CN116299108A - MR imaging method and system based on 3D-BUDA acquisition and combined low-rank constraint reconstruction - Google Patents
MR imaging method and system based on 3D-BUDA acquisition and combined low-rank constraint reconstruction Download PDFInfo
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Abstract
The invention provides an MR imaging method and system based on 3D-BUDA acquisition and combined low-rank constraint reconstruction, wherein the method comprises the steps of firstly acquiring a pair of multi-echo data sets with opposite phase coding directions by using a 3DGRE-EPI sequence, and accelerating acquisition in a layer coding direction by adopting a CAIPI excitation technology; then carrying out SENSE reconstruction on the multi-echo data set acquired in the step S1 to obtain images with opposite deformation so as to obtain a field map of the non-uniform distribution condition of the magnetic field; finally, the field diagram obtained in the step S2 and the multi-echo data set acquired in the step S2 are used as input of a magnetic resonance plane echo imaging reconstruction model based on Hankel low-rank constraint to obtain a non-deformation magnetic resonance image.
Description
Technical Field
The invention relates to the technical field of magnetic resonance imaging, in particular to an MR imaging method and system based on 3D-BUDA acquisition and combined low-rank constraint reconstruction.
Background
Plane echo imaging (echo planar imaging, EPI) is a rapid coding mode, is widely applied to functional imaging, diffusion imaging and quantitative parameter imaging, and has important clinical application value. However, the inherent sensitivity of EPI sequences to magnetic field uniformity is such that the reconstructed images often contain deformations, high image resolution can make the effects of deformations more severe, while low resolution, large deformation images can also affect the diagnosis of small clinically relevant lesions, which limits the wide application of this technique in the clinic.
The combination of the EPI technique and the multi-channel acquisition parallel imaging technique (SENSE: sensitivity encoding, GRAPPA: generalized autocalibrating partially parallel acquisitions, etc.) can shorten the equivalent time between adjacent phase encoding spatial lines, thereby alleviating the deformation of the image to some extent. However, these parallel imaging techniques are limited by the coil geometry (g-factor), the noise of the image is large at high acceleration times, and aliasing artifacts caused by undersampling are difficult to eliminate, so the effect of reducing distortion is limited. The buma (block-Up and-down acquisition) technique, which corrects for deformations based on field patterns, obtains field patterns of non-uniform distribution of magnetic fields by using a pair of data sets inverted by phase encoding, and then combines the field patterns with a conventional SENSE reconstruction technique to obtain an image free of deformations. However, this technique is a 2D acquisition method, and the image signal-to-noise ratio is low during high resolution imaging, and residual folding artifacts are prone to exist.
In view of the above, the invention provides an MR imaging method and system based on 3D-BUDA acquisition and combined low-rank constrained reconstruction, aiming at the problems of low signal-to-noise ratio and residual artifacts existing in the prior imaging technology.
Disclosure of Invention
The invention aims to provide an MR imaging method and system based on 3D-BUDA acquisition and combined low-rank constraint reconstruction, and aims to solve the technical problems that the image signal-to-noise ratio of MR imaging is low and residual folding artifacts are easy to exist.
To achieve the above object, in a first aspect, the present invention provides an MR imaging method based on 3D-BUDA acquisition and joint low-rank constrained reconstruction, comprising the steps of:
s1: a pair of multi-echo data sets with opposite phase coding directions are acquired by utilizing a 3D GRE-EPI sequence, and the acquisition is accelerated by adopting a CAIPI (Controlled Aliasing In Parallel Imaging control parallel imaging aliasing) excitation technology in the layer coding direction;
s2: carrying out SENSE reconstruction on the multi-echo data set acquired in the step S1 to obtain images with opposite deformation so as to obtain a field map of the non-uniform distribution condition of the magnetic field;
s3: and (3) taking the field map obtained in the step (S2) and the multi-echo data set acquired in the step (S1) as the input of a magnetic resonance plane echo imaging reconstruction model based on Hankel low-rank constraint, and obtaining a non-deformation magnetic resonance image.
As a further improvement of the above scheme, the method for acquiring a pair of multi-echo data sets with opposite phase encoding directions by using the 3D GRE-EPI sequence comprises the following steps:
the opposite polarity interleaved acquisition along the phase encoding direction results in a multi-echo EPI and produces the opposite distortion direction to obtain the B0 field pattern.
