WO2022236823A1

WO2022236823A1 - Reconstruction method for wrap-field-of-view magnetic resonance image, computer device, and storage medium

Info

Publication number: WO2022236823A1
Application number: PCT/CN2021/093909
Authority: WO
Inventors: 梁栋; 贾森; 丘志浪; 张磊; 王海峰; 刘新; 郑海荣
Original assignee: 中国科学院深圳先进技术研究院
Priority date: 2021-05-13
Filing date: 2021-05-14
Publication date: 2022-11-17
Also published as: CN113298901A; CN113298901B

Abstract

A reconstruction method for a wrap-field-of-view magnetic resonance image, a computer device, and a storage medium. The method comprises: acquiring wrap-field-of-view undersampling data of a target object under excitation by a first pulse sequence (S1); acquiring full-field-of-view self-calibration sampling data of the target object under excitation by a second pulse sequence (S2); calculating a full-field-of-view coil sensitivity map on the basis of the full-field-of-view self-calibration data (S3); and performing image reconstruction according to the wrap-field-of-view undersampling data and the full-field-of-view coil sensitivity map (S4), to obtain a full-field-of-view magnetic resonance image. According to the reconstruction method, image reconstruction is performed on wrap-field-of-view undersampling data by means of full-field-of-view sampling data modeling to obtain a full-field-of-view magnetic resonance image, thereby avoiding the phenomenon of a reconstruction aliasing artifact in a wrap-field-of-view scanning scene and improving the quality of a reconstructed image.

Description

卷褶视野磁共振图像的重建方法、计算机设备及存储介质Reconstruction method, computer equipment and storage medium of magnetic resonance image in folded field of view

技术领域technical field

本发明涉及磁共振成像技术领域，尤其涉及一种卷褶视野磁共振图像的重建方法、计算机设备及存储介质。The invention relates to the technical field of magnetic resonance imaging, in particular to a method for reconstructing a magnetic resonance image of a convoluted field of view, a computer device and a storage medium.

背景技术Background technique

磁共振成像(MRI，Magnetic Resonance Imaging)技术由于其无辐射、分辨率高等优点被广泛的应用于临床医学与医学研究。根据奈奎斯特采样定理，磁共振成像在相位编码方向的成像视野(field of view，FOV)或覆盖范围应大于被扫描对象的实际大小，然而，增大成像视野导致扫描相位编码数增多，进而增加扫描和重建时间。因此，在某些场景下，相位编码方向的成像视野会被人为设置成小于物体在该方向的尺寸，该场景称之为卷褶视野扫描场景。例如，在高分辨率三维成像中，人为地减小相位编码方向的成像视野，缩短扫描时间，才能在临床可接受的时间内获得诊断图像。但是，在卷褶视野的扫描场景下，传统的全局自动校准部分并行采集技术(generalized auto-calibrating partially parallel acquisitions，GRAPPA)和迭代自相一致并行成像技术(iterative self-consistent Parallel Imaging Reconstruction，SPIRiT)等重建方法只能得到卷褶视野的磁共振图像且会存在伪影，无法用于诊断。Magnetic Resonance Imaging (MRI, Magnetic Resonance Imaging) technology is widely used in clinical medicine and medical research due to its advantages of no radiation and high resolution. According to the Nyquist sampling theorem, the imaging field of view (FOV) or coverage area of magnetic resonance imaging in the phase encoding direction should be larger than the actual size of the scanned object. This in turn increases scan and rebuild times. Therefore, in some scenarios, the imaging field of view in the phase encoding direction is artificially set to be smaller than the size of the object in this direction, and this scene is called a convolution field of view scanning scene. For example, in high-resolution 3D imaging, the imaging field of view in the phase-encoding direction is artificially reduced, and the scan time is shortened so that diagnostic images can be obtained within a clinically acceptable time. However, in the scanning scene of the convoluted field of view, the traditional generalized auto-calibrating partially parallel acquisitions (GRAPPA) and iterative self-consistent Parallel Imaging Reconstruction (SPIRiT) Such reconstruction methods can only obtain the magnetic resonance images of the folded field of view and there will be artifacts, which cannot be used for diagnosis.

发明内容Contents of the invention

为了解决现有技术的不足，本发明提供一种卷褶视野磁共振图像的重建方法、计算机设备及存储介质，能够得到在卷褶视野扫描场景中的全视野磁共振图像且能够去除重建混叠伪影，提升重建图像的质量。In order to solve the deficiencies in the prior art, the present invention provides a reconstruction method, computer equipment and storage medium of a convoluted field of view magnetic resonance image, which can obtain a full-field magnetic resonance image in a convoluted field of view scanning scene and can remove reconstruction aliasing Artifacts to improve the quality of the reconstructed image.

本发明提出的具体技术方案为：提供一种卷褶视野磁共振图像的重建方法，所述重建方法包括：The specific technical solution proposed by the present invention is to provide a method for reconstructing a magnetic resonance image of a convoluted field of view, the reconstruction method comprising:

获取目标对象在第一脉冲序列激发下的卷褶视野欠采样数据；Obtain undersampling data of the target object under the excitation of the first pulse sequence;

获取目标对象在第二脉冲序列激发下的全视野自校准采样数据；Acquiring the full field of view self-calibration sampling data of the target object under the excitation of the second pulse sequence;

基于所述全视野自校准采样数据计算全视野线圈敏感度图；calculating a full-field coil sensitivity map based on the full-field self-calibration sampling data;

根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像。Image reconstruction is performed according to the undersampled data of the convoluted field of view and the sensitivity map of the full field of view to obtain a full field of view magnetic resonance image.

进一步地，若所述卷褶视野欠采样数据为采用笛卡尔采样轨迹模式获得的欠采样数据，所述第一脉冲序列和所述第二脉冲序列相同。Further, if the convoluted field of view undersampled data is undersampled data obtained by using a Cartesian sampling trajectory mode, the first pulse sequence is the same as the second pulse sequence.

进一步地，所述根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得磁共振图像，包括：Further, the image reconstruction is performed according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, and the magnetic resonance image is obtained, including:

将所述全视野线圈敏感度图分解成第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图；Decomposing the full field of view coil sensitivity map into a first convoluted field of view coil sensitivity map and a second convoluted field of view coil sensitivity map;

根据所述卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图建立优化模型；Establishing an optimization model according to the undersampled data of the pleat field of view, the sensitivity map of the first pleat field of view coil, and the sensitivity map of the second pleat field of view coil;

求解所述优化模型的最小值，获得两个卷褶视野磁共振图像；Solving the minimum value of the optimization model to obtain two magnetic resonance images of the convoluted field of view;

将所述两个卷褶视野磁共振图像进行拼接获得全视野磁共振图像。The two folded field of view magnetic resonance images are spliced to obtain a full field of view magnetic resonance image.

进一步地，若所述卷褶视野欠采样数据为采用波浪可控混叠编码采样轨迹模式获得的欠采样数据，所述第一脉冲序列是由所述第二脉冲序列增加正弦梯度场获得，在根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像之前，所述重建方法还包括：Further, if the undersampled data of the convoluted field of view is the undersampled data obtained by adopting the wave controllable aliasing encoding sampling trajectory mode, the first pulse sequence is obtained by adding a sinusoidal gradient field to the second pulse sequence. Perform image reconstruction according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, and before obtaining the full field of view magnetic resonance image, the reconstruction method further includes:

根据目标对象的全视野二维全采样数据获得全视野点扩散函数；Obtain the full-view point spread function according to the full-view two-dimensional full-sampling data of the target object;

相应的，根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像具体为：Correspondingly, image reconstruction is performed according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, and the full field of view magnetic resonance image is specifically obtained as follows:

根据所述卷褶视野欠采样数据、全视野线圈敏感度图、全视野点扩散函数进行图像重建，获得全视野磁共振图像。Image reconstruction is performed according to the undersampled data of the convoluted field of view, the full field of view coil sensitivity map, and the full field of view point spread function, and a full field of view magnetic resonance image is obtained.

进一步地，所述根据目标对象的全视野二维全采样数据获得全视野点扩散函数，包括：Further, the obtaining the full-view point spread function according to the full-view two-dimensional full sampling data of the target object includes:

获取目标对象在第三脉冲序列激发下的第一全视野二维全采样数据；Acquiring the first full field of view two-dimensional full sampling data of the target object under the excitation of the third pulse sequence;

获取目标对象在第四脉冲序列激发下的第二全视野二维全采样数据，所述第四脉冲序列是由所述第三脉冲序列增加正弦梯度场获得；Acquiring the second full-field two-dimensional full sampling data of the target object excited by the fourth pulse sequence, the fourth pulse sequence is obtained by adding a sinusoidal gradient field to the third pulse sequence;

将所述第二全视野二维全采样数据除以所述第一全视野二维全采样数据得到全视野点扩散函数。dividing the second full-view two-dimensional full-sampling data by the first full-view two-dimensional full-sampling data to obtain a full-view point spread function.

