Magnetic resonance imaging method, device, equipment and medium based on multi-segment simultaneous excitation

Abstract

The present application relates to the field of image processing technology, and in particular to a magnetic resonance imaging method, device, equipment and medium based on multi-segment simultaneous excitation, including: using a multi-segment simultaneous excitation imaging sequence with added parallel imaging gradient control aliasing to acquire multi-channel k-space data; establishing a four-dimensional k-space signal model, dividing the gradient encoding of the layer direction corresponding to the sequence diagram into intra-segment encoding and inter-segment encoding, and forming the above data into a four-dimensional k-space signal; correcting the interference phase of the four-dimensional k-space signal generated by the intra-segment and inter-segment encoding sharing the same physical z-axis, and reconstructing the image based on this to generate the magnetic resonance imaging result of the target object. Therefore, the present application can apply the blipped-CAIPI technology to eliminate the phase interference of the intra-segment and inter-segment encoding sharing the same physical z-axis, and is suitable for the simultaneous excitation of multiple three-dimensional thick segments, EPI imaging signal acquisition and image reconstruction of any form and contrast, and improves the acquisition efficiency and image signal-to-noise ratio.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a magnetic resonance imaging method, device, equipment and medium based on multi-segment simultaneous excitation. Background Art

[0002] MRI (magnetic resonance imaging) is a non-ionizing radiation, non-invasive medical imaging technology with excellent soft tissue contrast. It is an important method in clinical examination and neuroscience research. For EPI (echo-planarimaging), the acquisition modes of MRI include two-dimensional acquisition and three-dimensional acquisition: the traditional two-dimensional acquisition method is efficient, but the SNR (signal-to-noise ratio) is limited; although the three-dimensional acquisition method can achieve a higher spatial resolution or SNR, the acquisition time is too long. Therefore, a series of two-dimensional / three-dimensional hybrid acquisition methods have been proposed. SMS (simultaneous multi-slice) technology acquires by simultaneously exciting multiple layers, and the number of layers excited simultaneously is measured by the MB (multi-band) factor. 3D multi-slab imaging divides the imaging field of view in the layer direction into multiple three-dimensional thick segments and excites them one by one (MB=1). For each thick segment, the phase encoding in the layer direction is used to reconstruct different layers in the segment. SMSlab (simultaneous multi-slab) imaging is an acquisition technology that combines three-dimensional multi-segment imaging and multi-layer simultaneous excitation, that is, MB>1. Among them, the phase encoding for reconstructing different thin layers in each segment is called intra-segment encoding, and the phase encoding for the simultaneously excited inter-segment images is called inter-segment encoding.

[0003] In two-dimensional multi-segment simultaneous excitation imaging, the parallel blipped-CAIPI (blipped-controlled aliasing in parallel imaging) technique can be used to introduce different degrees of imaging field of view offset in the phase encoding direction in each layer of the simultaneously excited image, thereby making full use of the coil sensitivity information and reducing the signal-to-noise ratio loss related to the geometric arrangement of the coil sensitivity. However, in SMSlab imaging, the challenge of applying the blipped-CAIPI technique to SMSlab imaging is that both intra-segment encoding and inter-segment encoding require the use of the gradient axis in the layer direction, while there is only one physical z-axis in actual imaging, which needs to be shared by the two. However, sharing a physical z-axis will cause intra-segment encoding and inter-segment encoding to interfere with each other, and they will no longer be encoded independently of each other. Special means are needed to handle signal acquisition in this case. Summary of the invention

[0004] The present application provides a magnetic resonance imaging method, device, electronic device and storage medium based on multi-segment simultaneous excitation, which can eliminate the phase interference of sharing the same physical z-axis between the intra-segment coding and inter-segment coding dimensions, so that the blipped-CAIPI acceleration technology can be applied to multi-segment simultaneous excitation imaging, improve the acquisition efficiency and image signal-to-noise ratio, and improve the scanning quality; and it is suitable for simultaneous excitation of multiple three-dimensional thick segments, arbitrary contrast, and arbitrary form of EPI imaging signal acquisition and image reconstruction, and has a wide range of applications.

[0005] The first aspect of the present application provides a magnetic resonance imaging method based on multi-segment simultaneous excitation, comprising the following steps: Step S101: Use a multi-segment simultaneous excitation imaging sequence with an added parallel imaging gradient control aliasing function to perform data acquisition to obtain multi-channel k-space data; Step S102: Establish a four-dimensional k-space signal model, divide the gradient encoding in the layer direction corresponding to the sequence diagram into intra-segment encoding and inter-segment encoding, and form the acquired k-space data into a four-dimensional k-space signal; Step S103: Correct the interference phase of the four-dimensional k-space signal caused by the intra-segment encoding and the inter-segment encoding sharing the same physical z-axis, and perform image reconstruction based on the corrected four-dimensional k-space signal to generate a magnetic resonance imaging result of the target to be imaged.

[0006] Optionally, the method is applicable to echo planar imaging of multiple three-dimensional thick segments with any contrast and any form simultaneously excited, and the step S101 specifically includes: applying a kz coding gradient along the layer direction for intra-segment coding, and the kz gradient area size is:

[0007] A z =n kz ·2π / (γ·FOV z ),

[0008] Among them, n kz k z Coding number, γ is the gyromagnetic ratio constant, FOV z is the thickness of each segment; and during the EPI readout process, k with alternating polarity is applied along the layer direction m The gradient is used for inter-segment coding, the k m The gradient area size is:

[0009] A blip =2π / (γ·Δz m ·R m ),

[0010] Where γ is the gyromagnetic ratio constant, Δz m is the center distance of adjacent segments excited simultaneously, R m is the number of segments excited simultaneously; and / or when used for diffusion weighted imaging, in each k z During the encoding process, the navigation echo is collected to obtain each k z Phase information of the excitation.

[0011] Optionally, the four-dimensional k-space signal model pre-established in step S102 is:

[0012]

[0013] Among them, n m ∈[0,R m -1] is the sequence number of the image domain in the inter-segment coding direction, n km ∈[0,R m -1] is the serial number of the four-dimensional k-space in the inter-segment encoding direction, n z ∈[0,N z -1] is the sequence number of the image domain in the encoding direction within the segment, n kz ∈[-N z / 2,N z / 2-1] is the serial number of the encoding direction of the four-dimensional k-space within the segment, s(n km ,n kz ) is the nth dimension along the inter-segment coding dimension in the four-dimensional k-space km codes, along the intra-segment coding dimension nth kz The coded signal, μ(n m ,n z ) is the nth simultaneously excited m The nth paragraph z The signal of the layer, k x , k y , k m and k z represents the four dimensions of the four-dimensional k-space, where k m and kz denote the inter-segment coding dimension and the intra-segment coding dimension respectively, and x, y, m and z denote the four dimensions of the image domain; k z The phase of inter-segment interference caused by the gradient, k m Phase of intra-segment interference caused by gradient.