As a further improvement of the above solution, before step S2, the method further includes:
three-dimensional low-resolution fast low-angle (FLASH) acquisition is bound to the 3D-BUDA sequence and is performed before the 3D-BUDA sequence to obtain a coil sensitivity map of scan field FOV (Field of View) matching.
As a further improvement of the above scheme, in step S1, the CAIPI excitation technique is adopted to accelerate the acquisition in the slice encoding direction to acquire data of multiple slices at the same time of one excitation, so as to accelerate the data acquisition and improve the signal-to-noise ratio of the image.
As a further improvement of the above scheme, the 3D GRE-EPI sequence described in step S1 is used to acquire a dataset, and the 3D EPI sequence is used instead of the conventional 2D EPI sequence acquisition to improve the signal-to-noise ratio of the image.
As a further improvement of the above scheme, in step S2, a set of images with complementary deformation information is obtained by using a reverse encoding method, so as to obtain a field pattern of the magnetic field with uneven distribution.
As a further improvement of the above scheme, phase encoding gradients G are used respectively PE Layer gradient G z Additional gradients in the pre-phase portion of (2) acquire an edge k for each echo y And k z The dimensions have different acquisition positions of the interleaved k-space trajectory, thereby implementing up/down phases for each echoDifferent shot encodings (white and gray portions in the phase encoding gradient, respectively);
in order to reduce the signal-to-noise ratio loss caused by the restriction of a coil geometry factor (g-factor) for acquiring data with high acceleration multiple and improve the reconstruction condition, different CAIPI offsets in ky-kz dimensions are also adopted in the shots of different up/down encoding blip-up/down.
As a further improvement of the above solution, the magnetic resonance planar echo imaging reconstruction model based on Hankel low rank constraint in step S3 is:
wherein t represents the excitation index, n represents the echo index, M is the sampling template, F is the discrete Fourier transform, E is the field pattern calculated in step S2, C is the coil sensitivity information, I is the matrix Hadamard product, I is the image to be reconstructed, d is the acquired k-space data, H (I) is the Hankel low rank constraint matrix, and γ is the rank of the target image.
As a further improvement of the scheme, the magnetic resonance plane echo imaging reconstruction model based on Hankel low-rank constraint is solved by adopting an iterative hard threshold algorithm based on truncated SVD.
As a further improvement of the scheme, the root mean square error of two times before and after is adopted to judge the convergence of the iterative hard threshold algorithm based on the truncated SVD.
As a further improvement of the above scheme, the Root Mean Square Error (RMSE) is as follows:
wherein I is ref (r) is the image reconstructed from the fully sampled data, and I (r) is the image reconstructed from the downsampled data using different reconstruction methods.
As a further improvement of the above scheme, in step S3, different excitation data and different echo data are combined to construct a Hankel low-rank matrix, so that the matrix has better low-rank characteristics, and a better reconstruction effect is obtained.
In a second aspect, the invention also provides an MR imaging system comprising:
at least one memory and at least one processor, wherein:
the at least one memory is used for storing a computer program;
the at least one processor is configured to invoke the computer program stored in the at least one memory to perform the MR imaging method based on the 3D-BUDA acquisition and the joint Hankel low-rank constrained reconstruction described above.
Due to the adoption of the technical scheme, the invention has the beneficial effects that:
the invention provides an MR imaging method based on 3D-BUDA acquisition and combined Hankel low-rank constraint reconstruction, and particularly relates to an MR imaging method based on 3D-BUDA acquisition and combined Hankel low-rank constraint reconstruction, which firstly utilizes the advantage of high EPI acquisition efficiency and introduces sequence codes with opposite phase directions to compensate the distortion problem of EPI acquisition. Through the acquired images with opposite deformation directions, a B0 field map can be calculated, and then the information is introduced into a SENSE parallel imaging model, and joint low-rank constraint is added. The invention skillfully applies the encoding mode with opposite phases to obtain the EPI acquisition images with opposite deformation directions, thereby deducing the real-time change information of the B0 field. This information is introduced into the reconstruction module to correct the distortion problem of the EPI in each iteration of the joint low-rank model; according to the acquisition scheme and the combined low-rank reconstruction model, quick undistorted multi-echo high-definition imaging can be obtained, the 3D imaging technology and the CAIPI excitation technology are arranged to improve the signal to noise ratio of images, meanwhile, a Hankel-based low-rank constraint method is nested into a traditional SENSE parallel imaging image reconstruction frame, low-rank characteristics among different excitation and different echo images are constrained, so that image aliasing artifacts and reconstruction noise caused by undersampling are reduced, and the image reconstruction quality is improved; compared with the traditional SENSE and Hybrid-SENSE methods, the method has higher precision, and is embodied in lower root-mean-square-error (RMSE);
in addition, the MR imaging method based on the 3D-BUDA acquisition and the combined low-rank constraint reconstruction has strong expansibility, and can be used for other imaging technologies based on EPI sequences, such as diffusion imaging, magnetic sensitive imaging, functional magnetic resonance imaging and the like.