进一步地，所述将所述第二全视野二维全采样数据除以所述第一全视野二维全采样数据得到全视野点扩散函数，包括：Further, the dividing the second full-view two-dimensional full-sampling data by the first full-view two-dimensional full-sampling data to obtain a full-view point spread function includes:

将所述第二全视野二维全采样数据除以所述第一全视野二维全采样数据得到初始点扩散函数；dividing the second full-field two-dimensional full-sampling data by the first full-field two-dimensional full-sampling data to obtain an initial point spread function;

将所述初始点扩散函数在K空间沿着频率编码方向进行线性拟合获得全视野点扩散函数。The initial point spread function is linearly fitted along the frequency encoding direction in K space to obtain a point spread function of the whole field of view.

进一步地，所述根据所述卷褶视野欠采样数据、全视野线圈敏感度图、全视野点扩散函数进行图像重建，获得全视野磁共振图像，包括：Further, the image reconstruction is performed according to the undersampled data of the convoluted field of view, the full field of view coil sensitivity map, and the full field of view point spread function, and the full field of view magnetic resonance image is obtained, including:

将所述全视野点扩散函数分解成第一卷褶视野点扩散函数、第二卷褶视野点扩散函数；Decomposing the full view point spread function into a first convoluted view point spread function and a second convoluted view point spread function;

根据所述卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图、第一卷褶视野点扩散函数、第二卷褶视野点扩散函数建立优化模型；An optimization model is established according to the undersampled data of the pleat field of view, the coil sensitivity map of the first pleat field of view, the coil sensitivity map of the second pleat field of view, the point spread function of the first pleat field of view, and the point spread function of the second pleat field of view ;

进一步地，所述基于所述全视野自校准采样数据计算全视野线圈敏感度图，包括：Further, the calculation of the full-field coil sensitivity map based on the full-field self-calibration sampling data includes:

获取所述全视野自校准采样数据的特征值；Obtaining the eigenvalues of the full field of view self-calibration sampling data;

求解所述特征值中最大的特征值对应的特征向量并将所述特征向量作为全视野线圈敏感度图。Solving the eigenvector corresponding to the largest eigenvalue among the eigenvalues and using the eigenvector as a sensitivity map of the full field of view coil.

本发明还提供了一种计算机设备，包括存储器、处理器及存储在存储器上的计算机程序，所述处理器执行所述计算机程序以实现如上任一项所述的重建方法。The present invention also provides a computer device, including a memory, a processor and a computer program stored on the memory, the processor executes the computer program to implement the reconstruction method described in any one of the above.

本发明还提供了一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机指令，所述计算机指令被处理器执行时实现如上任一项所述的重建方法。The present invention also provides a computer-readable storage medium, where computer instructions are stored on the computer-readable storage medium, and when the computer instructions are executed by a processor, the reconstruction method described in any one of the above items is implemented.

本发明提供的卷褶视野磁共振图像的重建方法根据目标对象的全视野自校准采样数据获得全视野线圈敏感度图，再根据卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，即利用全视野采样数据建模来对卷褶视野欠采样数据进行图像重建，以获得全视野磁共振图像，从而避免了在卷褶视野扫描场景中的重建混叠伪影现象，提升重建图像的质量。The reconstruction method of the magnetic resonance image of the convoluted field of view provided by the present invention obtains the full field of view coil sensitivity map according to the full field of view self-calibration sampling data of the target object, and then performs image reconstruction according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, That is to use the full-field sampling data modeling to reconstruct the under-sampled data of the convoluted field of view to obtain a full-field magnetic resonance image, thereby avoiding the reconstruction aliasing artifacts in the convoluted field of view scanning scene and improving the quality of the reconstructed image. quality.

附图说明Description of drawings

下面结合附图，通过对本发明的具体实施方式详细描述，将使本发明的技术方案及其它有益效果显而易见。The technical solutions and other beneficial effects of the present invention will be apparent through the detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings.

图1为本申请实施例一中卷褶视野磁共振图像的重建方法的流程示意图；FIG. 1 is a schematic flowchart of a method for reconstructing a magnetic resonance image of a convoluted field of view in Embodiment 1 of the present application;

图2为本申请实施例一中第一脉冲序列、第二脉冲序列为二维GRE序列的示意图；2 is a schematic diagram of the first pulse sequence and the second pulse sequence being two-dimensional GRE sequences in Embodiment 1 of the present application;

图3为本申请实施例一中第一脉冲序列、第二脉冲序列为三维GRE序列的示意图；3 is a schematic diagram of the first pulse sequence and the second pulse sequence being a three-dimensional GRE sequence in Embodiment 1 of the present application;

图4为本申请实施例一中根据规则欠采样的方法获得的卷褶视野欠采样数据在二维K空间中的示意图；Fig. 4 is a schematic diagram of the undersampled data of the convoluted field of view obtained according to the method of regular undersampling in the first embodiment of the present application in the two-dimensional K space;

图5为本申请实施例一中根据规则欠采样的方法获得的卷褶视野欠采样数据在三维K空间中的示意图；Fig. 5 is a schematic diagram of the undersampled data of the convoluted field of view obtained according to the method of regular undersampling in the first embodiment of the present application in the three-dimensional K space;

图6为本申请实施例一中对K空间中心进行全采样获得的全视野自校准采样数据在二维K空间中的示意图；FIG. 6 is a schematic diagram of the full-view self-calibration sampling data obtained by performing full sampling on the K-space center in the two-dimensional K-space in Embodiment 1 of the present application;

图7为本申请实施例一中对K空间中心进行全采样获得的全视野自校准采样数据在三维K空间中的示意图；FIG. 7 is a schematic diagram of the full-view self-calibration sampling data obtained by performing full sampling on the K-space center in the first embodiment of the present application in the three-dimensional K-space;

图8为本申请实施例一中将全视野线圈敏感度图分解成第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图的示意图；Fig. 8 is a schematic diagram of decomposing the full field of view coil sensitivity map into a first convoluted field of view coil sensitivity map and a second convoluted field of view coil sensitivity map in Embodiment 1 of the present application;

图9为本申请实施例一中将两个卷褶视野磁共振图像进行拼接获得全视野磁共振图像的示意图；9 is a schematic diagram of splicing two convoluted field-of-view magnetic resonance images to obtain a full-field magnetic resonance image in Embodiment 1 of the present application;

图10为本申请实施例一中的重建方法在卷褶视野扫描场景下采用笛卡尔采样轨迹模式的测试结果示意图；FIG. 10 is a schematic diagram of the test results of the reconstruction method in Embodiment 1 of the present application using the Cartesian sampling trajectory mode in the convoluted field of view scanning scene;

图11为本申请实施例二中卷褶视野磁共振图像的重建方法的流程示意图；FIG. 11 is a schematic flowchart of a method for reconstructing a magnetic resonance image of a convoluted field of view in Embodiment 2 of the present application;

图12为本申请实施例二中二维空间下的第一脉冲序列的示意图；FIG. 12 is a schematic diagram of the first pulse sequence in a two-dimensional space in Embodiment 2 of the present application;

图13为本申请实施例二中三维空间下的第一脉冲序列的示意图；FIG. 13 is a schematic diagram of the first pulse sequence in the three-dimensional space in Embodiment 2 of the present application;

图14为本申请实施例二中第三脉冲序列为GRE序列的示意图；FIG. 14 is a schematic diagram of the third pulse sequence in Embodiment 2 of the present application being a GRE sequence;

图15为本申请实施例二中二维空间下的第四脉冲序列的示意图；FIG. 15 is a schematic diagram of a fourth pulse sequence in a two-dimensional space in Embodiment 2 of the present application;

图16为本申请实施例二中相位编码方向的脉冲序列的示意图；FIG. 16 is a schematic diagram of the pulse sequence in the phase encoding direction in Embodiment 2 of the present application;

图17为本申请实施例二中选层方向的脉冲序列的示意图；Fig. 17 is a schematic diagram of the pulse sequence in the layer selection direction in the second embodiment of the present application;

图18为本申请实施例二中第四脉冲序列中的相位编码方向的脉冲序列的示意图；FIG. 18 is a schematic diagram of the pulse sequence in the phase encoding direction in the fourth pulse sequence in Embodiment 2 of the present application;

图19为本申请实施例二中第四脉冲序列中的选层方向的脉冲序列的示意图；FIG. 19 is a schematic diagram of the pulse sequence in the layer selection direction in the fourth pulse sequence in Embodiment 2 of the present application;