[0014] Optionally, in step S103, correcting the interference phase of the four-dimensional k-space signal caused by the intra-segment coding and the inter-segment coding sharing the same physical z-axis includes: z Gradient-induced inter-segment interference phase Phase compensation is applied to the RF pulses in multiple simultaneous excitation sequences to eliminate Or through the preset reconstruction algorithm, the four-dimensional k-space signal is reconstructed along k m The dimension is one-dimensionally inverse Fourier transformed, and the linear phase is corrected after the Fourier transform, or a circular shift is performed in the image domain; for k m Phase of linear interference within a segment caused by gradient When it belongs to the non-diffusion weighted data type, the four-dimensional k-space signal along k z Dimensional one-dimensional inverse Fourier transform, for each k m The coded signals are corrected from different layer positions Or when it belongs to the diffusion weighted data type, it is corrected sequentially or simultaneously by a preset reconstruction algorithm and different k z Phase difference caused by motion between excitations; when applied to diffusion-weighted imaging, for different k z The phase difference caused by inconsistent motion between excitations is removed based on the navigation echo; when the actual position of the reference layer corresponding to the excitation segment is not at the center of the physical z-axis gradient during multi-segment simultaneous excitation imaging, the relative position of the reference layer and the center of the physical z-axis gradient is calculated based on the actual position, and the relative position is corrected in k z and k m The off-center phase error caused by the gradient.

[0015] The second aspect of the present application provides a magnetic resonance imaging device based on multi-segment simultaneous excitation, including: an acquisition module, used to acquire data through a multi-segment simultaneous excitation imaging sequence with a parallel imaging gradient control aliasing function added to obtain multi-channel k-space data; a modeling module, used to establish a four-dimensional k-space signal model, divide the gradient encoding in the layer direction corresponding to the sequence diagram into intra-segment encoding and inter-segment encoding, and form the acquired k-space data into a four-dimensional k-space signal; a reconstruction module, used to correct the interference phase of the four-dimensional k-space signal caused by the intra-segment encoding and the inter-segment encoding sharing the same physical z-axis, and perform image reconstruction based on the corrected four-dimensional k-space signal to generate a magnetic resonance imaging result of the target to be imaged.

[0016] Optionally, the method is applicable to echo planar imaging of multiple three-dimensional thick segments simultaneously excited with any contrast and any form, and the acquisition module is further used to: apply a kz coding gradient along the layer direction for intra-segment coding, and the kz gradient area size is:

[0017] A z =n kz ·2π / (γ·FOV z ),

[0018] Among them, n kz is the kz encoding number, γ is the gyromagnetic ratio constant, FOV z is the thickness of each segment; and during the EPI readout process, a km gradient with alternating polarity is applied along the layer direction for inter-segment encoding, and the km gradient area size is:

[0019] A blip =2π / (γ·Δz m ·R m ),

[0020] Where γ is the gyromagnetic ratio constant, Δz m is the center distance of adjacent segments excited simultaneously, R m is the number of segments excited simultaneously; and / or when used for diffusion weighted imaging, during each kz encoding process, the navigation echo is collected to obtain the phase information of each kz excitation.

[0021] Optionally, the four-dimensional k-space signal model pre-established by the modeling module is:

[0022]

[0023] Among them, n m ∈[0,R m -1] is the sequence number of the image domain in the inter-segment coding direction, n km ∈[0,R m -1] is the serial number of the four-dimensional k-space in the inter-segment encoding direction, nz ∈[0,N z -1] is the sequence number of the image domain in the encoding direction within the segment, n kz ∈[-N z / 2,N z / 2-1] is the serial number of the encoding direction of the four-dimensional k-space within the segment, s(n km ,n kz ) is the nth dimension along the inter-segment coding dimension in the four-dimensional k-space km codes, along the intra-segment coding dimension nth kz The coded signal, μ(n m ,n z ) is the nth simultaneously excited m The nth paragraph z The signal of the layer, k x , k y , k m and k z represents the four dimensions of the four-dimensional k-space, where k m and k z Tables represent intra-segment coding dimensions and inter-segment coding dimensions respectively, and x, y, m and z represent four dimensions of the image domain; k z The phase of inter-segment interference caused by the gradient, k m Phase of intra-segment interference caused by gradient.

[0024] Optionally, the reconstruction module is further used for: for k z Gradient-induced inter-segment interference phase Phase compensation is applied to the RF pulses in multiple simultaneous excitation sequences to eliminate Or through the preset reconstruction algorithm, the four-dimensional k-space signal is reconstructed along k m The dimension is one-dimensionally inverse Fourier transformed, and the linear phase is corrected after the Fourier transform, or a circular shift is performed in the image domain; for k m Phase of linear interference within a segment caused by gradient When it belongs to the non-diffusion weighted data type, the four-dimensional k-space signal along k z Dimensional one-dimensional inverse Fourier transform, for each k m The coded signals are corrected from different layer positions Or when it belongs to the diffusion weighted data type, it is corrected sequentially or simultaneously by a preset reconstruction algorithm and different k z Phase difference caused by motion between excitations; when applied to diffusion-weighted imaging, for different k zThe phase difference caused by inconsistent motion between excitations is removed based on the navigation echo; when the actual position of the reference layer corresponding to the excitation segment is not at the center of the physical z-axis gradient during multi-segment simultaneous excitation imaging, the relative position of the reference layer and the center of the physical z-axis gradient is calculated based on the actual position, and the relative position is corrected in k z and k m The off-center phase error caused by the gradient.

[0025] A third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the magnetic resonance imaging method based on multi-segment simultaneous excitation as described in the above embodiment.

[0026] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the magnetic resonance imaging method based on multi-segment simultaneous excitation as described in the above embodiments.