And the method can be applied to any number of multi-channel coil arrays meeting parallel imaging, and can be applied to from 2 to 128 coil channels.
Furthermore, from the technical aspect of the invention, the combined low-rank constraint reconstruction is used, but the invention is not limited to the image reconstruction technology, other similar low-rank reconstruction algorithms, such as LORAKS, subspace and other sparse reconstruction schemes, can be used.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings may be obtained from the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a sequence diagram of a 3D-BUDA multi-excitation multi-echo acquisition disclosed by the invention;
FIG. 2 is a schematic diagram of a 3D-BUDA reconstruction process disclosed by the invention;
FIG. 3 is a graph showing the results of a reconstruction of a set of intra-layer acceleration 4-fold data sets using different methods in an embodiment of the present invention:
FIG. 4 is a graph showing the results of reconstruction of a data set using different methods for 8-fold acceleration in layers and 1-fold and 2-fold acceleration between layers, respectively, in an embodiment of the present invention;
FIG. 5 is a graph of calculated quantitative T2 versus a reference graph for a method disclosed in an example of an embodiment of the present invention;
FIG. 6 is a graph of quantitative QSM calculated by the method disclosed in an example of an embodiment of the invention;
fig. 7 is a schematic image of 6 different levels of visual cortex activation in an example of application of the invention in fMRI.
The achievement of the object, functional features and advantages of the present invention will be further described with reference to the drawings in connection with the embodiments.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, based on the embodiments of the invention, which are apparent to those of ordinary skill in the art without inventive faculty, are intended to be within the scope of the invention.
It should be noted that all directional indicators (such as upper and lower … …) in the embodiments of the present invention are merely used to explain the relative positional relationship, movement conditions, etc. between the components in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indicator is changed accordingly.
The technical solutions of the embodiments of the present invention may be combined with each other, but it is necessary to base the implementation of those skilled in the art, and when the combination of the technical solutions contradicts or cannot be implemented, it should be considered that the combination of the technical solutions does not exist and is not within the scope of protection claimed by the present invention.
Example 1:
referring to fig. 1 and 2, the present invention provides an MR imaging method based on 3D-BUDA acquisition and joint Hankel low-rank constrained reconstruction, comprising the steps of:
s1: a pair of multi-echo data sets with opposite phase coding directions are acquired by utilizing a 3D GRE-EPI sequence, and the acquisition is accelerated by adopting a CAIPI technology in the layer coding direction; the multi-echo dataset is obtained by reverse polarity interleaved EPI acquisition along a phase encoding direction, producing opposite distortion directions to obtain a B0 field map for model-based distortion correction;
in order to obtain a coil sensitivity map with matched FOV, three-dimensional low-resolution rapid low-angle acquisition (FLASH) is bound with a 3D-BUDA sequence, and acquisition is carried out before the 3D-BUDA sequence;
s2: carrying out SENSE reconstruction on the multi-echo data set acquired in the step S1 to obtain images with opposite deformation, and further obtaining a field map of the non-uniform distribution condition of the magnetic field;
specifically, G is used separately PE And G z Additional gradients in the pre-phase portion of (2) acquire an edge k for each echo y And k z The dimensions have different acquisition positions of the interleaved k-space trajectory, so that different shot encodings of the up/down phase (white and grey parts in the phase encoding gradient, respectively) are performed for each echo;
in order to reduce the signal-to-noise ratio loss caused by g-factor restriction of high-rate undersampled data and improve reconstruction conditions, k is also adopted in the shots of different blip-up/down y -k z Different CAIPI offsets in dimensions;
s3: the coil sensitivity map, the field map and the multi-echo data acquired by S1 and S2 are used as input of a Hankel low-rank constraint-based magnetic resonance plane echo imaging reconstruction model, so that a non-deformation magnetic resonance image is obtained;
the invention introduces a 3D imaging technology and combines the CAIPI layer excitation technology to improve the signal-to-noise ratio of the image, and simultaneously, a Hankel-based low-rank constraint method is nested into a traditional SENSE parallel imaging image reconstruction frame to constrain the low-rank characteristics among different excitation and different echo images, thereby reducing image aliasing artifacts and reconstruction noise caused by undersampling and improving the image reconstruction quality; compared with the traditional SENSE and Hybrid-SENSE methods, the method has higher precision and is embodied in lower Root-Mean-Square-Error (RMSE).
