CN104597420B - Based on the magnetic resonance diffusion imaging method repeatedly excited - Google Patents
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Abstract
Present invention proposition is a kind of based on the magnetic resonance diffusion imaging method repeatedly excited, including：Measured target is repeatedly excited, and signal acquisition is carried out to measured target during exciting every time, to obtain the k-space data that the drop repeatedly excited is adopted；The k-space data that the drop repeatedly excited according to having been collected in the preset range where data point to be restored is adopted recovers the k-space data of data point to be restored, to obtain the k-space data repeatedly excited；Inverse Fourier transform is carried out to the k-space data repeatedly excited, with the image domain data repeatedly excited；The image domain data repeatedly excited is merged to generate required image.The method of the embodiment of the present invention, the motion artifacts between different excite can be effectively eliminated, can be used for the mode diffusion image of multi collect, there is provided the resolution ratio of hi-vision, reduced anamorphose, simplify process of reconstruction.
Description
Technical Field
The invention relates to the technical field of magnetic resonance, in particular to a magnetic resonance diffusion imaging method based on multiple times of excitation.
Background
The magnetic resonance diffusion imaging technology is the only image means for measuring the water molecule diffusion movement of the living body at present, senses the microscopic movement of water molecules by applying diffusion gradient to detect the microstructure of the tissue, can obtain structural information and can generate functional information, so that the technology is rapidly developed in the last decade and gradually becomes an important conventional clinical examination and scientific research tool. Currently, the diffusion Imaging method used clinically is generally single shot Planar Echo Imaging (EPI). Single shot EPI imaging is characterized by short scan time and less influence from the subject's motion, however, single shot imaging techniques also have their own drawbacks, since the acquisition bandwidth along the phase encoding direction is small, more severe image deformation can occur at different tissue junctions where the magnetic medium rates differ significantly, which also limits the spatial resolution of the image.
In order to reduce image distortion and improve image resolution, multiple excitation spread imaging has been proposed in recent years. The multiple excitations improve the acquisition bandwidth by reducing the number of phase codes acquired by each excitation, thereby effectively reducing the image deformation, achieving a larger acquisition matrix and improving the spatial resolution. However, because of the diffusion gradient applied, the moving protons are not fully phasic, resulting in a random phase error in the image during each excitation.
Phase correction in the image domain can be used to remove phase errors in multi-shot diffusion imaging. There are many methods for correcting the phase of the image domain, and generally, navigation data is acquired before each shot is imaged, phase information of each shot is obtained, and thus the phase is removed in the reconstruction process. However, the phase correction in the image domain still has the defect that the navigation data and the imaging data are required to be matched in the image domain, and in many cases, the acquisition bandwidths of the navigation data and the imaging data cannot be completely the same, so that the phase error is inaccurate, and the final image quality is affected. In this case, image registration between the imaging data and the navigation data is required, which may be troublesome for imaging and reconstruction.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art.
In view of this, the present invention needs to provide a magnetic resonance diffusion imaging method based on multiple excitations, which can be used for diffusing images in a multiple acquisition manner, effectively eliminate motion artifacts between different excitations, provide high image resolution, reduce image deformation, and avoid troubles in imaging and reconstruction processes.
According to an embodiment of the invention, a magnetic resonance diffusion imaging method based on multiple excitations is proposed, comprising the following steps:
exciting a measured target for multiple times, and acquiring signals of the measured target in the process of each excitation to acquire multi-excited acquisition-reduction k-space data;
recovering k-space data of the data point to be recovered according to the acquired descending-acquisition k-space data which is excited for multiple times and is in the preset range of the data point to be recovered so as to obtain k-space data excited for multiple times;
performing inverse Fourier transform on the multi-excitation k-space data to obtain multi-excitation image domain data; and
the image domain data for the multiple shots is combined to generate a desired image.