[0027] Therefore, this application has at least the following beneficial effects:

[0028] The parallel imaging gradient control aliasing function can be used in multi-segment simultaneous excitation imaging to solve the phase interference problem caused by intra-segment coding and inter-segment coding sharing the same physical z-axis, decouple the two coding dimensions into two independent dimensions, improve the image signal-to-noise ratio, and improve the scanning quality; it can be applicable to the simultaneous excitation of multiple three-dimensional thick segments, using blipped-CAIPI technology, any contrast, any form of EPI (including gradient echo EPI, spin echo EPI and other possible forms of EPI) imaging signal acquisition and image reconstruction, and has a wide range of applications; and the embodiment of the present application also performs special processing for the special properties of diffusion imaging: by collecting additional navigation echoes or using other forms to obtain navigation echo information, and performing phase correction between different excitations caused by physiological movement in reconstruction; it can also include the use of motion compensated (1st order or 2nd order at the same time) diffusion coding gradient to eliminate the influence of movement between different excitations.

[0029] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0031] Figure 1 A flowchart of a magnetic resonance imaging method based on multi-segment simultaneous excitation provided according to an embodiment of the present application;

[0032] Figure 2 A schematic diagram of a blipped-SMSlab sequence for simultaneously exciting two segments and a sampling diagram thereof provided according to an embodiment of the present application;

[0033] Figure 3 A schematic diagram of SMSlab excitation and its four-dimensional k-space provided according to an embodiment of the present application;

[0034] Figure 4 Schematic diagram of SMSlab excitation and k according to the embodiment of the present application z and k m Phase distribution after encoding;

[0035] Figure 5 According to the embodiment of the present application, The blipped-SMSlab non-diffusion weighted (b=0) image results before and after correction;

[0036] Figure 6 According to the embodiment of the present application, Blipped-SMSlab non-diffusion weighted (b=0) and diffusion weighted (b=1000s / mm) images before and after correction 2 )Image result graph;

[0037] Figure 7 A comparison diagram of SMSlab image reconstruction performance between blipped-CAIPI sampling and non-CAIPI sampling provided according to an embodiment of the present application;

[0038] Figure 8 A comparison diagram of diffusion imaging using blipped-SMSlab and traditional 2D blipped-SMS according to an embodiment of the present application;

[0039] Fig. 9 An exemplary diagram of a magnetic resonance imaging device based on multi-segment simultaneous excitation is provided according to an embodiment of the present application;

[0040] Fig.10 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application.

[0041] Description of reference numerals:

[0042] Figure 2 Figure a is a blipped-SMSlab sequence diagram provided according to an embodiment of the present application, Figure b is a schematic diagram of four-dimensional k-space sampling provided according to an embodiment of the present application, and Figure c is a schematic diagram of existing non-CAIPI sampling in a four-dimensional k-space framework provided according to an embodiment of the present application; Figure 3Figures a and b in the figure show the image domain and k-space respectively. 4D FT means four-dimensional Fourier transform. Figure 3 k is not shown in x dimension, each dot can represent the entire row k x coding; Figure 8 The first three columns show the anisotropy map FA, and the fourth column shows the fiber orientation distribution function map ODF. DETAILED DESCRIPTION

[0043] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0044] The following describes the magnetic resonance imaging method, device, electronic device and storage medium based on multi-segment simultaneous excitation of the embodiment of the present application with reference to the accompanying drawings. In response to the problems mentioned in the above background technology, the present application provides a magnetic resonance imaging method based on multi-segment simultaneous excitation, which can eliminate the phase interference of sharing the same physical z-axis for the intra-segment coding and inter-segment coding dimensions, so that the parallel imaging gradient controlled aliasing (blipped-CAIPI) acceleration technology can be applied to multi-segment simultaneous excitation imaging, improve the acquisition efficiency and image signal-to-noise ratio, and improve the scanning quality; and it is suitable for simultaneous excitation of multiple three-dimensional thick segments, arbitrary contrast, and any form of EPI imaging signal acquisition and image reconstruction, and has a wide range of applications.

[0045] Specifically, Figure 1 A schematic flow chart of a magnetic resonance imaging method based on multi-segment simultaneous excitation provided in an embodiment of the present application.

[0046] like Figure 1 As shown, the magnetic resonance imaging method based on multi-segment simultaneous excitation includes the following steps:

[0047] In step S101, a multi-segment simultaneous excitation imaging sequence with blipped-CAIPI (SMSlab based on blipped-CAIPI) function is used to collect data and obtain multi-channel k-space data.

[0048] This sequence is suitable for planar echo imaging with multiple three-dimensional thick segments of any contrast and any form excited simultaneously.

[0049] It can be understood that the embodiment of the present application can use the four-dimensional k-space concept in SMSlab imaging, and can use the blipped-CAIPI sampling mode under the four-dimensional k-space framework, wherein the k y -km The dimension uses the blipped-CAIPI sampling mode such as Figure 3 As shown in Figure b, the traditional non-CAIPI sampling mode in the four-dimensional k-space framework is as follows Figure 3 As shown in Figure c in the figure. The four-dimensional k-space will be described in the following embodiments, and will not be repeated here to avoid redundancy.

[0050] In the embodiment of the present application, step S101 specifically includes:

[0051] The kz coding gradient is applied along the layer direction for intra-segment coding, and the kz gradient area size is:

[0052] A z =n kz ·2π / (γ·FOV z ),

[0053] Among them, n kz k z Coding number, γ is the gyromagnetic ratio constant, FOV z is the thickness of each segment; and

[0054] During the EPI readout process, a k-pole with alternating polarity is applied along the layer direction. m The gradient (i.e., blipped-CAIPI gradient) is used for inter-segment coding, k m The gradient area size is:

[0055] A blip =2π / (γ·Δz m ·R m ),

[0056] Where γ is the gyromagnetic ratio constant, Δz m is the center distance of adjacent segments excited simultaneously, R m is the number of segments that are excited simultaneously; and / or

[0057] When used for diffusion-weighted imaging, at each k z During the encoding process, the navigation echo is collected to obtain each k z The phase information of the excitation.

[0058] It is understandable that the present application embodiment may use a blipped-SMSlab (SMSlab based on blipped-CAIPI) sequence, such as Figure 2 As shown in Figure a, based on the two-dimensional EPI imaging sequence, k z Encoding, k z The gradient area is A z =n kz ·2π / (γ·FOV z ), where nkz k z Coding number, γ is the gyromagnetic ratio constant, FOV z is the thickness of each segment; the imaging echo is collected after the refocusing pulse; the imaging echo is at k x -k y The dimension is acquired using EPI, which can be applied to both single and multiple excitations. If the blipped-SMSlab sequence is used to acquire diffusion-weighted images, it is necessary to apply a diffusion-weighted gradient before and after the first refocusing pulse, and apply a second refocusing pulse after the imaging echo; before the second refocusing pulse, apply a reverse k z Encoded gradient, k before EPI readout z The coding phase is offset; after the second refocusing pulse, a two-dimensional navigation echo is collected to record each k z Phase changes caused by physiological motion during excitation. Navigator echo in k x -k y The dimension is acquired using single-shot EPI, and the number of excitation segments is consistent with the imaging echo. Blipped-CAIPI is achieved by applying k m Encoding gradient, application time and k applied during EPI readout y The encoding gradient is consistent, the applied width is also consistent, and the adjacent k m The effective gradient area increment corresponding to the encoding is A blip =2π / (γ·Δz m ·R m ), where γ is the gyromagnetic ratio constant.