As a preferred embodiment, the method of using the CAIPI excitation technique in the slice encoding direction in step S1 accelerates the acquisition of data for multiple slices at the same time as one excitation, so as to improve the signal-to-noise ratio of the image while accelerating the data acquisition.
As a preferred embodiment, the 3D GRE-EPI sequence described in step S1 is used to acquire a dataset, with the 3D EPI sequence replacing the traditional 2D EPI sequence acquisition to improve the signal-to-noise ratio of the image.
As a preferred embodiment, in step S2, a set of images with complementary deformation information is obtained by means of a reverse encoding to obtain a field pattern for the case of non-uniform magnetic field distribution.
As a preferred embodiment, the magnetic resonance planar echo imaging reconstruction model based on Hankel low rank constraint in step S3 is:
wherein t represents the excitation index, n represents the echo index, M is the sampling template, F is the fast Fourier transform, E is the field pattern calculated in step S2, C is the coil sensitivity information, I is the matrix Hadamard product, I is the image to be reconstructed, d is the acquired k-space data, H (I) is the Hankel low rank constraint matrix of the target image, and γ is the target rank.
As a preferred embodiment, an iterative hard threshold algorithm based on truncated SVD is adopted to solve the magnetic resonance plane echo imaging reconstruction model based on Hankel low-rank constraint.
As a preferred embodiment, a root mean square error of two times before and after is adopted to detect the convergence of the iterative hard threshold algorithm based on the truncated SVD; in this example, the algorithm is considered to achieve convergence when the root mean square error of the two times before and after is less than 0.1%.
As a preferred embodiment, the root mean-square error (RMSE) is formulated as follows:
wherein I is ref (r) is a reference image reconstructed from the fully sampled data, and I (r) is an image reconstructed from the downsampled data by a different reconstruction method.
As a preferred embodiment, in step S3, different excitation data and different echo data are combined to construct a Hankel low-rank matrix, so that the matrix has better low-rank characteristics, and a better reconstruction effect is obtained.
Fig. 3 shows an embodiment of the invention for single echo acquisition, data acquisition in a 3.0T magnetic resonance (Magnetom Trio System; siemens Healthineers, erlangen, germany) apparatus from siemens medical company, the set of data acquired from a 32-channel head coil, the sequence used being an EPI pulse sequence, the imaging parameters comprising: the in-layer acceleration multiple is 4 times, the in-layer acceleration multiple is 1 time, and fov=224×224×128mm 3 TR/te=72/36 ms, resolution 1x1x1mm 3 The flip angle is 16 ° (Ernst angle). As can be seen from the white arrow points of this embodiment and the positions defined by the two gray dashed lines of the first row, there is a significant distortion in the conventional SENSE reconstructed image, and both the Hybrid-SENSE and the proposed BUDA methods can correct the image distortion. Compared with Hybrid-SENSE, the MR imaging method based on 3D-BUDA acquisition and combined low-rank constrained reconstruction provided by the invention can further reduce residual noise and image reconstruction artifacts (pointed by gray arrows) caused by phase errors.