图20为本申请实施例二中将全视野点扩散函数分解成第一卷褶视野点扩散函数、第二卷褶视野点扩散函数的示意图；Fig. 20 is a schematic diagram of decomposing the full view point spread function into the first convoluted view point spread function and the second convoluted view point spread function in the second embodiment of the present application;

图21为本申请实施例二中将两个卷褶视野磁共振图像进行拼接获得全视野磁共振图像的示意图；21 is a schematic diagram of splicing two convoluted field-of-view magnetic resonance images to obtain a full-field magnetic resonance image in Example 2 of the present application;

图22为本申请实施例二中的重建方法在卷褶视野扫描场景下采用波浪可控混叠编码采样轨迹模式的测试结果示意图；Fig. 22 is a schematic diagram of the test results of the reconstruction method in Embodiment 2 of the present application using wave controllable aliasing encoding sampling track mode in the scene of the field of view scanning of folds;

图23为本申请实施例三中的重建***的结构示意图；FIG. 23 is a schematic structural diagram of the reconstruction system in Embodiment 3 of the present application;

图24为本申请实施例四中的重建***的结构示意图；FIG. 24 is a schematic structural diagram of the reconstruction system in Embodiment 4 of the present application;

图25为本申请实施例五中的计算机设备的结构示意图。FIG. 25 is a schematic structural diagram of a computer device in Embodiment 5 of the present application.

具体实施方式Detailed ways

以下，将参照附图来详细描述本发明的实施例。然而，可以以许多不同的形式来实施本发明，并且本发明不应该被解释为限制于这里阐述的具体实施例。相反，提供这些实施例是为了解释本发明的原理及其实际应用，从而使本领域的其他技术人员能够理解本发明的各种实施例和适合于特定预期应用的各种修改。在附图中，相同的标号将始终被用于表示相同的元件。Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the specific embodiments set forth herein. Rather, the embodiments are provided to explain the principles of the invention and its practical application, thereby enabling others skilled in the art to understand the invention for various embodiments and with various modifications as are suited to particular intended uses. In the drawings, the same reference numerals will be used to denote the same elements throughout.

本申请提出的卷褶视野磁共振图像的重建方法包括：The method for reconstructing the magnetic resonance image of the folded field of view proposed in this application includes:

基于全视野自校准采样数据计算全视野线圈敏感度图；Calculate the full-field coil sensitivity map based on the full-field self-calibration sampling data;

根据卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像。Image reconstruction was performed according to the undersampled data of the convoluted field of view and the sensitivity map of the full field of view to obtain a full field of view magnetic resonance image.

本申请提供的卷褶视野磁共振图像的重建方法利用全视野采样数据建模来对卷褶视野欠采样数据进行图像重建，以获得全视野磁共振图像，从而避免了在卷褶视野扫描场景中的重建混叠伪影现象，提升重建图像的质量。The method for reconstructing the magnetic resonance image of the convoluted field of view provided by this application utilizes full-field sampling data modeling to perform image reconstruction on the undersampled data of the convoluted field of view to obtain a full-field magnetic resonance image, thereby avoiding the The reconstructed aliasing artifact phenomenon can improve the quality of the reconstructed image.

下面通过几个具体的实施例并结合附图来对本申请中的卷褶视野磁共振图像的重建方法、计算机设备及存储介质进行详细的描述。The reconstruction method, computer equipment and storage medium of the magnetic resonance image of the folded field of view in the present application will be described in detail through several specific embodiments and with reference to the accompanying drawings.

实施例一Embodiment one

参照图1，本实施例中的卷褶视野磁共振图像的重建方法包括步骤：Referring to Fig. 1, the method for reconstructing the magnetic resonance image of the convoluted field of view in the present embodiment includes steps:

S1、获取目标对象在第一脉冲序列激发下的卷褶视野欠采样数据；S1. Obtain undersampling data of the target object under the excitation of the first pulse sequence;

S2、获取目标对象在第二脉冲序列激发下的全视野自校准采样数据；S2. Obtain the full field of view self-calibration sampling data of the target object under the excitation of the second pulse sequence;

S3、基于全视野自校准采样数据计算全视野线圈敏感度图；S3. Calculate the full-field coil sensitivity map based on the full-field self-calibration sampling data;

S4、根据卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像。S4. Perform image reconstruction according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map to obtain a full field of view magnetic resonance image.

本实施例中卷褶视野欠采样数据、全视野自校准采样数据的获取顺序可以为根据实际需要来调整，即步骤S1、S2的先后顺序可以调整，本实施例仅以依次获取卷褶视野欠采样数据、全视野自校准采样数据为例来进行说明，但是，这并不用于对卷褶视野欠采样数据、全视野自校准采样数据的获取顺序进行限定。In this embodiment, the acquisition order of undersampled data of the pleat field of view and the self-calibration sampling data of the full field of view can be adjusted according to actual needs, that is, the order of steps S1 and S2 can be adjusted. The sampling data and the full field of view self-calibration sampling data are taken as examples for illustration, but this is not used to limit the acquisition order of the convoluted field of view undersampling data and the full field of view self-calibration sampling data.

在步骤S1，卷褶视野欠采样数据为采用笛卡尔采样轨迹模式获得的欠采样数据，本实施例中的第一脉冲序列和第二脉冲序列相同。In step S1, the undersampled data of the convoluted field of view is the undersampled data obtained by adopting the Cartesian sampling trajectory mode, and the first pulse sequence and the second pulse sequence in this embodiment are the same.

本实施例以第一脉冲序列、第二脉冲序列为梯度回波(gradient echo，GRE)序列为例来对本实施例中的重建方法进行详细的描述，当然，这里仅仅是作为示例示出，并不用于限定，本实施例中的第一脉冲序列、第二脉冲序列还可以选自快速自旋回波(fast spin echo，FSE)序列、平衡稳态自由进动(balanced steady-state free precession，bSSFP)序列和平面回波(echo planar imaging，EPI)序列中的一种。In this embodiment, the first pulse sequence and the second pulse sequence are gradient echo (gradient echo, GRE) sequences as an example to describe the reconstruction method in this embodiment in detail. Of course, this is only shown as an example, and Not for limitation, the first pulse sequence and the second pulse sequence in this embodiment can also be selected from fast spin echo (fast spin echo, FSE) sequence, balanced steady-state free precession (balanced steady-state free precession, bSSFP) ) sequence and echo planar imaging (echo planar imaging, EPI) sequence.

参照图2～3，本实施例中的重建方法可以用于二维磁共振图像的重建，也可以应用于三维磁共振图像的重建，图2示出了第一脉冲序列、第二脉冲序列为二维GRE序列的示意图，图3示出了第一脉冲序列、第二脉冲序列为三维GRE序列的示意图，其中，三维GRE序列是由二维GRE序列在选层方向上增加梯度场得到的，增加的梯度场位于选层方向上的两个读出序列之间，不会对目标对象在第一脉冲序列、第二脉冲序列激发下的信号造成影响，从而不会引入额外的伪影。Referring to Figures 2 to 3, the reconstruction method in this embodiment can be used for the reconstruction of two-dimensional magnetic resonance images, and can also be applied to the reconstruction of three-dimensional magnetic resonance images. Figure 2 shows that the first pulse sequence and the second pulse sequence are A schematic diagram of a two-dimensional GRE sequence, Figure 3 shows a schematic diagram of the first pulse sequence and the second pulse sequence being a three-dimensional GRE sequence, wherein the three-dimensional GRE sequence is obtained by increasing the gradient field in the layer selection direction of the two-dimensional GRE sequence, The increased gradient field is located between the two readout sequences in the layer selection direction, and will not affect the signal of the target object under the excitation of the first pulse sequence and the second pulse sequence, thus will not introduce additional artifacts.