According to an embodiment of the invention, wherein the k-space data of the data point to be recovered is recovered by the following formula:
wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) (m, n) is the coordinate of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j (m, n) is k-space data corresponding to the jth channel of the data point to be recovered in the ith excitation, (m ', n') is coordinates of the acquired data point in the preset range where the data point to be recovered is located in the frequency encoding direction and the phase encoding direction, and d i′,j′ (m ', N ') is k-space data of the data point (m ', N ') collected by the jth channel in the preset range of the data point to be recovered in the ith ' excitation process, A is the preset range, and N is s Total number of excitations, N c Is the total number of channels, N s And N c And w (i ', j', m ', n') is a weight coefficient corresponding to the ith 'excitation, the jth' channel and the data point (m ', n').
According to an embodiment of the present invention, wherein the k-space data of the data point to be restored is restored by the following formula:
wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) K, k' e (1, NSA), (m, n) are coordinates of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j,k (m, n) is k-space data corresponding to the jth channel of the data point to be recovered in the kth acquisition and the ith excitation, (m ', n') is the coordinates of the acquired data point in the preset range of the data point to be recovered in the frequency encoding direction and the phase encoding direction, and d i′,j′,k′ (m ', N') is k-space data of the data point (m ', N') acquired by the jth channel in the preset range of the data point to be recovered in the k 'th acquisition and the ith' th excitation processes, A is the preset range, and N is the preset range s Total number of excitations, N c Total number of channels, NSA total number of acquisitions, N s 、N c And NSA is a positive integer, w (i ', j', m ', n', k ') is a weight coefficient corresponding to the kth' acquisition, the ith 'excitation, the jth' channel, and the data point (m ', n').
According to an embodiment of the present invention, the recovering the k-space data of the data point to be recovered according to the acquired multi-shot reduced-sampling k-space data within the preset range where the data point to be recovered is located to obtain the multi-shot k-space data specifically includes:
respectively recovering the phase encoding lines which are adjacent to the acquired phase encoding lines in each excitation and are not acquired according to the descending acquisition k-space data obtained in each excitation;
restoring other non-collected phase code lines in the preset range according to the collected phase code lines which are excited for multiple times and the phase code lines obtained by restoration through the following formula:
wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) K, k' e (1, NSA), (m, n) are coordinates of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j (m, n) is k-space data corresponding to the jth channel of the data point to be recovered in the ith excitation, (m ', n') is coordinates of the acquired data point in the preset range where the data point to be recovered is located in the frequency encoding direction and the phase encoding direction, and d i′,j′ (m ', N') is k-space data of the data point (m ', N') collected by the jth channel in the preset range of the data point to be recovered in the ith excitation process, A is the preset range, and N is s Total number of excitations, N c Is the total number of channels, N s And N c And w (i ', j', m ', n') is a weight coefficient corresponding to the ith 'excitation, the jth' channel and the data point (m ', n').
According to an embodiment of the present invention, the recovering, according to the acquired k-space data of the down-sampling of the multiple shots, the k-space data that is not acquired within the preset range in each shot to obtain the k-space data of the multiple shots specifically includes:
respectively recovering the phase encoding lines which are adjacent to the collected phase encoding lines and are not collected in each excitation and are in a preset number according to the descending-collection k-space data obtained in each excitation;
restoring other non-collected phase code lines in the preset range according to the collected phase code lines which are excited for multiple times and the phase code lines obtained by restoration through the following formula:
wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) K, k' e (1, NSA), (m, n) are coordinates of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j,k (m,n)For the k-space data corresponding to the jth channel of the data point to be recovered in the k-th collection and the i-th excitation, (m ', n') is the coordinates of the collected data point in the preset range of the data point to be recovered in the frequency encoding direction and the phase encoding direction, and d i′,j′,k′ (m ', N') is k-space data of the data point (m ', N') acquired by the jth channel in the preset range of the data point to be recovered in the k '-th acquisition and the ith' excitation processes, A is the preset range, and N is s Total number of excitations, N c Total number of channels, NSA total number of acquisitions, N s 、N c And NSA is a positive integer, w (i ', j', m ', n', k ') is a weight coefficient corresponding to the kth' acquisition, the ith 'excitation, the jth' channel, and the data point (m ', n').