[0059] It should be noted that the navigation echo is x -k y The dimension can be reduced or fully mined, and its k x -k y When downsampling, both blipped-CAIPI sampling and non-CAIPI sampling are applicable. m Pre-rewind gradients, such as R m =2, so that n km ∈[0,1] becomes n km ∈[-1 / 2,1 / 2], the embodiment of the present application is still applicable. Among them, the blipped-CAIPI sampling mode in the four-dimensional k-space framework is as follows Figure 2 As shown in Figure b, along k m -k y The blipped-CAIPI sampling mode is used in the four-dimensional k-space framework; the traditional non-CAIPI sampling mode in the four-dimensional k-space framework is as follows Figure 2 As shown in Figure c.

[0060] In step S102, a four-dimensional k-space signal model is established, the gradient coding in the layer direction corresponding to the sequence diagram is divided into intra-segment coding and inter-segment coding, and the collected k-space data is formed into a four-dimensional k-space signal.

[0061] It is understandable that if Figure 3 As shown in Figure a, when the four-dimensional k-space concept is used in SMSlab imaging, the embodiment of the present application can split the encoding in the layer direction into two dimensions: intra-segment encoding and inter-segment encoding, respectively using k z and k m Indicates that Figure 3 As shown in Figure b.

[0062] Specifically, for the complete SMSlab four-dimensional k-space, the images of multiple internal thin layers excited simultaneously can be reconstructed by iFT (inverse Fourier transformation). In the four-dimensional Fourier transform relationship, the dimensions of the image domain and k-space are xymz and k respectively. x -k y -k m -k z express.

[0063] like Figure 3 As shown, the resolution Δz corresponding to the intra-segment coding is defined as the layer thickness of the thin layer image to be reconstructed, and its field of view size is FOV z =N z Δz, where FOV z is the thickness of each segment, N z is the number of thin layers contained in each segment (including oversampling layers); the resolution Δz corresponding to the inter-segment coding m It is defined as the center distance of the segments excited simultaneously, and its field of view size is FOV m =R m Δz m , where R m is the number of segments excited simultaneously; the k-space encoding step sizes of the two are Δk z =1 / FOV z , Δk m =1 / FOV m .

[0064] In the embodiment of the present application, the pre-established four-dimensional k-space signal model is:

[0065]

[0066] Among them, n m ∈[0,R m-1] is the sequence number of the image domain in the inter-segment coding direction, n km ∈[0,R m -1] is the sequence number of the four-dimensional k-space in the inter-segment coding direction, n z ∈[0,N z -1] is the sequence number of the image domain in the encoding direction within the segment, n kz ∈[-N z / 2,N z / 2-1] is the serial number of the encoding direction of the four-dimensional k-space within the segment, s(n km ,n kz ) is the nth dimension along the inter-segment coding dimension in the four-dimensional k-space km codes, along the intra-segment coding dimension nth kz The coded signal, μ(n m ,n z ) is the nth simultaneously excited m The nth paragraph z The signal of the layer, k x , k y , k m and k z Represents the four dimensions of the four-dimensional k-space, where k m and k z They represent the inter-segment coding dimension and the intra-segment coding dimension respectively, and x, y, m and z represent the four dimensions of the image domain; k z The phase of inter-segment interference caused by the gradient, k m Phase of intra-segment interference caused by gradient.

[0067] It can be understood that according to the formula of the pre-established four-dimensional k-space signal model, when k z and k m When the codes share the same physical z-axis, due to the segment spacing Δz m In k z Phase shift occurs under the effect of coding gradient And k m The encoded gradient introduces an additional set of linearly varying phases at different layer positions in each segment Therefore, the intra-segment coding and inter-segment coding dimensions are not independent of each other, that is, the four-dimensional k-space signal model cannot directly meet the four-dimensional Fourier coding conditions. Therefore, the embodiment of the present application can correct the above two interference phases in step S103.

[0068] In step S103, correcting the interference phase of the four-dimensional k-space signal caused by intra-segment coding and inter-segment coding sharing the same physical z-axis includes:

[0069] For k z Gradient-induced inter-segment interference phase

[0070] Phase compensation is applied to the RF pulses in multiple simultaneous excitation sequences to eliminate Or through the preset reconstruction algorithm, the four-dimensional k-space signal is reconstructed along k m Perform one-dimensional inverse Fourier transform on the image dimension and correct the linear phase after Fourier transform, or perform cyclic shift in the image domain;

[0071] For k m Phase of linear interference within a segment caused by gradient

[0072] When it belongs to the non-diffusion weighted data type, the four-dimensional k-space signal along k z Dimensional one-dimensional inverse Fourier transform, for each k m The coded signals are corrected from different layer positions Or when it belongs to the diffusion weighted data type, it is corrected sequentially or simultaneously by a preset reconstruction algorithm and different k z Phase differences between excitations due to motion;

[0073] When applied to diffusion-weighted imaging, for different k z Phase differences caused by inconsistent motion between excitations are removed based on the navigation echo;

[0074] When the actual position of the reference layer corresponding to the excitation segment is not at the center of the physical z-axis gradient during multi-segment simultaneous excitation imaging, the relative position of the reference layer and the center of the physical z-axis gradient is calculated based on the actual position, and the relative position is corrected in k z and k m The off-center phase error caused by the gradient.

[0075] It should be noted that, assuming that the sequence number of the bottom segment among all segments excited simultaneously is n m =0, the sequence number of the bottom layer in the segment is n z =0 (hereinafter referred to as n z = 0 is the reference layer); when the reference layer 1 is located at the gradient center (z = 0), Figure 4 As shown in Figure a, the interference phase and The generation process is as follows Figure 4 As shown in Figures b and c. Among them, Figure 4 The center position of the ac reference layer is at the center of the gradient; the position of the de reference layer deviates from the center of the gradient.