参照图4～5，本实施例中得到的卷褶视野欠采样数据可以根据已有的K空间欠采样方法来获得，例如，可以采用规则欠采样、随机欠采样、混合采样、可控混叠并行采样(Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration，CAIPIRINHA)等方法来获得卷褶视野欠采样数据，其中，随机欠采样又包括等密度随机欠采样、变密度随机欠采样。图4示出了根据规则欠采样的方法获得的卷褶视野欠采样数据在二维K空间中的示意图，其中，在频率编码方向3倍欠采样，加速倍数为3倍，虚线为全采样所需采集的读出线，实线为3倍欠采样所需采集的读出线。图5示出了根据规则欠采样的方法获得的卷褶视野欠采样数据在三维K空间中的示意图，其中，同时与相位编码方向和选层方向垂直的方向为读出方向，在相位编码方向2倍欠采样，在选层方向2倍欠采样，总的加速倍数为4倍，虚线交点为全采样所需采集的读出线，加粗实心圆点为4倍欠采样所需采集的读出线。Referring to Figures 4-5, the undersampled data of the convoluted field of view obtained in this embodiment can be obtained according to existing K-space undersampling methods, for example, regular undersampling, random undersampling, mixed sampling, controllable aliasing can be used Parallel sampling (Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration, CAIPIRINHA) and other methods are used to obtain undersampling data of the convoluted field of view. Among them, random undersampling includes equal density random undersampling and variable density random undersampling. Fig. 4 shows the schematic diagram of the undersampled data of the convoluted field of view obtained according to the method of regular undersampling in the two-dimensional K space, in which, in the frequency encoding direction, the undersampling is 3 times, the acceleration factor is 3 times, and the dotted line is the result of full sampling The readout line to be collected, the solid line is the readout line to be collected by 3 times undersampling. Fig. 5 shows a schematic diagram of the undersampled data of the convoluted field of view obtained according to the method of regular undersampling in the three-dimensional K space, wherein the direction perpendicular to the phase encoding direction and the layer selection direction is the readout direction, and in the phase encoding direction 2 times undersampling, 2 times undersampling in the direction of layer selection, the total acceleration factor is 4 times, the dotted line intersection is the readout line required for full sampling, and the bold solid circle is the readout required for 4 times undersampling qualify.

本实施例通过采用欠采样方法来获得卷褶视野欠采样数据可以有效减少磁共振的扫描时间，有效提升了数据采集效率。In this embodiment, by adopting the undersampling method to obtain the undersampled data of the convoluted field of view, the scanning time of the magnetic resonance can be effectively reduced, and the data acquisition efficiency can be effectively improved.

参照图6～7，在步骤S2中，由于K空间中心的数据决定重建图像的对比度，为了能够获得较清晰的重建图像，通过对K空间中心进行全采样来获得全视野自校准采样数据，图6示出了对K空间中心进行全采样获得的全视野自校准采样数据在二维K空间中的示意图，虚线为全采样所需采集的读出线，实线为全视野自校准采样所需采集的读出线，图7示出了对K空间中心进行全采样获得的全视野自校准采样数据在三维K空间中的示意图，其中，同时与相位编码方向和选层方向垂直的方向为读出方向，虚线交点为全采样所需采集的读出线，加粗实心圆点为全视野自校准采样所需采集的读出线，其中，读出线的数量可以根据实际需要来设定，图6、图7中仅仅是作为示例示出，并不作限定。Referring to Figures 6-7, in step S2, since the data at the center of K-space determines the contrast of the reconstructed image, in order to obtain a clearer reconstructed image, the full-view self-calibration sampling data is obtained by performing full sampling on the center of K-space, as shown in Fig. 6 shows the schematic diagram of the full-field self-calibration sampling data obtained by full sampling of the K-space center in two-dimensional K-space. The collected readout line, Fig. 7 shows a schematic diagram of the full field of view self-calibration sampling data in the three-dimensional K space obtained by performing full sampling on the center of K space, where the direction perpendicular to the phase encoding direction and layer selection direction is the readout In the direction of output, the dotted line intersection is the readout line required for full sampling, and the bold solid circle is the readout line required for full field of view self-calibration sampling. The number of readout lines can be set according to actual needs. 6 and 7 are shown as examples only, and are not intended to be limiting.

在步骤S3中，在获得全视野自校准采样数据后，基于全视野自校准采样数据计算全视野线圈敏感度图，具体包括：In step S3, after obtaining the full-field self-calibration sampling data, the full-field coil sensitivity map is calculated based on the full-field self-calibration sampling data, specifically including:

S31、获取全视野自校准采样数据的特征值；S31. Acquiring feature values of the full field of view self-calibration sampling data;

S32、求解特征值中最大的特征值对应的特征向量并将该特征向量作为全视野线圈敏感度图。S32. Solve an eigenvector corresponding to the largest eigenvalue among the eigenvalues and use the eigenvector as a sensitivity map of the full field of view coil.

具体地，在获得全视野自校准采样数据后便可以求出其对应的所有特征值，再根据所有特征值中最大的特征值求出该最大特征值对应的特征向量

其中，N _c表示线圈通道数量，将C作为全视野线圈敏感度图，需要说明的是，本实施例中求解全视野线圈敏感度图也可以采用已有的线圈敏感度图估计方法，这里不做限定。 Specifically, after obtaining the full-field self-calibration sampling data, all corresponding eigenvalues can be obtained, and then the eigenvector corresponding to the largest eigenvalue can be obtained according to the largest eigenvalue among all eigenvalues

Wherein, N _c represents the number of coil channels, and C is used as the full-field coil sensitivity map. It should be noted that the existing coil sensitivity map estimation method can also be used to solve the full-field coil sensitivity map in this embodiment, which is not described here. Do limited.

在步骤S4中，根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得磁共振图像，具体包括：In step S4, perform image reconstruction according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, and obtain a magnetic resonance image, specifically including:

S41、将全视野线圈敏感度图分解成第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图；S41. Decomposing the full field of view coil sensitivity map into a first pleat field of view coil sensitivity map and a second pleat field of view coil sensitivity map;

S42、根据卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图建立优化模型；S42. Establish an optimization model according to the undersampled data of the pleat field of view, the sensitivity map of the first pleat field of view coil, and the sensitivity map of the second pleat field of view coil;

S43、求解优化模型的最小值，获得两个卷褶视野磁共振图像；S43, solving the minimum value of the optimization model, and obtaining two magnetic resonance images of the convoluted field of view;

S44、将两个卷褶视野磁共振图像进行拼接获得全视野磁共振图像。S44. Splicing the two convoluted field of view magnetic resonance images to obtain a full field of view magnetic resonance image.

参照图8，在步骤S41中，将全视野线圈敏感度图的均分为两部分，将中间的一部分作为第一卷褶视野线圈敏感度图，将剩余的边缘的部分作为第二卷褶视野线圈敏感度图，图8中左边的图为全视野线圈敏感度图的示意图，右边的两个图分别为第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图的示意图，需要说明的是，本实施例中也可以采用其他的分解方式对全视野线圈敏感度图进行分解，例如，从全视野线圈敏感度图的中间剪切，将全视野线圈敏感度图分解为左右两部分并将左右两部分分别作为第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图。Referring to FIG. 8 , in step S41, the full field of view coil sensitivity map is divided into two parts equally, the middle part is used as the first convolution field of view coil sensitivity map, and the remaining edge part is used as the second convolution field of view Coil sensitivity diagram, the left diagram in Fig. 8 is the schematic diagram of the coil sensitivity diagram of the whole field of view, and the two diagrams on the right are respectively the schematic diagrams of the coil sensitivity diagram of the first coiled field of view and the coil sensitivity diagram of the second coiled field of view, It should be noted that in this embodiment, other decomposition methods can also be used to decompose the full-field coil sensitivity map, for example, cutting from the middle of the full-field coil sensitivity map, decomposing the full-field coil sensitivity map into left and right Two parts and the left and right parts are respectively used as the sensitivity map of the first pleated field of view coil and the sensitivity map of the second pleated field of view coil.

在步骤S42中，根据卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图建立优化模型如下：In step S42, an optimization model is established according to the undersampled data of the pleat field of view, the coil sensitivity map of the first pleat field of view, and the sensitivity map of the second pleat field of view coil as follows:

其中，M表示卷褶视野K空间的欠采样模板，F _xy表示沿着频率编码方向和相位编码方向的二维傅里叶变换，N _c表示线圈通道数量，C _i1表示第一卷褶视野线圈敏感度图的第i通道的线圈敏感度图，C _i2表示第二卷褶视野线圈敏感度图的第i通道的线圈敏感度图，y _i表示卷褶视野欠采样数据的第i通道的欠采样数据，λ表示稀疏约束权重，W表示小波变换，x _j表示待求解的两个卷褶视野磁共振图像。 Among them, M represents the undersampling template of the convoluted view K space, F _xy represents the two-dimensional Fourier transform along the frequency encoding direction and the phase encoding direction, N _c represents the number of coil channels, C _i1 represents the first convoluted view coil The coil sensitivity map of the i-th channel of the sensitivity map, C _i2 represents the coil sensitivity map of the i-th channel of the second convoluted field of view coil sensitivity map, y _i represents the undersampling of the i-th channel of the convoluted field of view undersampling data Sampling data, λ represents the sparse constraint weight, W represents the wavelet transform, and x _j represents the magnetic resonance images of the two convoluted fields of view to be solved.