According to an embodiment of the invention, wherein the non-acquired phase-encoded lines adjacent to the acquired phase-encoded lines in each shot are separately recovered using the GRAPPA algorithm based on the acquired k-space data obtained for each shot.
According to one embodiment of the invention, the signal acquisition is primarily multi-shot EPI diffusion imaging or multi-shot helical diffusion imaging with navigation data.
According to an embodiment of the present invention, the weight coefficients are obtained by solving linear equations constructed based on navigation data of multiple excitations.
According to an embodiment of the invention, the navigation data of the multiple shots is self-navigation data or additionally acquired navigation data.
According to one embodiment of the present invention, the method for combining the image domain data of the multiple shots mainly comprises an optimized signal-to-noise ratio method, a sum of squares (SOS) method, an adaptive reconstruction (ACC) method, a PCA method and a Singular Value Decomposition (SVD) method.
The magnetic resonance diffusion imaging method based on multiple excitations of the embodiment of the invention utilizes the correlation of multiple excitations data brought by phase errors to reconstruct images in a k space, can effectively eliminate motion artifacts among different excitations, can be used for diffusing the images in a multiple acquisition mode, further provides high image resolution, reduces image deformation, is insensitive to mismatching between navigation data and imaging data, does not need image registration, and avoids troubles in the imaging and reconstruction processes.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
figure 1 is a flow chart of a magnetic resonance diffusion imaging method based on multiple excitations according to an embodiment of the invention;
FIG. 2 is a schematic diagram of the recovery of k-space data of a data point to be recovered by equation (2) according to one embodiment of the present invention;
fig. 3 is a schematic diagram of restoring k-space data of a data point to be restored through S21 and S22 according to an embodiment of the present invention.
Detailed Description
A magnetic resonance diffusion imaging method based on multiple shots is described below with reference to the drawings, in which the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention and are not to be construed as limiting the present invention.
The embodiment of the invention provides a magnetic resonance diffusion imaging method based on multiple times of excitation.
Fig. 1 is a flow chart of a magnetic resonance diffusion imaging method based on multiple excitations according to an embodiment of the present invention.
As shown in fig. 1, the magnetic resonance diffusion imaging method based on multiple excitations according to the embodiment of the invention comprises the following steps: s1, exciting a detected target for multiple times, and acquiring a signal of the detected target in the exciting process of each time to acquire degraded acquisition k-space data excited for multiple times; s2, recovering k-space data of the data point to be recovered according to the acquired multi-time excited descending-sampling k-space data in the preset range where the data point to be recovered is located, so as to obtain multi-time excited k-space data; s3, performing inverse Fourier transform on the multi-excitation k space data to obtain multi-excitation image domain data; and S4, combining the image domain data of the multiple excitations to generate a required image.
It should be understood that in the embodiments of the present invention, the signal acquisition may employ a multi-shot imaging sequence with navigation data, such as but not limited to multi-shot planar echo imaging (EPI) diffusion imaging or multi-shot helical diffusion imaging with navigation data. Embodiments of the present invention are not limited to the kind of imaging method for multiple shots. The navigation data may be self-navigation data (for example, variable Density helical imaging, VDS for short), or may be additionally acquired navigation data.
As shown in fig. 1, the multi-shot EPI diffusion imaging method based on additionally acquired navigation data is used as an example to explain the multi-shot magnetic resonance diffusion imaging method proposed by the present invention in the embodiment of the present invention.
In step S1, a target to be measured is excited for multiple times, and signal acquisition is performed on the target to be measured during each excitation to acquire acquired k-space data of the multiple excitations.
In one embodiment of the invention, in multi-excitation diffusion weighted imaging, signal acquisition can be performed through a single-channel coil and can also be performed through a multi-channel coil.