[0076] When k is applied z When encoding the gradient, along the z-axis, the gradient will be in the segment interval Δz mUnder the action of

[0077]

[0078] When k is applied m When encoding the gradient, along the z-axis, the gradient will be in each segment of the FOV z An additional set of linear interference phases is generated within the range

[0079]

[0080] Specifically, the interference phase correction of the embodiment of the present application may include off-center phase correction, Correction and The three steps are carried out in sequence as follows:

[0081] (1) Off-center phase correction:

[0082] In the embodiment of the present application, when the actual position of the reference layer corresponding to the excitation segment is not at the center of the physical z-axis gradient during multi-segment simultaneous excitation imaging, the relative position of the reference layer and the center of the physical z-axis gradient is calculated according to the actual position, and the relative position is corrected in k z and k m The off-center phase error caused by the gradient.

[0083] It is understandable that the embodiment of the present application may adopt an off-center phase correction. Specifically, Figure 4 As shown in Figure d, when the reference layer position of the excitation segment is not at the center of the z-axis encoding gradient, k z and k m The coding gradient will produce an additional phase error due to the off-center distance, such as Figure 4 As shown in Figures e and f, it is called off-center phase:

[0084]

[0085] Among them, d off_iso is the relative position of the reference layer away from the center of the z-axis encoding gradient. In the process of k-space data preprocessing, the corresponding k z and k m Encoded k-space data removal

[0086] (2) Correction:

[0087] In the embodiment of the present application, for k z Gradient-induced inter-segment interference phase Phase compensation is applied to the RF pulses in multiple simultaneous excitation sequences to eliminate Or through the preset reconstruction algorithm, the four-dimensional k-space signal is reconstructed along k m The image is transformed by performing a one-dimensional inverse Fourier transform and correcting the linear phase after the Fourier transform, or performing a cyclic shift in the image domain.

[0088] It is understandable that according to the above The calculation formula can be used to calculate the value of each k z Inter-segment interference phase corresponding to the code The phase is frequency-band specific. Therefore, the embodiment of the present application can correct the For example, in the embodiment of the present application, a RF pulse modulation compensation can be added to the excitation signal. It can also be removed during image reconstruction The details are as follows:

[0089] As a possible implementation method, the embodiment of the present application can adopt a method for applying phase compensation to the radio frequency pulses in the multi-segment simultaneous excitation sequence, based on the radio frequency pulse phase modulation to remove

[0090] Specifically, by z During excitation, the waveform of a specific frequency band of the multi-band RF pulse is subtracted The collected signal does not contain interference.

[0091] For the gradient echo EPI sequence, the SMSlab RF pulse with phase modulation is:

[0092]

[0093] Among them, RF(t) is a single-band pulse based on For nth m The center frequency of the band.

[0094] For the spin echo EPI sequence, the acquisition of imaging echoes requires two RF pulses: excitation and refocusing:

[0095]

[0096]

[0097] Among them, RF ex (t)-based single-band excitation pulse, RF echo_1 (t) is the first refocusing pulse.

[0098] For diffusion imaging based on spin echo EPI sequences, a second refocusing pulse is also required to acquire a two-dimensional navigator echo for phase correction between different kz excitations:

[0099]

[0100] Among them, RF echo_2 (t) is the second basic single-band refocusing pulse.

[0101] As another possible implementation method, the embodiment of the present application can adopt a method of removing The method is to use a preset reconstruction algorithm to reconstruct the four-dimensional k-space signal along the k m The image is transformed by performing a one-dimensional inverse Fourier transform and correcting the linear phase after the Fourier transform, or performing a cyclic shift in the image domain.

[0102] It can be understood that for both non-diffusion-weighted and diffusion-weighted data, we can first z Encode and reconstruct the image in the xym domain, and then for each k z Encoded in frequency band n m Phase removal This process is essentially equivalent to reconstructing thin-layer images of all segments and then The thin layer images within the affected frequency band are cyclically shifted in the layer direction.

[0103] Specifically, if Figure 5 As shown, Figure 5 Shown Image results before and after correction: In the present embodiment, when Δz m / (N z When Δz) is an integer, k z The interference phase generated by the coding gradient is exactly an integer multiple of 2π, so there is no need to Correction. When Δz m / (N z · When Δz) is not an integer, if no Correction, the interference phase causes segment 1' to produce an image shift along the layer direction, after After correction, correct reconstruction can be achieved.

[0104] (3) Correction:

[0105] In the embodiment of the present application, for k m Phase of linear interference within a segment caused by gradient When it belongs to the non-diffusion weighted data type, the four-dimensional k-space signal along k z Dimensions are subjected to one-dimensional inverse Fourier transform, and each km The coded signals are corrected from different layer positions Or when it belongs to the diffusion weighted data type, it is corrected sequentially or simultaneously by a preset reconstruction algorithm and different k z Phase differences between excitations due to motion.

[0106] Among them, in the embodiment of this application The correction is performed during data preprocessing, and the preset reconstruction algorithm may include a reconstruction algorithm based on k-space, based on image domain, and based on a hybrid space of k-space and image domain.

[0107] Specifically, for non-diffusion-weighted data, we can directly calculate the k z Direction is removed after one-dimensional inverse Fourier transform For diffusion-weighted data, since each k z The phase inconsistency caused by the inconsistent motion between excitations cannot be directly z To perform a one-dimensional inverse Fourier transform in the direction, an additional phase calculation between each excitation is required, that is, According to different reconstruction algorithms, these two corrections can be performed sequentially or simultaneously.

[0108] As a possible implementation method, the preset reconstruction algorithm is used to correct the and Including: Using k-space-based image reconstruction algorithm, correcting and

[0109] Specifically, first correct Recalibration The correction steps are as follows: First, the collected diffusion-weighted data are preliminarily reconstructed in xymk z domain using navigation echo information to remove different k z Phase differences between excitations caused by motion At this time, we can follow k z Do a one-dimensional Fourier transform in the direction; transform to k x -k y -k m After the -z domain, the interfering phase at each z position is removed Next, the above process is reversed, that is, in xymk z Domain Add it back and then transform it to k x -k y -k m -k z domain, will be Impact of km The data of the actual sampling position in the code is extracted and replaced by the original Corrected sampling points are then used for subsequent reconstruction.