参照图9，在步骤S43～S44中，通过求解上述优化方程的最小值并将最小值对应的两个值作为两个卷褶视野磁共振图像，再根据反卷褶的方法将两个卷褶视野磁共振图像进行拼接，最终获得全视野磁共振图像，其中，图9中左边的两个图分别为两个卷褶视野磁共振图像的示意图，图9中右边的图为全视野磁共振图像的示意图。Referring to Fig. 9, in steps S43-S44, by solving the minimum value of the above-mentioned optimization equation and taking the two values corresponding to the minimum value as two convoluted field-of-view magnetic resonance images, the two convoluted images are then deconvoluted according to the deconvoluted method. The field of view magnetic resonance images are spliced to finally obtain a full field of view magnetic resonance image, wherein the two pictures on the left in Figure 9 are schematic diagrams of two convoluted field of view magnetic resonance images, and the right picture in Figure 9 is a full field of view magnetic resonance image schematic diagram.

参照图10，图10示出了本实施例中的重建方法在卷褶视野扫描场景下采用笛卡尔采样轨迹模式的测试结果，其中，图10右边的图为本实施例中的重建方法得到的磁共振图像，图10左边的图为传统的敏感度编码重建方法得到的磁共振图像，从图10中可以看出，与传统的敏感度编码重建方法相比，本实施例中的重建方法均能够得到在卷褶视野扫描场景下采用笛卡尔采样轨迹模式的全视野磁共振图像且能够很好的去除边缘伪影，重建图像的质量较好。Referring to Fig. 10, Fig. 10 shows the test results of the reconstruction method in this embodiment using the Cartesian sampling trajectory mode in the convoluted field of view scanning scene, wherein the figure on the right side of Fig. 10 is obtained by the reconstruction method in this embodiment Magnetic resonance image, the figure on the left side of Fig. 10 is the magnetic resonance image obtained by the traditional sensitivity coding reconstruction method, as can be seen from Fig. 10, compared with the traditional sensitivity coding reconstruction method, the reconstruction method in the present embodiment is It can obtain a full-field magnetic resonance image using the Cartesian sampling trajectory mode in the pleated field of view scanning scene, and can remove edge artifacts very well, and the quality of the reconstructed image is good.

本实施例中的重建方法除了应用到二维、三维磁共振图像的重建中，还可以应用到多层(SMS)成像中，其基本原理与本实施例所描述的相同，这里不再赘述。The reconstruction method in this embodiment is not only applied to the reconstruction of 2D and 3D magnetic resonance images, but also can be applied to multi-slice (SMS) imaging. The basic principle is the same as that described in this embodiment, and will not be repeated here.

实施例二Embodiment two

参照图11，本实施例中的卷褶视野磁共振图像的重建方法包括步骤：Referring to FIG. 11 , the reconstruction method of the magnetic resonance image of the convoluted field of view in this embodiment includes steps:

S4、根据目标对象的全视野二维全采样数据获得全视野点扩散函数，其中，全视野二维全采样数据的成像视野与全视野自校准采样数据的成像视野相同；S4. Obtain a full-view point spread function according to the full-view two-dimensional full-sampling data of the target object, wherein the imaging field of view of the full-view two-dimensional full-sampling data is the same as the imaging field of view of the full-view self-calibration sampling data;

S5、根据卷褶视野欠采样数据、全视野点扩散函数、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像。S5. Perform image reconstruction according to the undersampled data of the convoluted field of view, the point spread function of the full field of view, and the sensitivity map of the full field of view coil, and obtain a full field of view magnetic resonance image.

本实施例中卷褶视野欠采样数据、全视野自校准采样数据、全视野点扩散函数的获取顺序可以为根据实际需要来调整，即步骤S1、S2、S4的先后顺序可以调整，本实施例仅以依次获取卷褶视野欠采样数据、全视野自校准采样数据、全视野点扩散函数为例来进行说明，但是，这并不用于对卷褶视野欠采样数据、全视野自校准采样数据、全视野点扩散函数的获取顺序进行限定。In this embodiment, the acquisition order of the undersampled data of the pleated field of view, the self-calibration sampling data of the full field of view, and the point spread function of the full field of view can be adjusted according to actual needs, that is, the sequence of steps S1, S2, and S4 can be adjusted. In this embodiment, It is only illustrated by taking the undersampling data of the pleated field of view, the self-calibration sampling data of the full field of view, and the point spread function of the full field of view sequentially as an example. The acquisition order of the full field of view point spread function is limited.

在步骤S1中，卷褶视野欠采样数据为采用波浪可控混叠编码采样轨迹模式获得的欠采样数据，第一脉冲序列是由第二脉冲序列增加正弦梯度场获得，正旋梯度场包括相位编码方向的正弦梯度场和选层方向的正旋梯度场。本实施例以第二脉冲序列为梯度回波(gradient echo，GRE)序列为例来对本实施例中的重建方法进行详细的描述，当然，这里仅仅是作为示例示出，并不用于限定，本实施例中的第二脉冲序列还可以选自快速自旋回波(fast spin echo，FSE)序列、平衡稳态自由进动(balanced steady-state free precession，bSSFP)序列和平面回波(echo planar imaging，EPI)序列中的一种。In step S1, the undersampled data of the convoluted field of view is the undersampled data obtained by using the wave controllable aliasing coding sampling trajectory mode, the first pulse sequence is obtained by adding a sinusoidal gradient field to the second pulse sequence, and the sinusoidal gradient field includes the phase The sinusoidal gradient field in the encoding direction and the sinusoidal gradient field in the layer selection direction. This embodiment takes the second pulse sequence as a gradient echo (gradient echo, GRE) sequence as an example to describe the reconstruction method in this embodiment in detail. Of course, this is only shown as an example and is not used for limitation. The second pulse sequence in the embodiment can also be selected from fast spin echo (fast spin echo, FSE) sequence, balanced steady-state free precession (balanced steady-state free precession, bSSFP) sequence and planar echo (echo planar imaging) , one of the EPI) sequences.

参照图12～13，本实施例中的重建方法可以用于二维磁共振图像的重建，也可以应用于三维磁共振图像的重建，图12示出了二维空间下的第一脉冲序列的示意图，图13示出了三维空间下的第一脉冲序列的示意图，其中，二维空间下的第一脉冲序列是由第二脉冲序列在相位编码方向上增加正弦梯度场得到的，三维空间下的第一脉冲序列是由第二脉冲序列在相位编码方向上增加正弦梯度场和在选层方向上增加正弦梯度场得到的，第二脉冲序列为GRE序列的示意图参见实施例一中的图2所示，这里定义，在相位编码方向上增加的正弦梯度场为第一正弦梯度场，在选层方向上增加的正弦梯度场为第二正弦梯度场，第一正弦梯度场与第二正弦梯度场的相位差为π/2，第一正弦梯度场和第二正弦梯度场的波形均为正弦波，第一正弦梯度场的波形可以与第二正弦梯度场的波形相同，也可以不同。Referring to Figures 12-13, the reconstruction method in this embodiment can be used for the reconstruction of two-dimensional magnetic resonance images, and can also be applied to the reconstruction of three-dimensional magnetic resonance images, Figure 12 shows the first pulse sequence in two-dimensional space Schematic diagram, Fig. 13 shows a schematic diagram of the first pulse sequence in three-dimensional space, wherein, the first pulse sequence in two-dimensional space is obtained by adding a sinusoidal gradient field in the phase encoding direction of the second pulse sequence, and in three-dimensional space The first pulse sequence is obtained by increasing the sinusoidal gradient field in the phase encoding direction and the sinusoidal gradient field in the layer selection direction by the second pulse sequence, and the second pulse sequence is a schematic diagram of the GRE sequence. Refer to Figure 2 in Embodiment 1 As shown, it is defined here that the sinusoidal gradient field increased in the phase encoding direction is the first sinusoidal gradient field, the sinusoidal gradient field increased in the layer selection direction is the second sinusoidal gradient field, the first sinusoidal gradient field and the second sinusoidal gradient field The field phase difference is π/2, the waveforms of the first sinusoidal gradient field and the second sinusoidal gradient field are both sinusoidal waves, and the waveform of the first sinusoidal gradient field can be the same as that of the second sinusoidal gradient field, or can be different.

第一正旋梯度场位于相位编码方向上的两个读出序列之间，第二正弦梯度场位于选层方向上的两个读出序列之间，这样，第一正旋梯度场和第二正弦梯度场不会对目标对象在第二脉冲序列激发下的信号造成影响，从而不会引入额外的伪影。The first sinusoidal gradient field is located between the two readout sequences in the phase encoding direction, and the second sinusoidal gradient field is located between the two readout sequences in the layer selection direction. In this way, the first forward gradient field and the second The sinusoidal gradient field does not affect the signal of the target object excited by the second pulse train, so that no additional artifacts are introduced.