If a multi-channel receiving radio frequency coil is used to acquire signals, the data expression of the acquired k-space is formula (1):
d i,j ＝F i S j P i f (1)
wherein d is i,j Represents the k control data collected by the jth channel in the ith excitation, i belongs to (1, N) s ),j∈(1,N c )，N s Total number of excitations, N c For the total number of channels, f is the diffusion-weighted image to be reconstructed, P i Is an index of the motion-induced phase error in the i-th excitation, S j Is the coil sensitivity coefficient of the jth channel, F i Is the fourier encoding matrix of the i-th shot.
Wherein S is j P i May be combined into one term and named sensitivity encoding term.
If the total number of excitation times is N s Then each shot of k-space data will be processed by N s And in the multiple reduction acquisition process, the reduced acquired k-space data cannot be directly combined together due to different phase errors. Therefore, image reconstruction is required through the methods of steps S2-S4, which can improve imaging efficiency and accuracy while correcting phase errors caused by free motion between different excitations, and does not require image registration, simplifying the reconstruction process, compared to the conventional method of compensating for the influence of phase errors by performing phase correction in the image domain.
In step S2, k-space data of the data point to be restored is restored according to the acquired multi-excitation multi-channel down-sampling k-space data within the preset range where the data point to be restored is located, so as to obtain multi-excitation multi-channel k-space data.
The data points to be recovered are data points acquired from k-space data. The preset range in which the data point to be restored is located may be an area of a preset size and shape with the data point to be restored as a center. The size and shape of the preset range can be set arbitrarily, and the present invention is not limited thereto.
In an embodiment of the invention, the k-space data obtained for each excitation is subjected to a different phase error P for each individual channel i Encoded with different phase errors P i And coil sensitivity coefficient S j Can be combined into one item and viewed as a phased array coilSensitivity (sensitivity coding term). Thus, the k-space data of each shot are correlated in the form of a linear convolution. That is, in the image domain, each image shot is modified by a phase factor, P i f. The basic assumption of this theory is that the resulting images have a common amplitude for each excitation. Based on this basic theory, two dimensions of the number of excitations and the number of channels of signal acquisition can be combined, and then the k-space data of each channel and each excitation can be recovered according to the acquired k-space data of the down-sampling.
In particular, k-space data of data points to be recovered can be recovered from acquired k-space data by means of interpolation. And the data point to be recovered is a coordinate point of the frequency coding direction and the phase coding direction which are not acquired.
In one embodiment of the invention, k-space data of a data point to be recovered is recovered by formula (2) or formula (3):
wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) (m, n) are the coordinates of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j (m, n) is k-space data corresponding to the jth channel of the data point to be recovered in the ith excitation, (m ', n') is the coordinates of the acquired data point in the preset range where the data point to be recovered is located in the frequency encoding direction and the phase encoding direction, and d i′,j′ (m ', N') is k-space data of the data point (m ', N') collected by the jth channel in the preset range of the data point to be recovered in the ith excitation process, A is the preset range, and N is the preset range s Total number of excitations, N c Is the total number of channels, N s And N c W (i ', j', m ', n') is a weight coefficient corresponding to the ith 'excitation, jth' channel, and data point (m ', n').
Wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) K, k' e (1, NSA), (m, n) are coordinates of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j,k (m, n) is k-space data corresponding to the jth channel of the data point to be recovered in the kth acquisition and the ith excitation, (m ', n') is the coordinates of the acquired data point in the frequency encoding direction and the phase encoding direction within the preset range of the data point to be recovered, and d i′,j′,k′ (m ', N') is k-space data of the data point (m ', N') acquired by the jth channel in the preset range of the data point to be recovered in the kth 'time acquisition and the ith' time excitation process, A is the preset range, and N is the preset range s Total number of excitations, N c The total number of channels, NSA is the total number of acquisition times (or called average times), N s 、N c And NSA is a positive integer, w (i ', j', m ', n', k ') is a weight coefficient corresponding to the kth' acquisition, the ith 'excitation, the jth' channel, and the data point (m ', n').