[0110] As another possible implementation method, the following methods are corrected sequentially or simultaneously by a preset reconstruction algorithm: and Including: reconstruction of diffusion-weighted images based on a hybrid space reconstruction algorithm of k-space and image domain to simultaneously correct and

[0111] Specifically, when a diffusion-weighted image is reconstructed using a reconstruction algorithm based on a hybrid space of k-space and image domain, the embodiment of the present application can simultaneously correct the above two phases and establish the following signal model, where only in k-space y -k m An example of downsampling by dimension:

[0112]

[0113] Where I represents the image to be reconstructed, C represents the coil sensitivity information, and F y_m represents the Fourier transform in the dimension other than the intra-segment coding dimension and with downsampling, M represents the downsampling trajectory, and s represents the signal in the mixed space, which is xk in the example case y -k m The reconstruction process is to solve the inverse problem of the model, which can be solved using optimization algorithms such as the least squares method.

[0114] It should be noted that in step (2) During calibration, if you choose to remove In step (3) The correction needs to be considered at the same time The impact of As another to be processed.

[0115] It is understandable that if Figure 6 As shown, Figure 6 Shown Image results before and after correction: In the present embodiment, if no correction is performed Correction, the interference phase causes a certain degree of image aliasing, as shown in the area indicated by the arrow; After correction, correct reconstruction can be achieved.

[0116] In the embodiment of the present application, the embodiment of the present application can reconstruct an image based on the corrected four-dimensional k-space signal. Reconstruction algorithms based on k-space (such as GRAPPA and its extended algorithms), image domain (such as SENSE and its extended algorithms), and hybrid space based on k-space and image domain can all be applied to the proposed four-dimensional k-space blipped-SMSlab sampling mode. Correct the above k z and k m After the interference phase generated by the encoding process, we can first z The image is reconstructed from the stimulated data. At this time, for non-diffusion weighted data, it is possible to directly z The final image is obtained by performing a one-dimensional inverse Fourier transform in the dimensional space. For diffusion-weighted data, the phase information caused by the motion recorded by the navigation echo is used to obtain the final image for different k z The image to be excited is subjected to motion phase correction. When multiple excitations are used for intra-layer coding, motion phase correction between each excitation is also required. Then, the k z The final image is obtained by performing one-dimensional inverse Fourier transform.

[0117] In the embodiment of the present application, the SMSlab image g factor calculation is performed using the blipped-CAIPI and non-CAIPI sampling modes to reconstruct the SMSlab image, and the SMSlab blipped-CAIPI sampling and the existing non-CAIPI sampling results are compared. Figure 7 As shown in Figure a, two different levels are shown. The results show that the g factor of CAIPI sampling is generally lower than that of non-CAIPI sampling. This means that the g-factor-related signal-to-noise ratio loss is lower in the CAIPI sampling mode, which can explain why the SNR of CAIPI sampling is higher than that of non-CAIPI sampling (such as Figure 7 The reconstructed b=0 image is enlarged and displayed for the red and blue frame areas selected in layer A and layer B, respectively. Figure 7 As shown in Figure c, it can also be directly seen that the signal-to-noise ratio of CAIPI sampling imaging is significantly higher than that of non-CAIPI sampling.

[0118] In the present application example, blipped-SMSlab and traditional two-dimensional multi-layer simultaneous excitation imaging are compared, wherein the results of blipped-SMSlab imaging and traditional two-dimensional blipped-CAIPI accelerated multi-layer simultaneous excitation technology (2D blipped-SMS) are as follows: Figure 8 As shown. Both use blipped-CAIPI sampling and the scanning time is the same. It can be seen that the blipped-SMSlab technology of the embodiment of the present application shows obvious signal-to-noise ratio advantages and the ability to depict the direction of smoother nerve fiber bundles.

[0119] In summary, the embodiments of the present application can use the parallel imaging gradient control aliasing function in multi-segment simultaneous excitation imaging to solve the phase interference problem caused by intra-segment coding and inter-segment coding sharing the same physical z-axis, decouple the two coding dimensions into two independent dimensions, so that the blipped-CAIPI acceleration technology can be applied to multi-segment simultaneous excitation imaging, improve scanning efficiency and image signal-to-noise ratio, and improve image quality; it can be applicable to multiple three-dimensional thick segments simultaneously excited, any contrast, any form of EPI (including gradient echo EPI, spin echo EPI and other possible forms of EPI) imaging signal acquisition and image reconstruction, and has a wide range of applications; and the embodiments of the present application also carry out special processing for the special properties of diffusion imaging: by collecting additional navigation echoes or using other forms to obtain navigation echo information, and performing phase correction between different excitations caused by physiological movement in reconstruction; it can also include the use of motion compensated (1st order or 2nd order at the same time) diffusion coding gradient to eliminate the influence of movement between different excitations.

[0120] Next, a magnetic resonance imaging device based on multi-segment simultaneous excitation according to an embodiment of the present application is described with reference to the accompanying drawings.

[0121] Fig. 9 It is a block diagram of a magnetic resonance imaging device based on multi-segment simultaneous excitation according to an embodiment of the present application.

[0122] like Fig. 9 As shown, the magnetic resonance imaging device 10 based on multi-segment simultaneous excitation includes: an acquisition module 100 , a modeling module 200 and a reconstruction module 300 .

[0123] Among them, the acquisition module 100 is used to obtain a sequence diagram of the target to be imaged when multiple segments are simultaneously excited for imaging; the modeling module 200 is used to establish a four-dimensional k-space signal model, divide the gradient coding in the layer direction corresponding to the sequence diagram into intra-segment coding and inter-segment coding, and form the acquired k-space data into a four-dimensional k-space signal; the reconstruction module 300 is used to correct the interference phase of the intra-segment coding and / or inter-segment coding, and perform image reconstruction based on the corrected coding to generate the magnetic resonance imaging result of the target to be imaged.

[0124] In the embodiment of the present application, the method is applicable to the planar echo imaging of multiple three-dimensional thick segments excited simultaneously in any contrast and any form, and the acquisition module 100 is further used to: apply a kz coding gradient along the layer direction for intra-segment coding, and the kz gradient area size is:

[0125] A z =n kz ·2π / (γ·FOV z ),

[0126] Among them, n kzis the kz encoding number, γ is the gyromagnetic ratio constant, FOV z is the thickness of each segment; and during the EPI readout process, a km gradient with alternating polarity is applied along the layer direction for inter-segment encoding, and the km gradient area size is:

[0127] A blip =2π / (γ·Δz m ·R m ),

[0128] Where γ is the gyromagnetic ratio constant, Δz m is the center distance of adjacent segments excited simultaneously, R m is the number of segments excited simultaneously; and / or when used for diffusion weighted imaging, during each kz encoding process, the navigation echo is collected to obtain the phase information of each kz excitation.