再次参照图4～5，本实施例中得到的卷褶视野欠采样数据可以根据已有的K空间欠采样方法来获得，例如，可以采用规则欠采样、随机欠采样、混合采样、可控混叠并行采样(Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration，CAIPIRINHA)等方法来获得卷褶视野欠采样数据，其中，随机欠采样又包括等密度随机欠采样、变密度随机欠采样。图4示出了根据规则欠采样的方法获得的卷褶视野欠采样数据在二维K空间中的示意图，其中，在频率编码方向3倍欠采样，加速倍数为3倍，虚线为全采样所需采集的读出线，实线为3倍欠采样所需采集的读出线。图5示出了根据规则欠采样的方法获得的卷褶视野欠采样数据在三维K空间中的示意图，其中，同时与相位编码方向和选层方向垂直的方向为读出方向，在相位编码方向2倍欠采样，在选层方向2倍欠采样，总的加速倍数为4倍，虚线交点为全采样所需采集的读出线，加粗实心圆点为4倍欠采样所需采集的读出线。Referring to Figures 4-5 again, the undersampled data of the pleat field of view obtained in this embodiment can be obtained according to existing K-space undersampling methods, for example, regular undersampling, random undersampling, mixed sampling, controllable mixed sampling can be used. Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration (CAIPIRINHA) and other methods to obtain the undersampling data of the convoluted field of view. Among them, random undersampling includes equal density random undersampling and variable density random undersampling. Fig. 4 shows the schematic diagram of the undersampled data of the convoluted field of view obtained according to the method of regular undersampling in the two-dimensional K space, in which, in the frequency encoding direction, the undersampling is 3 times, the acceleration factor is 3 times, and the dotted line is the result of full sampling The readout line to be collected, the solid line is the readout line to be collected by 3 times undersampling. Fig. 5 shows a schematic diagram of the undersampled data of the convoluted field of view obtained according to the method of regular undersampling in the three-dimensional K space, wherein the direction perpendicular to the phase encoding direction and the layer selection direction is the readout direction, and in the phase encoding direction 2 times undersampling, 2 times undersampling in the direction of layer selection, the total acceleration factor is 4 times, the dotted line intersection is the readout line required for full sampling, and the bold solid circle is the readout required for 4 times undersampling qualify.

通过采用欠采样方法来获得卷褶视野欠采样数据可以有效减少磁共振的扫描时间，同时通过采用增加正弦梯度场的第一脉冲序列来对目标对象进行激发，在频率编码方向造成扩散混叠来降低几何因子，几何因子降低，重建图像的信噪比损失降低，从而在实现减少扫描时间的同时提升重建图像的质量。Obtaining the undersampling data of the convoluted field of view by using the undersampling method can effectively reduce the scanning time of magnetic resonance. At the same time, the target object is excited by the first pulse sequence with an increased sinusoidal gradient field, which causes diffusion aliasing in the frequency encoding direction. The geometric factor is reduced, the geometric factor is reduced, and the signal-to-noise ratio loss of the reconstructed image is reduced, thereby reducing the scanning time and improving the quality of the reconstructed image.

再次参照图6～7，由于K空间中心的数据决定重建图像的对比度，为了能够获得较清晰的重建图像，通过对K空间中心进行全采样来获得全视野自校准采样数据，图6示出了对K空间中心进行全采样获得的全视野自校准采样数据在二维K空间中的示意图，虚线为全采样所需采集的读出线，实线为低分辨率全采样所需采集的读出线，图7示出了对K空间中心进行全采样获得的全视野自校准采样数据在三维K空间中的示意图，其中，同时与相位编码方向和选层方向垂直的方向为读出方向，虚线交点为全采样所需采集的读出线，加粗实心圆点为低分辨率全采样所需采集的读出线，其中，读出线的数量可以根据实际需要来设定，图6～7中仅仅是作为示例示出，并不作限定。Referring to Figures 6 to 7 again, since the data at the center of K-space determines the contrast of the reconstructed image, in order to obtain a clearer reconstructed image, the full-view self-calibration sampling data is obtained by performing full sampling on the center of K-space. Figure 6 shows Schematic diagram of the full field of view self-calibration sampling data obtained by full sampling in the center of K space in two-dimensional K space, the dotted line is the readout line required for full sampling, and the solid line is the readout required for low resolution full sampling line, Figure 7 shows a schematic diagram of the full-view self-calibration sampling data in the three-dimensional K space obtained by performing full sampling on the center of K space, where the direction perpendicular to the phase encoding direction and layer selection direction is the readout direction, and the dotted line The intersection points are the readout lines required for full sampling, and the bold solid circles are the readout lines required for low-resolution full sampling. The number of readout lines can be set according to actual needs, as shown in Figures 6-7 is shown as an example only, and is not intended to be limiting.

在步骤S4中，对于二维磁共振图像的重建，根据目标对象的全视野二维全采样数据获得点扩散函数，其中，全视野二维全采样数据的成像视野与全视野自校准采样数据的成像视野相同，即全视野二维全采样数据的大小与全视野自校准采样数据的大小相等，步骤S4具体包括：In step S4, for the reconstruction of the two-dimensional magnetic resonance image, the point spread function is obtained according to the full-field two-dimensional full sampling data of the target object, wherein, the imaging field of view of the full-field two-dimensional full sampling data and the full-field self-calibration sampling data The imaging field of view is the same, that is, the size of the full field of view two-dimensional full sampling data is equal to the size of the full field of view self-calibration sampling data. Step S4 specifically includes:

S41、获取目标对象在第三脉冲序列激发下的第一全视野二维全采样数据；S41. Acquiring the first full-field two-dimensional full sampling data of the target object excited by the third pulse sequence;

S42、获取目标对象在第四脉冲序列激发下的第二全视野二维全采样数据，第四脉冲序列是由第三脉冲序列增加正弦梯度场获得，其中，第一全视野二维全采样数据和第二全视野二维全采样数据的成像视野相同；S42. Obtain the second full-view two-dimensional full-sampling data of the target object under the excitation of the fourth pulse sequence. The fourth pulse sequence is obtained by adding a sinusoidal gradient field to the third pulse sequence, wherein the first full-view two-dimensional full-sampling data It is the same as the imaging field of view of the second full field of view 2D full sampling data;

S43、将第二全视野二维全采样数据除以第一全视野二维全采样数据得到点扩散函数。S43. Divide the second full-view two-dimensional full-sampling data by the first full-view two-dimensional full-sampling data to obtain a point spread function.

具体地，步骤S43包括：Specifically, step S43 includes:

S431、将第二全视野二维全采样数据除以第一全视野二维全采样数据得到初始点扩散函数；S431. Dividing the second full-view two-dimensional full sampling data by the first full-view two-dimensional full sampling data to obtain an initial point spread function;

S432、将初始点扩散函数在K空间沿着频率编码方向进行线性拟合获得全视野点扩散函数。S432. Perform linear fitting on the initial point spread function along the frequency encoding direction in K space to obtain a point spread function of the whole field of view.

参照图14～15，将本实施例中的重建方法用于二维磁共振图像的重建时，第三脉冲序列是由第二脉冲序列关闭频率编码梯度场而得到，图14示出了第三脉冲序列为GRE序列的示意图，二维空间下的第四脉冲序列是由第三脉冲序列在相位编码方向上增加第一正弦梯度场得到的，图15示出了二维空间下的第四脉冲序列的示意图。Referring to Figures 14-15, when the reconstruction method in this embodiment is used for the reconstruction of two-dimensional magnetic resonance images, the third pulse sequence is obtained by turning off the frequency encoding gradient field of the second pulse sequence, and Figure 14 shows the third The pulse sequence is a schematic diagram of the GRE sequence. The fourth pulse sequence in the two-dimensional space is obtained by adding the first sinusoidal gradient field in the phase encoding direction of the third pulse sequence. Figure 15 shows the fourth pulse in the two-dimensional space Schematic diagram of the sequence.

在获得目标对象在第三脉冲序列、第四脉冲序列激发下的第一全视野二维全采样数据、第二全视野二维全采样数据后，通过下面的式子获得初始点扩散函数：After obtaining the first full field of view two-dimensional full sampling data and the second full field of view two-dimensional full sampling data of the target object under the excitation of the third pulse sequence and the fourth pulse sequence, the initial point spread function is obtained by the following formula:

PsfY(k _x,y)＝P′ _y(k _x,y)/P _y(k _x,y) PsfY(k _x ,y)=P′ _y (k _x ,y)/P _y (k _x ,y)

其中，P _y(k _x,y)表示相位编码方向上的第一全视野二维全采样数据，P′ _y(k _x,y)表示相位编码方向上的第二全视野二维全采样数据，PsfY(k _x,y)表示相位编码方向上的初始点扩散函数。 Among them, P _y (k _x , y) represents the first full-view two-dimensional full-sampling data in the phase encoding direction, and P′ _y (k _x , y) represents the second full-view two-dimensional full-sampling data in the phase encoding direction , PsfY(k _x ,y) represents the initial point spread function in the phase encoding direction.