It should be understood that in formula (2) and formula (3), when N is c =1, in a manner of recovering k-space of the data to be recovered during signal acquisition by means of a single-channel coil, when N c &And 1, the method is a method for recovering the k space of the data to be recovered when the multi-channel coil is used for signal acquisition.
The interpolation method in the formula (2) only presents k-space data for recovering a data point to be recovered according to two dimensions of the excitation times and the channel number, and the formula (3) is used for incorporating the signal average times (NSA) into the image reconstruction process, namely expanding the interpolation process to the third dimension (signal acquisition times), so that the number of equations can be increased under the condition that the unknown number is not changed, and the condition for solving the equations is improved.
Wherein, the weight coefficient w is obtained by solving a linear equation constructed based on the navigation data of multiple times of excitation. The navigation data can be two-dimensional navigation data or three-dimensional navigation data according to actual calculation requirements. For example, the weight coefficient in formula (2) is obtained by solving a linear equation constructed from two-dimensional navigation data, and the weight coefficient in formula (3) is obtained by solving a linear equation constructed from three-dimensional navigation data. The navigation data for multiple shots may be self-navigation data or additionally acquired navigation data.
Based on formula (2), according to the collected navigation data, there is the following correspondence:
wherein the content of the first and second substances,is the Nb-th navigation k-space data point of the jth channel in the ith shot, and Nb is the total number of navigation data points; a is nb (i′,j′,m′ na ,n′ na ),i′∈(1,N s ),j′∈(1,N c ) And na is in the data pointIs provided, and the coordinates of the nth navigation k-space data point corresponding to the jth channel in the ith ' excitation in the preset range of (i ') are (m ' na ,n′ na ) Na is at the data pointThe total number of navigation data points within the preset range; w is the weight coefficient to be found. It should be noted that if the distribution modes of the data points acquired within the preset range are different, the weighting coefficients are different; therefore, there is a specific w for each arrangement, and separate equations solution is required.
Based on the formula (3), according to the collected navigation data, there is the following correspondence relationship similarly:
wherein the content of the first and second substances,is the Nb-th navigation k-space data point of the jth channel in the k-th collection and the i-th excitation, and Nb is the total number of navigation data points;
a nb (i′,j′,m′ na ,n′ na ,k′),i′∈(1,N s ),j′∈(1,N c ) K' is in the form of (1, NSA) and na is in the form of (1, na) at the data pointIs within the preset range, and the coordinates of the nth navigation k-space data point corresponding to the jth 'channel in the kth' acquisition and ith 'excitation are (m' na ,n′ na ) Na is at the data pointThe total number of navigation data points within a preset range; w is the weight coefficient to be found. Similarly, if the distribution of the data points collected in the preset range is different, the weighting coefficients are different, so that each arrangement has a specific w, and an equation solution needs to be separately constructed.
Either equation (4) or equation (5) may be equivalent to equation (6) expressed in matrix form as follows:
AW＝B (6)
wherein a, W and B are respectively equal to the matrix formed by a, W and B in the formula (4) or the formula (5), and the weight coefficient can be obtained by solving the linear equation.
The method of interpolating by formula (2) or formula (3) to recover the non-acquired k-space data may be referred to as split Encoded Parallel-imaging Technology.
Fig. 2 is a schematic diagram of recovering k-space data of a data point to be recovered by formula (2) according to an embodiment of the present invention.
As shown in fig. 2, 3 shots (shot 1, shot 2, and shot 3, respectively), 3 channels (channel 1, channel 2, and channel 3, respectively) are taken as examples for illustration (shot 2 and shot 3 collected by channel 2 are not listed).
In this embodiment, the preset range may be a rectangular area centered on the data point to be restored and having a size including all data points adjacent to the data point to be restored. For example, for the data points to be restored AA and BB in fig. 2, the corresponding preset ranges can be the areas D1 and D2, respectively. Thus, as shown in fig. 2, k-space data of the data point AA to be recovered can be recovered by interpolating formula (2) or formula (3) from k-space data acquired in the region D1 by all channels (channel 1, channel 2, and channel 3) in all excitations (excitation 1, excitation 2, and excitation 3); and can interpolate by formula (2) or formula (3) from the k-space data acquired in region D2 by all channels (channel 1, channel 2 and channel 3) in all shots (shot 1, shot 2 and shot 3) to recover the k-space data of data point BB to be recovered. Wherein kx is the frequency encoding direction and ky is the phase encoding direction.