[0129] In the embodiment of the present application, the four-dimensional k-space signal model pre-established by the modeling module 200 is:

[0130]

[0131] Among them, n m ∈[0,R m -1] is the sequence number of the image domain in the inter-segment coding direction, n km ∈[0,R m -1] is the sequence number of the four-dimensional k-space in the inter-segment coding direction, n z ∈[0,N z -1] is the sequence number of the image domain in the encoding direction within the segment, n kz ∈[-N z / 2,N z / 2-1] is the serial number of the encoding direction of the four-dimensional k-space within the segment, s(n km ,n kz ) is the nth dimension along the inter-segment coding dimension in the four-dimensional k-space km codes, along the intra-segment coding dimension nth kz The coded signal, μ(n m ,n z ) is the nth simultaneously excited m The nth paragraph z The signal of the layer, k x , k y , k m and k z Represents the four dimensions of the four-dimensional k-space, where k m and k z The tables represent the intra-segment coding dimension and the inter-segment coding dimension respectively, and x, y, m and z represent the four dimensions of the image domain; k z The phase of inter-segment interference caused by the gradient, k m Phase of intra-segment interference caused by gradient.

[0132] In the embodiment of the present application, the reconstruction module 300 is further used to: z Gradient-induced inter-segment interference phase Phase compensation is applied to the RF pulses in multiple simultaneous excitation sequences to eliminate Or through the preset reconstruction algorithm, the four-dimensional k-space signal is reconstructed along k m The one-dimensional inverse Fourier transform is performed in the image domain, and the linear phase is corrected after the Fourier transform, or a cyclic shift is performed in the image domain; for the linear interference phase within the segment caused by the km gradient When it belongs to the non-diffusion weighted data type, the four-dimensional k-space signal along k z Dimensional one-dimensional inverse Fourier transform, for each k m The encoded signals are corrected along the z direction Or when it belongs to the diffusion weighted data type, it is corrected sequentially or simultaneously by a preset reconstruction algorithm and different k z Phase difference caused by motion between excitations; when applied to diffusion-weighted imaging, for different k z The phase difference caused by inconsistent motion between excitations is removed based on the navigation echo; when the actual position of the reference layer corresponding to the excitation segment is not at the center position of the encoding gradient corresponding to the physical z-axis during simultaneous multi-segment excitation imaging, the relative position of the reference layer and the physical z-axis is calculated based on the actual position, and the off-center phase error caused by the relative position and the gradient is corrected.

[0133] It should be noted that the above explanation of the embodiment of the magnetic resonance imaging method based on multi-segment simultaneous excitation is also applicable to the magnetic resonance imaging device based on multi-segment simultaneous excitation of this embodiment, which will not be described in detail here.

[0134] According to the magnetic resonance imaging device based on multi-segment simultaneous excitation proposed in the embodiment of the present application, the parallel imaging gradient control aliasing function can be used in multi-segment simultaneous excitation imaging to solve the phase interference problem caused by intra-segment coding and inter-segment coding sharing the same physical z-axis, and the two coding dimensions are decoupled into two independent dimensions, so that the blipped-CAIPI acceleration technology can be applied to multi-segment simultaneous excitation imaging, thereby improving scanning efficiency and image signal-to-noise ratio, and improving image quality; it can be applicable to imaging signal acquisition and image reconstruction of multiple three-dimensional thick segments simultaneously excited, with any contrast and any form of EPI (including gradient echo EPI, spin echo EPI and other possible forms of EPI), and has a wide range of applications.

[0135] Fig.10A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0136] A memory 1001 , a processor 1002 , and a computer program stored in the memory 1001 and executable on the processor 1002 .

[0137] When the processor 1002 executes the program, the magnetic resonance imaging method based on multi-segment simultaneous excitation provided in the above embodiment is implemented.

[0138] Furthermore, the electronic device further comprises:

[0139] The communication interface 1003 is used for communication between the memory 1001 and the processor 1002 .

[0140] The memory 1001 is used to store computer programs that can be executed on the processor 1002 .

[0141] The memory 1001 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0142] If the memory 1001, the processor 1002 and the communication interface 1003 are implemented independently, the communication interface 1003, the memory 1001 and the processor 1002 can be connected to each other through a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.10 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0143] Optionally, in a specific implementation, if the memory 1001, the processor 1002 and the communication interface 1003 are integrated on a chip, the memory 1001, the processor 1002 and the communication interface 1003 can communicate with each other through an internal interface.

[0144] The processor 1002 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0145] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the magnetic resonance imaging method based on multi-segment simultaneous excitation as described above.

[0146] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0147] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0148] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0149] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0150] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

Claims

1. A magnetic resonance imaging method based on multi-segment simultaneous excitation, characterized in that: The following steps are involved: Step S101: using a multi-segment simultaneous excitation imaging sequence with a parallel imaging gradient control aliasing function to perform data acquisition to obtain multi-channel k-space data; Step S102: establishing a four-dimensional k-space signal model, dividing the gradient coding in the layer direction corresponding to the sequence diagram into intra-segment coding and inter-segment coding, and forming a four-dimensional k-space signal from the acquired k-space data; Step S103: correcting the interference phase of the four-dimensional k-space signal generated by the intra-segment coding and the inter-segment coding sharing the same physical z-axis, and performing image reconstruction based on the corrected four-dimensional k-space signal to generate a magnetic resonance imaging result of the target to be imaged; The step S103 corrects the interference phase of the four-dimensional k-space signal caused by the intra-segment coding and the inter-segment coding sharing the same physical z-axis, including: For k z Gradient-induced inter-segment interference phase Phase compensation is applied to the RF pulses in multiple simultaneous excitation sequences to eliminate Or through the preset reconstruction algorithm, the four-dimensional k-space signal is reconstructed along k m Perform one-dimensional inverse Fourier transform on the image dimension and correct the linear phase after Fourier transform, or perform cyclic shift in the image domain; For k m Phase of linear interference within a segment caused by gradient When it belongs to the non-diffusion weighted data type, the four-dimensional k-space signal along k z Dimensional one-dimensional inverse Fourier transform, for each k m The coded signals are corrected from different layer positions Or when it belongs to the diffusion weighted data type, it is corrected sequentially or simultaneously by a preset reconstruction algorithm and different k z Phase differences between excitations due to motion; When applied to diffusion-weighted imaging, for different k z Phase differences caused by inconsistent motion between excitations are removed based on the navigation echo; When the actual position of the reference layer corresponding to the excitation segment during the multi-segment simultaneous excitation imaging is not at the center of the physical z-axis gradient, the relative position of the reference layer and the center of the physical z-axis gradient is calculated according to the actual position, and the relative position is corrected in k z and k m The off-center phase error caused by the gradient.