参照图16～19，将本实施例中的重建方法用于三维磁共振图像的重建时，第三脉冲序列包括相位编码方向的脉冲序列和选层方向的脉冲序列，相位编码方向的脉冲序列由第二脉冲序列关闭频率编码梯度场、选层梯度场而得到，选层方向的脉冲序列由第二脉冲序列关闭频率编码梯度场、相位编码梯度场而得到，图16示出了相位编码方向的脉冲序列的示意图，图17示出了选层方向的脉冲序列的示意图，三维空间下的第四脉冲序列也包括相位编码方向的脉冲序列和选层方向的脉冲序列，其中，第四脉冲序列中的相位编码方向的脉冲序列是由第三脉冲中的相位编码方向的脉冲序列在相位编码方向上增加第一正弦梯度场得到，第四脉冲序列中的选层方向的脉冲序列是由第三脉冲中的选层方向的脉冲序列在选层方向上增加第二正弦梯度场得到，图18示出了第四脉冲序列中的相位编码方向的脉冲序列的示意图，图19示出了第四脉冲序列中的选层方向的脉冲序列的示意图。Referring to Figures 16-19, when the reconstruction method in this embodiment is used for the reconstruction of a three-dimensional magnetic resonance image, the third pulse sequence includes a pulse sequence in the phase encoding direction and a pulse sequence in the layer selection direction, and the pulse sequence in the phase encoding direction is composed of The second pulse sequence is obtained by turning off the frequency encoding gradient field and the layer selection gradient field, and the pulse sequence in the layer selection direction is obtained by turning off the frequency encoding gradient field and the phase encoding gradient field by the second pulse sequence. Figure 16 shows the phase encoding direction. A schematic diagram of the pulse sequence, Fig. 17 shows a schematic diagram of the pulse sequence in the layer selection direction, the fourth pulse sequence in the three-dimensional space also includes the pulse sequence in the phase encoding direction and the pulse sequence in the layer selection direction, wherein, in the fourth pulse sequence The pulse sequence in the phase encoding direction is obtained by adding the first sinusoidal gradient field in the phase encoding direction to the pulse sequence in the phase encoding direction in the third pulse, and the pulse sequence in the layer selection direction in the fourth pulse sequence is obtained by the third pulse The pulse sequence in the layer selection direction is obtained by adding the second sinusoidal gradient field in the layer selection direction. Figure 18 shows a schematic diagram of the pulse sequence in the phase encoding direction in the fourth pulse sequence, and Figure 19 shows the fourth pulse sequence Schematic illustration of the pulse sequence in the layer-selection direction.

在获得目标对象在第三脉冲序列、第四脉冲序列激发下的第一全视野二维全采样数据、第二全视野二维全采样数据后，第一全视野二维全采样数据包括相位编码方向的全采样数据和选层方向的全采样数据，第二全视野二维全采样数据也包括相位编码方向的全采样数据和选层方向的全采样数据，通过下面的式子获得相位编码方向上的初始点扩散函数：After obtaining the first full-field two-dimensional full-sampling data and the second full-field two-dimensional full-sampling data of the target object under the excitation of the third pulse sequence and the fourth pulse sequence, the first full-field two-dimensional full-sampling data includes phase encoding The full sampling data of the direction and the full sampling data of the layer selection direction, the second full field of view two-dimensional full sampling data also includes the full sampling data of the phase encoding direction and the full sampling data of the layer selection direction, and the phase encoding direction is obtained by the following formula The initial point spread function on :

其中，P _y(k _x,y)表示第一全视野二维全采样数据在相位编码方向上的全采样数据，P′ _y(k _x,y)表示第二全视野二维全采样数据在相位编码方向上的全采样数据，PsfY(k _x,y)表示相位编码方向上的初始点扩散函数。 Among them, P _y (k _x , y) represents the full sampling data of the first full-view two-dimensional full-sampling data in the phase encoding direction, and P′ _y (k _x , y) represents the second full-view two-dimensional full-sampling data in The full sampling data in the phase encoding direction, PsfY(k _x ,y) represents the initial point spread function in the phase encoding direction.

通过下面的式子获得选层方向上的初始点扩散函数：The initial point spread function in the layer selection direction is obtained by the following formula:

PsfZ(k _x,z)＝P′ _z(k _x,z)/P _z(k _x,z) PsfZ(k _x ,z)=P′ _z (k _x ,z)/P _z (k _x ,z)

其中，P _z(k _x,z)表示第一全视野二维全采样数据在选层方向上的全采样数据，P′ _z(k _x,z)表示第二全视野二维全采样数据在选层方向上的全采样数据，PsfZ(k _x,z)表示选层方向上的初始点扩散函数。 Among them, P _z (k _x , z) represents the full sampling data of the first full-view two-dimensional full-sampling data in the layer selection direction, and P′ _z (k _x , z) represents the second full-view two-dimensional full-sampling data in the layer selection direction. The full sampling data in the layer selection direction, PsfZ(k _x ,z) represents the initial point spread function in the layer selection direction.

在获得相位编码方向上的初始点扩散函数PsfY(k _x,y)和选层方向上的初始点扩散函数PsfZ(k _x,z)后，通过下面的式子获得三维空间中的初始点扩散函数： After obtaining the initial point spread function PsfY(k _x ,y) in the phase encoding direction and the initial point spread function PsfZ(k _x ,z) in the layer selection direction, the initial point spread in the three-dimensional space is obtained by the following formula function:

PsfYZ(k _x,y)＝PsfY(k _x,y)·PsfZ(k _x,z) PsfYZ(k _x ,y)＝PsfY(k _x ,y)·PsfZ(k _x ,z)

其中，PsfYZ(k _x,y)表示三维空间中的初始点扩散函数。 Among them, PsfYZ(k _x ,y) represents the initial point spread function in three-dimensional space.

在步骤S431中，通过获得二维空间、三维空间中的初始点扩散函数PsfY(k _x,y)、PsfYZ(k _x,y)后，还需要对初始点扩散函数在K空间沿着频率编码方向进行线性拟合获得二维空间、三维空间中的全视野点扩散函数Psf(k _x,y)、Psf′(k _x,y)，通过线性拟合可以得到更准确的点扩散函数，通过全视野点扩散函数对K空间采样轨迹进行校正，从而提升重建图像的准确度。这里的线型拟合方法可以采用常用的线性拟合方法，这里不再详细说明。 In step S431, after obtaining the initial point spread functions PsfY(k _x ,y) and PsfYZ(k _x ,y) in two-dimensional space and three-dimensional space, it is also necessary to encode the initial point spread function in K space along the frequency Direction linear fitting to obtain full-view point spread functions Psf(k _x ,y) and Psf′(k _x ,y) in two-dimensional space and three-dimensional space. A more accurate point spread function can be obtained through linear fitting. The full field of view point spread function corrects the K-space sampling trajectory, thereby improving the accuracy of the reconstructed image. The linear fitting method here can adopt a commonly used linear fitting method, which will not be described in detail here.

本实施例中通过目标对象的二维全采样数据来获得全视野点扩散函数，由于只需要对目标对象的二维数据进行采样，所需要的采样时间较短，从而进一步减小了磁共振的扫描时间。当然，除了本实施例提到的方法来获得全视野点扩散函数外，还可以通过其他轨迹校正的方法来获得全视野点扩散函数，例如，自动校正波浪可控混叠并行(Wave Controlled Aliasing In Parallel Imaging，Wave-CAIPI)重建等。In this embodiment, the point spread function of the full field of view is obtained through the two-dimensional full sampling data of the target object. Since only the two-dimensional data of the target object needs to be sampled, the required sampling time is relatively short, thereby further reducing the magnetic resonance Scan time. Of course, in addition to the method mentioned in this embodiment to obtain the full-view point spread function, other trajectory correction methods can also be used to obtain the full-view point spread function, for example, automatic correction of wave controllable aliasing in parallel (Wave Controlled Aliasing In Parallel Imaging, Wave-CAIPI) reconstruction, etc.