In another embodiment of the present invention, in order to utilize the correlation of signals of different channels and shorten the computation time, the recovery process of k-space data may be implemented in two steps, that is, k-space data not acquired within a preset range in each excitation is recovered according to acquired k-space data of multi-channel down-sampling of multiple excitations, which specifically includes steps S21 and S22.
In step S21, the non-acquired phase-coded lines adjacent to the acquired phase-coded lines in each shot are respectively recovered according to the multi-channel down-sampled k-space data obtained in each shot.
The phase encoding line consists of data points, namely the acquired phase encoding line consists of a plurality of data points acquired by k-space data, and the phase encoding line to be recovered consists of a plurality of data points to be recovered.
In one embodiment of the present invention, the non-acquired phase code lines adjacent to the acquired phase code lines in each shot are respectively recovered using GRAPPA algorithm (Griswold MA, jakob PM, heidmamann RM, nittka M, jellus V, wang J, kiefer B, haase a. Generalized automatic matching parallel acquisition (GRAPPA). Magnetic Resonance in Medicine 2002 (6): 1202-1210.) based on the multi-channel down-sampled k-space data obtained by each shot.
Fig. 3 is a schematic diagram of restoring k-space data of a data point to be restored through S21 and S22 according to an embodiment of the present invention.
As shown in fig. 3, 3 shots (shot 1, shot 2, and shot 3, respectively), and 3 channels (channel 1, channel 2, and channel 3, respectively) are exemplified for explanation.
In step S21, a first phase encoding line and a sixth phase encoding line (indicated by solid black lines) are acquired for 3 channels (channel 1, channel 2, and channel 3) in the first shot (shot 1), so that phase encoding lines to be recovered (a second phase encoding line, a fifth phase encoding line, and a seventh phase encoding line) respectively adjacent to the first phase encoding line and the sixth phase encoding line can be recovered by using the GRAPPA algorithm based on k-space data acquired for three channels in the first shot. Similarly, in the second shot (shot 2), the phase-encoded lines to be recovered (the first and third phase-encoded lines, the sixth and eighth phase-encoded lines) adjacent to the second phase-encoded line and the seventh phase-encoded line, respectively, can be recovered using the GRAPPA algorithm based on the k-space data acquired by the 3 channels. In the third excitation (excitation 3), phase-encoded lines to be recovered (second and fourth phase-encoded lines, and seventh phase-encoded line) respectively adjacent to the third phase-encoded line and the eighth phase-encoded line may be recovered using GRAPPA algorithm according to k-space data acquired by 3 channels. Thereby, k-space data in which only two phase encode lines are detected is restored to k-space data having 4 phase encode lines. The phase encoding line recovered in this step is represented by a solid light gray line.
In step S22, other non-acquired phase-coded lines in the preset range are recovered according to the acquired phase-coded lines of the multi-channel excited for multiple times and the recovered phase-coded lines by formula (2) or formula (3).
As shown in fig. 3, after the recovery in step S21, there are still phase encoding lines (phase encoding lines indicated by dotted lines) in which k-space data is not acquired. Therefore, the data of all points on the phase encoding line which are not collected can be further interpolated and recovered by formula (2) or formula (3) (i.e. the SEPARATE method). The phase encoding line recovered in step S22 is represented by a solid dark gray line.
In step S3, inverse fourier transformation is performed on the multi-channel k-space data of the multiple excitations to obtain multi-channel image domain data of the multiple excitations.
In step S4, the multi-shot multi-channel image domain data is combined to generate the desired image.