Fig. 4 to 6 show an embodiment of the multi-echo acquisition of the invention, data acquired in a 3.0T magnetic resonance (Magnetom Trio System; siemens Healthineers, erlangen, germany) apparatus of siemens medical company, the sequence used being an EPI pulse readout sequence, the imaging parameters of which include: the in-layer acceleration multiple is 8 times, the in-layer acceleration multiple is 1 or 2 times, and fov=220×220×128mm 3 Tr=86 ms, te= {18,43.17,68.34} ms, resolution 1.1x1.1x1.0mm 3 The flip angle is 19 °. Meanwhile, a group of standard 3D-GRE sequences are used for acquiring reference images, and imaging parameters are as follows: FOV = 220x220x128mm 3 Tr=86 ms, te= {6,18,30,43.17,55,68.34} ms, resolution 1.1x1.1x1.0mm 3 The flip angle is 19 °. As can be seen from fig. 4 of the present embodiment, the image residual artifact reconstructed by the MR imaging method based on the 3D-BUDA acquisition and the combined Hankel low-rank constraint reconstruction provided by the present invention is less, and RMSE is lower; at an interlayer acceleration multiple of 2, the CAIPI acquisition technique is combined (as shown in the upper right corner mask of the second line of FIG. 4, the k acquired by blip up/down z Direction of advanceLine offset), the reconstruction error is further reduced than when the interlayer is not accelerated and the CAIPI acquisition technique is not combined under the three-dimensional equivalent effective acceleration condition (RMSE: 5.98vs. 2.25%). The quantitative T2 analysis is performed in fig. 5, and it can be seen from the Bland-Altman consistency analysis in fig. 5c that, due to the combination of CAIPI and BUDA acquisition technologies, the results calculated by the MR imaging method based on 3D-BUDA acquisition and combined low-rank constrained reconstruction and the siemens reference method provided by the invention have good consistency. Based on the advantages of the method in quantitative T2 analysis, and the QSM technique also uses multi-echo sequence acquisition, the method can be further applied to quantitative QSM analysis, as shown in fig. 6.
Fig. 7 shows an example of the application of the invention in fMRI (fMRI, functional magnetic resonance imaging, functional magnetic resonance imaging), data from a 3.0T magnetic resonance (Discovery MR750, general Electric, milwaukee, WI) device from General Electric medical company in the united states, 3D EPI sequences for data acquisition, imaging modes for resting acquisition of 24s following each 24s excited state acquisition, other imaging parameters including: the head coil channel is 32 channels, FOV = 220x220x128mm 3 In-layer TR/te=75/30 ms, α≡β=15° (Ernst angle), resolution of 3.1x3.1x4.0mm 3 The intra-layer phase encoding direction acceleration factor is 2. The phase encoding direction of the full sample is up and down two sets of data, respectively, for comparison. FIG. 7 shows the results of an fMRI experiment with visual stimulus in which six levels of activation patterns are superimposed on the corresponding T 1 Weighted image. As expected, fMRI activation was observed in both visual cortex. The activation map obtained by the invention better matches brain parenchyma with visual cortex areas in the T1 weighted structure image than two independently acquired fully sampled 3D EPI images. This demonstrates the ability of the present invention to dynamically correct distortion during fMRI time over conventional methods. Comparable average activation volumes between subjects were detected (3D full sample EPI taken at blip-up alone: 30.6 cm) 3 3D full sample EPI of single blip-Down acquisition: 25.3cm 3 Results of the reconstruction according to the invention: 27.2cm 3 )。
It should be noted that, the MR imaging method based on 3D-BUDA acquisition and combined low-rank constraint reconstruction provided by the invention is essentially to introduce a 3D imaging technology and a CAIPI excitation technology to improve the signal-to-noise ratio of an image, and nest the combined Hankel-based low-rank constraint method into a traditional SENSE parallel imaging image reconstruction framework, so that the MR imaging reconstruction method is called BUDA, and is marked as BUDA in the drawing, namely, the corresponding result obtained by adopting the MR imaging reconstruction method provided by the invention.
Example 2:
in a second aspect, the invention also provides an MR imaging system comprising:
at least one memory and at least one processor, wherein:
the at least one memory is used for storing a computer program;
the at least one processor is configured to invoke the computer program stored in the at least one memory to perform the above-described MR imaging method based on 3D-BUDA acquisition and joint low-rank constrained reconstruction.
