difference in the relative position of each coil and the detection object. problem, so the imaging effect can be improved.

As shown in Figure 8, another approach can include:

Step 403 , based on the K-space data, use a parallel imaging algorithm to perform data interpolation processing to obtain an intermediate result corresponding to an unfilled position in the K-space.

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, and intermediate results corresponding to the unfilled positions are obtained. The number of filled locations adjacent to the unfilled locations can be determined from a preset reconstruction kernel. As shown in FIG. 9 , the preset reconstruction kernel is 3. For each unfilled position, data interpolation processing is performed according to the magnetic resonance signals in the three adjacent filled positions to obtain an intermediate result corresponding to the unfilled position. In this embodiment, the intermediate results are determined by the following methods: taking the data lines that are completely filled in the vertical direction in FIG. 9 as calibration data points; synthesizing filters using the calibration data points; A dataset of locations to obtain multiple coupled simultaneous linear equations with multiple unknowns; solve multiple coupled simultaneous linear equations with multiple unknowns to obtain a complete dataset. In another embodiment, the intermediate result is determined by the following method: obtaining calibration data points for each data set, and taking the data lines completely filled in the vertical direction in FIG. 9 as the calibration data points; for each radio frequency receiving coil, A complete k-space data set is formed according to the k-space data of the radio frequency receiving coil and the k-space data of the radio frequency receiving coils of the remaining channels; the above steps are repeated until the k-space data of the radio frequency receiving coils of all channels form a complete k-space data set .

Step 404 , based on the intermediate result, perform iterative processing with the compressed sensing algorithm to obtain the undersampled data corresponding to the unfilled position.

According to the calculated intermediate results corresponding to the unfilled positions, the compressed sensing algorithm is used for iterative processing to obtain the undersampled data corresponding to the unfilled positions. As shown in Figure 10, the gray origins represent undersampled data, and the black origins represent k-space data.

Step 405: Perform image reconstruction according to the K-space data and the under-sampling data to obtain a magnetic resonance image of the detection object.

After the under-sampling data is obtained, the under-sampling data and the K-space data fill the K-space completely. At this time, image reconstruction is performed according to the K-space data and the under-sampling data, and the magnetic resonance image of the detection object can be obtained.

As shown in Figure 11, there is another way that can include:

Step 406: Calculate the sensitivity of each coil according to the data of the middle filling area of the K space corresponding to each coil channel.

The magnetic resonance system has multiple coil channels. For each coil channel, the sensitivity of each coil is calculated using the data in the middle filled region of the K-space as a reference line. The sensitivity of each coil can represent the relative positional relationship between the coil and the detection object.

Step 407 , based on the sensitivity of each coil, use the sensitivity algorithm and the compressed sensing algorithm to sequentially perform iterative processing and image reconstruction processing to obtain a magnetic resonance image of the detection object.

After the sensitivities of the multiple coils are obtained, the sensitivity distribution of the multiple coils can be determined. After that, the sensitive algorithm and the compressed sensing algorithm are used for iterative processing to obtain the under-sampling data corresponding to the unfilled positions in the K-space, and then image reconstruction processing is performed according to the K-space data and the under-sampled data corresponding to the unfilled positions to obtain the detection object's undersampling data. Magnetic resonance images.

In the above step of performing image reconstruction according to K-space data to obtain the magnetic resonance image of the detection object, since there are unfilled positions that are not filled with magnetic resonance signals in the filling areas on both sides, the compressed sensing algorithm can be used for image reconstruction to improve the data acquisition speed , so that 3D GRASE sequences and 3D EPI sequences can be used in applications that require high data acquisition speed, expanding the application scope of 3D GRASE sequences and 3D EPI sequences.

It should be understood that although the steps in the flowcharts of FIGS. 2 to 11 are sequentially displayed according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in FIG. 2-FIG. 11 may include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but may be executed at different times. The order of execution is also not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the steps or stages within the other steps.

In one embodiment, as shown in FIG. 12, a magnetic resonance imaging apparatus is provided, comprising:

an area dividing module 501, configured to divide the K space into a plurality of filling areas along the first direction and the second direction;

a signal acquisition module 502, configured to use the scanning sequence to excite the detection object multiple times to acquire magnetic resonance signals;

The signal filling module 503 is used for filling the magnetic resonance signals into multiple filling regions in the k-space to obtain k-space data; wherein, at least two filling regions along the first direction have the same filling pattern, and filling in the second direction The area is a random fill pattern;

The image reconstruction module 504 is configured to perform image reconstruction according to the K-space data to obtain a magnetic resonance image of the detection object.

In one embodiment, the first direction is an EPI factor encoding direction, and the second direction is a phase encoding direction.

In one embodiment, as shown in FIG. 13, a magnetic resonance imaging apparatus is provided, the apparatus comprising:

The signal acquisition module 601 is used for placing the detection object in the static magnetic field, and using the scanning sequence to excite the detection object multiple times to obtain magnetic resonance signals; the readout gradient of the scan sequence includes multiple groups of alternately distributed positive polarity readout gradients and negative polarity readout gradient;

The signal filling module 602 is used to fill the magnetic resonance signal into the K-space to obtain K-space data; wherein, the K-space includes a first subregion and a second subregion that are adjacently distributed along the first direction, and the magnetic field corresponding to the positive polarity readout gradient is The resonance signal at least partially fills the first sub-region of the k-space, the magnetic resonance signal corresponding to the negative readout gradient at least partially fills the second sub-region of the k-space, and the first sub-region and the second sub-region have the same filling pattern;

The image reconstruction module 603 is configured to perform image reconstruction according to the K-space data to obtain a magnetic resonance image of the detection object.

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.

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

In one of the embodiments, the number of filling regions in each of the above partitions is determined according to the echo chain of the magnetic resonance signal corresponding to each excitation of the scanning sequence.