2. The method according to claim 1, characterized in that The method is applicable to planar echo imaging with multiple three-dimensional thick segments excited simultaneously in any contrast and any form, and the step S101 specifically includes: The kz coding gradient is applied along the layer direction for intra-segment coding, and the kz gradient area size is: A z =n kz ·2π / (γ·FOV z ), Among them, n kz k z Coding number, γ is the gyromagnetic ratio constant, FOV z is the thickness of each segment; and During the EPI readout process, a k-pole with alternating polarity is applied along the layer direction. m The gradient is used for inter-segment coding, the k m The gradient area size is: A blip =2π / (γ·Δz m ·R m ), Where γ is the gyromagnetic ratio constant, Δz m is the center distance of adjacent segments excited simultaneously, R m is the number of segments that are excited simultaneously; and / or When used for diffusion-weighted imaging, at each k z During the encoding process, the navigation echo is collected to obtain each k z The phase information of the excitation.

3. The method according to claim 1, characterized in that The four-dimensional k-space signal model pre-established in step S102 is: Among them, n m ∈[0,R m -1] is the sequence number of the image domain in the inter-segment coding direction, n km ∈[0,R m -1] is the serial number of the four-dimensional k-space in the inter-segment encoding direction, n z ∈[0,N z -1] is the sequence number of the image domain in the encoding direction within the segment, n kz ∈[-N z / 2,N z / 2-1] is the serial number of the encoding direction of the four-dimensional k-space within the segment, s(n km ,n kz ) is the nth dimension along the inter-segment coding dimension in the four-dimensional k-space km codes, along the intra-segment coding dimension nth kz The coded signal, μ(n m ,n z ) is the nth m The nth paragraph z The signal of the layer, k x , k y , k m and k z represents the four dimensions of the four-dimensional k-space, where k m and k z denote the inter-segment coding dimension and the intra-segment coding dimension respectively, and x, y, m and z denote the four dimensions of the image domain; k z The phase of inter-segment interference caused by the gradient, k m Phase of intra-segment interference caused by gradient.

4. A magnetic resonance imaging device based on multi-segment simultaneous excitation, characterized in that: include: An acquisition module is used to acquire data through a multi-segment simultaneous excitation imaging sequence with a parallel imaging gradient control aliasing function, thereby obtaining multi-channel k-space data; A modeling module is used to establish a four-dimensional k-space signal model, divide the gradient coding of the layer direction corresponding to the sequence diagram into intra-segment coding and inter-segment coding, and form the collected k-space data into a four-dimensional k-space signal; A reconstruction module, used for correcting the interference phase of the four-dimensional k-space signal caused by the intra-segment coding and the inter-segment coding sharing the same physical z-axis, and performing image reconstruction based on the corrected four-dimensional k-space signal to generate a magnetic resonance imaging result of the target to be imaged; The reconstruction module is further used for: For k z Gradient-induced inter-segment interference phase Phase compensation is applied to the RF pulses in multiple simultaneous excitation sequences to eliminate Or through the preset reconstruction algorithm, the four-dimensional k-space signal is reconstructed along k m Perform one-dimensional inverse Fourier transform on the image dimension and correct the linear phase after Fourier transform, or perform cyclic shift in the image domain; For k m Phase of linear interference within a segment caused by gradient When it belongs to the non-diffusion weighted data type, the four-dimensional k-space signal along k z Dimensional one-dimensional inverse Fourier transform, for each k m The coded signals are corrected from different layer positions Or when it belongs to the diffusion weighted data type, it is corrected sequentially or simultaneously by a preset reconstruction algorithm and different k z Phase differences between excitations due to motion; When applied to diffusion-weighted imaging, for different k z Phase differences caused by inconsistent motion between excitations are removed based on the navigation echo; When the actual position of the reference layer corresponding to the excitation segment during the multi-segment simultaneous excitation imaging is not at the center of the physical z-axis gradient, the relative position of the reference layer and the center of the physical z-axis gradient is calculated according to the actual position, and the relative position is corrected in k z and k m The off-center phase error caused by the gradient.

5. The device according to claim 4, characterized in that The device is suitable for planar echo imaging with multiple three-dimensional thick sections excited simultaneously in any contrast and any form, and the acquisition module is further used for: The kz coding gradient is applied along the layer direction for intra-segment coding, and the kz gradient area size is: A z =n kz ·2π / (γ·FOV z ), Among them, n kz is the kz encoding number, γ is the gyromagnetic ratio constant, FOV z is the thickness of each segment; and During the EPI readout process, a km gradient with alternating polarity is applied along the slice direction for inter-segment coding. The km gradient area size is: A blip =2π / (γ*Δz m ·R m ), Where γ is the gyromagnetic ratio constant, Δz m is the center distance of adjacent segments excited simultaneously, R m is the number of segments that are excited simultaneously; and / or When used for diffusion-weighted imaging, during each kz encoding process, the navigation echo is collected to obtain the phase information of each kz excitation.

6. The device according to claim 4, characterized in that The four-dimensional k-space signal model pre-established by the modeling module is: Among them, n m ∈[0,R m -1] is the sequence number of the image domain in the inter-segment coding direction, n km ∈[0,R m -1] is the serial number of the four-dimensional k-space in the inter-segment encoding direction, n z ∈[0,N z -1] is the sequence number of the image domain in the encoding direction within the segment, n kz ∈[-N z / 2,N z / 2-1] is the serial number of the encoding direction of the four-dimensional k-space within the segment, s(n km ,n kz ) is the nth dimension along the inter-segment coding dimension in the four-dimensional k-space km codes, along the intra-segment coding dimension nth kz The coded signal, v(n m ,n z ) is the nth m The nth paragraph z The signal of the layer, k x , k y , k m and k z represents the four dimensions of the four-dimensional k-space, where k m and k z denote the intra-segment coding dimension and the inter-segment coding dimension respectively, and x, y, m and z denote the four dimensions of the image domain; k z The phase of inter-segment interference caused by the gradient, k m Phase of intra-segment interference caused by gradient.

7. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the magnetic resonance imaging method based on multi-segment simultaneous excitation as described in any one of claims 1 to 3.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the magnetic resonance imaging method based on multi-segment simultaneous excitation as described in any one of claims 1 to 3.

Images