In one embodiment of the present invention, the method of merging multi-shot multi-channel image domain data mainly includes the optimized signal-to-noise ratio method (Roemer PB, edelstein WA, hayes CE, souza SP, mueller om. The NMR phased array. Magnetic Resonance in Medicine 1990: 192-225.), the squaring and SOS method, the adaptive reconstruction ACC method (Walsh DO, gmro AF, marcellin MW.adaptive reception of phase array MR Imaging. Magnetic response in Medicine 2000 (5): 682-690.), the principal component analysis PCA method (Huang F, vijayakumar S, li Y, hertel S, duensing GR.A software channel compression detection with magnetic channels for surface acquisition 26 (1): 133-141) and the singular value decomposition SVD method (Zhang T, paul JM, vasanawa SS, lubricating M.coir for Imaging) 571-20169. The present invention can combine all multi-shot multi-channel image domain data into one image by, but not limited to, any of the above methods.
According to the magnetic resonance diffusion imaging method based on multiple excitations, disclosed by the embodiment of the invention, the image reconstruction is carried out in the k space by utilizing the correlation of multiple excitations data caused by phase errors, so that the motion artifacts among different excitations can be effectively eliminated, the image can be diffused in a multiple acquisition mode, the resolution of a high image is further provided, the image deformation is reduced, and the method is insensitive to the mismatching phenomenon between navigation data and imaging data, so that the image registration is not needed, and the troubles in the imaging and reconstruction processes are avoided.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a computer-readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (8)
1. A magnetic resonance diffusion imaging method based on multiple excitations is characterized by comprising the following steps:
exciting a measured target for multiple times, and acquiring signals of the measured target in the process of each excitation to acquire multi-excited down-sampling k-space data, wherein the signals are acquired through a single-channel coil or a multi-channel coil;
recovering k-space data of the data point to be recovered according to the acquired descending-acquisition k-space data which is excited for multiple times and is in the preset range of the data point to be recovered so as to obtain k-space data excited for multiple times; wherein the k-space data of the data point to be recovered is recovered by the following formula:
wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) (m, n) is the coordinate of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j (m, n) is k-space data corresponding to the jth channel of the data point to be restored in the ith excitation, (m ', n') is coordinates of the acquired data point in the preset range where the data point to be restored is located in the frequency encoding direction and the phase encoding direction, and d i′,j′ (m ', n ') is the j ' th during the i ' th excitation 'K-space data of data points (m ', N') acquired by each channel within a preset range of the data points to be restored, wherein A is the preset range, and N is the preset range s Total number of excitations, N c Is the total number of channels, N s And N c W (i ', j', m ', n') is a weight coefficient corresponding to the ith 'excitation, the jth' channel and the data point (m ', n'); and/or (b) a plurality of,
restoring k-space data for the data point to be restored by:
wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) K, k' epsilon (1, NSA), (m, n) are coordinates of the data point to be recovered in a frequency encoding direction and a phase encoding direction, d i,j,k (m, n) is k-space data corresponding to the jth channel of the data point to be recovered in the kth acquisition and the ith excitation, (m ', n') is the coordinates of the acquired data point in the preset range of the data point to be recovered in the frequency encoding direction and the phase encoding direction, and d i′,j′,k′ (m ', N') is k-space data of the data point (m ', N') acquired by the jth channel in the preset range of the data point to be recovered in the k 'th acquisition and the ith' th excitation processes, A is the preset range, and N is the preset range s Total number of excitations, N c Is the total number of channels, NSA is the total number of acquisitions, N s 、N c And NSA is a positive integer, w (i ', j', m ', n', k ') is a weight coefficient corresponding to the kth' acquisition, the ith 'excitation, the jth' channel and the data point (m ', n');
performing inverse Fourier transform on the multi-excitation k-space data to obtain multi-excitation image domain data; and combining the image domain data of the multiple shots to generate a desired image.