The foregoing description of the preferred embodiments of the present invention should not be construed as limiting the scope of the invention, but rather as utilizing equivalent structural changes made in the description of the present invention and the accompanying drawings or directly/indirectly applied to other related technical fields under the inventive concept of the present invention.
Claims (10)
1. An MR imaging method based on 3D-BUDA acquisition and combined low-rank constrained reconstruction, characterized by comprising the steps of:
s1: acquiring a pair of multi-echo data sets with opposite phase encoding directions by using a 3D GRE-EPI sequence and carrying out k-th encoding on the multi-echo data sets z The layer coding direction adopts a CAIPI excitation technology to accelerate acquisition;
s2: carrying out SENSE reconstruction on the multi-echo data set acquired in the step S1 to obtain images with opposite deformation so as to obtain a field map of the non-uniform distribution condition of the magnetic field;
s3: and (3) taking the field map obtained in the step (S2) and the multi-echo data set acquired in the step (S1) as the input of a magnetic resonance plane echo imaging reconstruction model based on Hankel low-rank constraint, and obtaining a non-deformation magnetic resonance image.
2. MR imaging method based on 3D-BUDA acquisition and joint low-rank constrained reconstruction according to claim 1, characterized in that the method steps of acquiring a pair of multi-echo datasets with opposite phase encoding directions using a 3D GRE-EPI sequence are:
the opposite polarity interleaved acquisition along the phase encoding direction results in a multi-echo EPI and produces the opposite distortion direction to obtain the B0 field pattern.
3. MR imaging method based on 3D-BUDA acquisition and joint low-rank constrained reconstruction according to claim 1 or 2, characterized in that it further comprises, before step S2:
binding three-dimensional low-resolution rapid low-angle acquisition with the 3D-BUDA sequence and acquiring before the 3D-BUDA sequence to obtain a coil sensitivity map with matched FOV.
4. MR imaging method based on 3D-BUDA acquisition and joint low-rank constrained reconstruction according to claim 1, characterized in that in step S1 the said phase is at k z The layer coding direction adopts the CAIPI excitation technology to accelerate the acquisition to one-time excitation and simultaneously acquire data of a plurality of layers.
5. The MR imaging method based on 3D-BUDA acquisition and joint low-rank constrained reconstruction according to claim 1, wherein in step S2, a set of images with complementary deformation information is obtained by means of a reverse encoding mode to obtain a field map of the non-uniform distribution of the magnetic field.
6. MR imaging method based on 3D-BUDA acquisition and combined low-rank constrained reconstruction according to claim 5, characterized in that phase encoding gradients G are used separately PE Layer gradient G z Additional gradients in the pre-phase portion of (2) acquire an edge k for each echo y And k z The dimensions have different acquisition positions of interleaved k-space trajectories, performing up/down for each echoAnd (4) carrying out shot coding with different phases so as to obtain an image set with complementary deformation information.
7. MR imaging method based on 3D-BUDA acquisition and joint low-rank constrained reconstruction according to claim 1 or 2, characterized in that the Hankel low-rank constrained based magnetic resonance planar echo imaging reconstruction model in step S3 is:
wherein t represents the excitation index, n represents the echo index, M is the sampling template, F is the discrete Fourier transform, E is the field pattern calculated in step S2, C is the coil sensitivity information, I is the matrix Hadamard product, I is the image to be reconstructed, d is the acquired k-space data, H (I) is the Hankel low rank constraint matrix, and γ is the target rank.
8. The MR imaging method based on 3D-BUDA acquisition and combined low-rank constrained reconstruction of claim 7, wherein the Hankel low-rank constrained magnetic resonance planar echo imaging reconstruction model is solved by using a truncated SVD-based iterative hard threshold algorithm.
9. The MR imaging method based on 3D-BUDA acquisition and joint Hankel low-rank constrained reconstruction of claim 8, wherein in step S3, different excitation and different echo data are combined to construct a Hankel low-rank matrix.
10. An MR imaging system, comprising:
at least one memory and at least one processor, wherein:
the at least one memory is used for storing a computer program;
the at least one processor is configured to invoke a computer program stored in the at least one memory to perform the MR imaging method based on 3D-BUDA acquisition and joint Hankel low-rank constrained reconstruction of any one of claims 1-9.
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