In one of the embodiments, the above-mentioned image reconstruction module 603 is specifically configured to perform iterative processing based on the K-space data by using the compressed sensing algorithm to obtain the under-sampled data corresponding to the unfilled positions in the K-space; The image is reconstructed to obtain the magnetic resonance image of the detection object.

In one embodiment, the above-mentioned image reconstruction module 603 is specifically configured to perform data interpolation processing using a parallel imaging algorithm based on K-space data to obtain an intermediate result corresponding to an unfilled position in the K-space; based on the intermediate result, use a compressed sensing algorithm Iterative processing is performed to obtain the under-sampling data corresponding to the unfilled position; image reconstruction is performed according to the K-space data and the under-sampling data, and the magnetic resonance image of the detection object is obtained.

In one embodiment, the above-mentioned image reconstruction module 603 is specifically configured to perform image reconstruction according to the K-space data and undersampling data corresponding to each coil channel to obtain a magnetic resonance image corresponding to each coil channel; The magnetic resonance images of the coil channels are merged to obtain a magnetic resonance image of the detection object.

In one embodiment, the above-mentioned image reconstruction module 603 is specifically configured to calculate the sensitivity of each coil according to the data of the K-space intermediate filling area corresponding to each coil channel; The perception algorithm sequentially performs iterative processing and image reconstruction processing to obtain the magnetic resonance image of the detected object.

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

In one embodiment, a computer device is provided, and the computer device may be a server, and its internal structure diagram may be as shown in FIG. 14 . The computer device includes a processor, memory, and a network interface connected by 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, an internal memory. The nonvolatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the execution of the operating system and computer programs 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. The computer program, when executed by a processor, implements a magnetic resonance imaging method.

Those skilled in the art can understand that the structure shown in FIG. 14 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied. Include more or fewer components than shown in the figures, or combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, including a memory and a processor, a computer program is stored in the memory, and the processor implements the following steps when executing the computer program:

dividing the K-space into a plurality of filling regions along the first direction and the second direction;

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

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 random filling patterns;

Image reconstruction is performed according to the K-space data, and the magnetic resonance image of the detection object is obtained.

In one embodiment, the first direction is an EPI factor encoding direction, and the second direction is a phase encoding direction.

In one embodiment, a computer-readable storage medium is provided on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

dividing the K-space into a plurality of filling regions along the first direction and the second direction;

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

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 random filling patterns;

Image reconstruction is performed according to the K-space data, and the magnetic resonance image of the detection object is obtained.

In one embodiment, the first direction is an EPI factor encoding direction, and the second direction is a phase encoding direction.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage In the medium, when the computer program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, any reference to memory, storage, database or other media used in the various embodiments provided in this application may include at least one of non-volatile and volatile memory. The non-volatile memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, and the like. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, the RAM may be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM).

The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features It is considered to be the range described in this specification.

The above-mentioned embodiments only represent several embodiments of the present application, and the descriptions thereof are specific and detailed, but should not be construed as a limitation on the scope of the invention patent. It should be pointed out that for those skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the scope of protection of the patent of the present application shall be subject to the appended claims.

Claims (10)

1. A magnetic resonance imaging method, characterized in that the method comprises:

dividing the K space into a plurality of filling areas along a first direction and a second direction;

exciting a detection object for multiple times by using a scanning sequence to acquire a magnetic resonance signal;

filling the magnetic resonance signals into a plurality of filling areas of the K space to obtain K space data; at least two filling areas along the first direction have the same filling pattern, and the filling areas along the second direction have a random filling pattern;

and carrying out image reconstruction according to the K space data to obtain a magnetic resonance image of the detection object.

2. The method of claim 1, wherein the first direction is an EPI-factor encoding direction and the second direction is a 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 exciting the detection object for multiple times by using a scanning sequence to obtain a magnetic resonance signal; the readout gradients of the scan sequence comprise a plurality of sets of positive readout gradients and negative readout gradients distributed alternately;

filling the magnetic resonance signals into a K space to obtain K space data; the magnetic resonance signals corresponding to the positive polarity readout gradients are at least partially filled into the first partition of the K space, 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 mode;

and carrying out image reconstruction according to the K space data to obtain a magnetic resonance image of the detection object.

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

5. A method as claimed in claim 3, wherein the scan sequence acquires a plurality of magnetic resonance signals per excitation, and the plurality of magnetic resonance signals are filled into different filling regions of the respective sub-regions.

6. The method of claim 5, wherein the number of filling regions in each of the segments is determined based on an echo train of each excitation of a corresponding magnetic resonance signal of the scan sequence.

7. A magnetic resonance imaging apparatus, characterized in that the apparatus comprises:

the area dividing module is used for dividing the K space into a plurality of filling areas along a first direction and a second direction;

the signal acquisition module is used for exciting the detection object for multiple times by utilizing the scanning sequence to acquire a magnetic resonance signal;

the signal filling module is used for filling the magnetic resonance signals into a plurality of filling areas of the K space to obtain K space data; at least two filling areas along the first direction have the same filling pattern, and the filling areas along the second direction have a random filling pattern;

and the image reconstruction module is used for reconstructing an image 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:

the signal acquisition module is used for placing a detection object in a static magnetic field and exciting the detection object for multiple times by utilizing a scanning sequence to obtain a magnetic resonance signal; the readout gradients of the scan sequence comprise a plurality of sets of positive readout gradients and negative readout gradients distributed alternately;

the signal filling module is used for filling the magnetic resonance signals into a K space to obtain K space data; the magnetic resonance signals corresponding to the positive polarity readout gradients are at least partially filled into the first partition of the K space, 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 mode;

and the image reconstruction module is used for reconstructing an image 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, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.

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