2. The multi-shot based magnetic resonance diffusion imaging method as claimed in claim 1, wherein the recovering the k-space data of the data point to be recovered according to the acquired k-space data of the multiple shots in the preset range where the data point to be recovered is located to obtain the k-space data of the multiple shots comprises:
respectively recovering the phase encoding lines which are adjacent to the acquired phase encoding lines in each excitation and are not acquired according to the descending acquisition k-space data obtained in each excitation;
and restoring other non-acquired phase encoding lines in the preset range according to the acquired phase encoding lines which are excited for multiple times and the phase encoding lines obtained through restoration by the following formula:
wherein i, i' is belonged to (1, N) s ),j,j′∈(1,N c ) K, k' e (1, NSA), (m, n) are coordinates of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j (m, n) is k-space data corresponding to the jth channel of the data point to be recovered in the ith excitation, (m ', n') is coordinates of the acquired data point in the preset range where the data point to be recovered is located in the frequency encoding direction and the phase encoding direction, and d i′,j′ (m ', N') is k-space data of the data point (m ', N') collected by the jth channel in the preset range of the data point to be recovered in the ith excitation process, A is the preset range, and N is s Total number of excitations, N c Is the total number of channels, N s And N c W (i ', j', m ', n') is a weight coefficient corresponding to the ith 'excitation, jth' channel, and data point (m ', n').
3. The multi-shot based magnetic resonance diffusion imaging method as claimed in claim 1, wherein the recovering the k-space data of the data point to be recovered according to the acquired k-space data of the multiple shots in the preset range where the data point to be recovered is located, so as to obtain the k-space data of the multiple shots, specifically comprises:
respectively recovering the phase encoding lines which are adjacent to the acquired phase encoding lines and are not acquired in each excitation in a preset number according to the descending acquisition k-space data obtained in each excitation;
restoring other non-collected phase code lines in the preset range according to the collected phase code lines which are excited for multiple times and the phase code lines obtained by restoration through the following formula:
wherein i, i' is epsilon (1,N) s ),j,j′∈(1,N c ) K, k' e (1, NSA), (m, n) are coordinates of the data point to be recovered in the frequency encoding direction and the phase encoding direction, d i,j,k (m, n) is k-space data corresponding to the jth channel of the data point to be recovered in the kth collection and the ith excitation, (m ', n') is coordinates of the collected data point in the preset range where the data point to be recovered is located in the frequency coding direction and the phase coding direction, and d i′,j′,k′ (m ', N') is k-space data of the data point (m ', N') acquired by the jth channel in the preset range of the data point to be recovered in the k '-th acquisition and the ith' excitation processes, A is the preset range, and N is s Total number of excitations, N c Is the total number of channels, NSA is the total number of acquisitions, N s 、N c And NSA is a positive integer, w (i ', j', m ', n', k ') is a weight coefficient corresponding to the kth' acquisition, the ith 'excitation, the jth' channel, and the data point (m ', n').
4. A multi-shot based magnetic resonance diffusion imaging method as claimed in claim 2 or 3, wherein the non-acquired phase encoding lines adjacent to the acquired phase encoding lines in each shot are respectively recovered using GRAPPA algorithm according to the acquired k-space data obtained from each shot.
5. The multi-shot based magnetic resonance diffusion imaging method of claim 1, wherein the signal acquisition is primarily multi-shot EPI diffusion imaging or multi-shot helical diffusion imaging with navigator data.
6. The multi-shot based magnetic resonance diffusion imaging method as claimed in claim 1, wherein the weight coefficients are obtained by solving a linear equation constructed based on the multi-shot navigator data.
7. The multi-shot based magnetic resonance diffusion imaging method as claimed in claim 6, wherein the multi-shot navigation data is self-navigation data or additionally acquired navigation data.
8. The multi-shot based magnetic resonance diffusion imaging method of claim 1, wherein the method of combining the multi-shot image domain data comprises mainly an optimized signal-to-noise ratio method, a sum-of-squares (SOS) method, an adaptive reconstruction (ACC) method, a Principal Component Analysis (PCA) method, and a Singular Value Decomposition (SVD) method.
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