在步骤S5中，根据卷褶视野欠采样数据、全视野线圈敏感度图、全视野点扩散函数进行图像重建，获得全视野磁共振图像，具体包括：In step S5, image reconstruction is performed according to the undersampled data of the convoluted field of view, the full field of view coil sensitivity map, and the full field of view point spread function, and a full field of view magnetic resonance image is obtained, specifically including:

S42、将全视野点扩散函数分解成第一卷褶视野点扩散函数、第二卷褶视野点扩散函数；S42. Decompose the point spread function of the full field of view into the point spread function of the first pleat field of view and the point spread function of the second pleat field of view;

S43、根据卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图、第一卷褶视野点扩散函数、第二卷褶视野点扩散函数建立优化模型；S43. Establish an optimization model according to the undersampled data of the view of the convolutions, the coil sensitivity map of the first view of the fold, the coil sensitivity map of the second view of the fold, the point spread function of the first view of the fold, and the point spread function of the view of the second fold. ;

S44、求解优化模型的最小值，获得两个卷褶视野磁共振图像；S44. Solve the minimum value of the optimization model, and obtain two magnetic resonance images of the convoluted field of view;

S45、将两个卷褶视野磁共振图像进行拼接获得全视野磁共振图像。S45. Splicing the two convoluted field of view magnetic resonance images to obtain a full field of view magnetic resonance image.

再次参照图8，在步骤S41中，将全视野线圈敏感度图的均分为两部分，将中间的一部分作为第一卷褶视野线圈敏感度图，将剩余的边缘的部分作为第二卷褶视野线圈敏感度图，图8中左边的图为全视野线圈敏感度图的示意图，右边的两个图分别为第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图的示意图，需要说明的是，本实施例中也可以采用其他的分解方式对全视野线圈敏感度图进行分解，例如，从全视野线圈敏感度图的中间剪切，将全视野线圈敏感度图分解为左右两部分并将左右两部分分别作为第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图。Referring to FIG. 8 again, in step S41, the full-field coil sensitivity map is equally divided into two parts, and the middle part is used as the first convoluted field-of-view coil sensitivity map, and the remaining edge part is used as the second convoluted part. The sensitivity map of the field of view coil, the left picture in Figure 8 is a schematic diagram of the full field of view coil sensitivity map, and the two pictures on the right are respectively the schematic diagrams of the sensitivity map of the first pleated field of view coil and the sensitivity map of the second pleated field of view coil , it should be noted that in this embodiment, other decomposition methods can also be used to decompose the full-field coil sensitivity map, for example, cutting from the middle of the full-field coil sensitivity map, decomposing the full-field coil sensitivity map into The left and right parts are used as the first coil sensitivity map and the second coil sensitivity map respectively.

参照图20，在步骤S42中，将全视野点扩散函数均分为两部分，将中间的一部分作为第一卷褶视野点扩散函数，将剩余的边缘的部分作为第二卷褶视野点扩散函数，图20中上方的图为全视野点扩散函数的示意图，下方的两个图分别为第一卷褶视野点扩散函数、第二卷褶视野点扩散函数的示意图，需要说明的是，本实施例中也可以采用其他的分解方式对全视野点扩散函数进行分解，例如，从全视野点扩散函数的中间剪切，将全视野点扩散函数分解为左右两部分并将左右两部分分别作为全视野点扩散函数。Referring to FIG. 20, in step S42, the full view point spread function is divided into two parts, the middle part is used as the first convolution view point spread function, and the remaining edge part is used as the second convolution view point spread function , the upper figure in Figure 20 is a schematic diagram of the point spread function of the full field of view, and the two lower figures are the schematic diagrams of the point spread function of the first pleat field of view and the point spread function of the second pleat field of view respectively. It should be noted that this implementation In this example, other decomposition methods can also be used to decompose the full-view point spread function, for example, cut from the middle of the full-view point spread function, decompose the full-view point spread function into left and right parts, and use the left and right parts as full View point spread function.

在步骤S43中，根据卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图、第一卷褶视野点扩散函数、第二卷褶视野点扩散函数建立优化模型如下：In step S43, according to the undersampling data of the convoluted view, the first convoluted view coil sensitivity map, the second convoluted view coil sensitivity map, the first convoluted view point spread function, and the second convoluted view point spread function The optimization model is established as follows:

其中，M表示卷褶视野K空间的欠采样模板，F _x表示沿着频率编码方向的傅里叶变换，F _y表示沿着相位编码方向的傅里叶变换，N _c表示线圈通道数量，C _i1、C _i2分别表示第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图的第i通道的线圈敏感度图，P ₁、P ₂分别表示第一卷褶视野点扩散函数、第二卷褶视野点扩散函数，y _i表示卷褶视野欠采样数据的第i通道的欠采样数据，λ表示稀疏约束权重，W表示小波变换，x _j表示待求解的两个卷褶视野磁共振图像。 Among them, M represents the undersampling template of the convoluted field of view K space, F _x represents the Fourier transform along the frequency encoding direction, F _y represents the Fourier transform along the phase encoding direction, N _c represents the number of coil channels, C _i1 and C _i2 represent the coil sensitivity map of the i-th channel in the coil sensitivity map of the first convoluted field of view and the coil sensitivity map of the second convoluted field of view respectively, and P ₁ and P ₂ respectively represent the point spread function of the first convoluted field of view , the point spread function of the second convoluted view, y _i represents the undersampled data of the i-th channel of the convoluted view undersampled data, λ represents the sparse constraint weight, W represents the wavelet transform, and x _j represents the two convoluted views to be solved Magnetic resonance image.

参照图21，在步骤S43～S44中，通过求解上述优化方程的最小值并将最小值对应的两个值作为两个卷褶视野磁共振图像，再根据反卷褶的方法将两个卷褶视野磁共振图像进行拼接，最终获得全视野磁共振图像，其中，图21中左边的两个图分别为两个卷褶视野磁共振图像的示意图，图21中右边的图为全视野磁共振图像的示意图。Referring to Fig. 21, in steps S43-S44, by solving the minimum value of the above optimization equation and taking the two values corresponding to the minimum value as two convoluted field-of-view magnetic resonance images, the two convoluted fields of view magnetic resonance images are then deconvoluted according to the deconvoluted method. The field of view magnetic resonance images are spliced to finally obtain a full field of view magnetic resonance image, wherein the two pictures on the left in Figure 21 are schematic diagrams of two convoluted field of view magnetic resonance images, and the right picture in Figure 21 is a full field of view magnetic resonance image schematic diagram.

参照图22，图22示出了本实施例中的重建方法在卷褶视野扫描场景下采用波浪可控混叠编码采样轨迹模式的测试结果，其中，图22右边的图为本实施例中的重建方法得到的磁共振图像，图22左边的图为传统的敏感度编码重建方法得到的磁共振图像，从图22中可以看出，与传统的敏感度编码重建方法相比，本实施例中的重建方法均能够得到在卷褶视野扫描场景下采用波浪可控混叠编码采样轨迹模式的全视野磁共振图像且能够很好的去除中心伪影和边缘伪影，重建图像的质量较好。Referring to Fig. 22, Fig. 22 shows the test results of the reconstruction method in this embodiment using wave controllable aliasing coded sampling track mode in the scene of convoluted field of view scanning, wherein the picture on the right side of Fig. 22 is the The magnetic resonance image obtained by the reconstruction method, the figure on the left side of Figure 22 is the magnetic resonance image obtained by the traditional sensitivity encoding reconstruction method, as can be seen from Figure 22, compared with the traditional sensitivity encoding reconstruction method, in this embodiment All the reconstruction methods can obtain full-field magnetic resonance images using wave controllable aliasing coding sampling trajectory mode in the convolution field of view scanning scene, and can well remove center artifacts and edge artifacts, and the quality of the reconstructed image is good.

实施例三Embodiment Three

参照图23，本实施例提供了一种卷褶视野磁共振图像的重建***，所述重建***包括获取模块100、全视野线圈敏感度图获取模块101、重建模块102。Referring to FIG. 23 , this embodiment provides a reconstruction system for a magnetic resonance image of a convoluted field of view. The reconstruction system includes an acquisition module 100 , a full-field coil sensitivity map acquisition module 101 , and a reconstruction module 102 .

获取模块100用于获取获取目标对象在第一脉冲序列激发下的卷褶视野欠采样数据、目标对象在第二脉冲序列激发下的全视野自校准采样数据。全视野线圈敏感度图获取模块101用于基于全视野自校准采样数据计算全视野线圈敏感度图，重建模块102用于根据卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像。The acquisition module 100 is configured to acquire under-sampled data of the convoluted field of view of the target object under the excitation of the first pulse sequence, and self-calibration sampling data of the full field of view of the target object under the excitation of the second pulse sequence. The full field of view coil sensitivity map acquisition module 101 is used to calculate the full field of view coil sensitivity map based on the full field of view self-calibration sampling data, and the reconstruction module 102 is used to perform image reconstruction according to the folded field of view undersampling data and the full field of view coil sensitivity map to obtain Full field magnetic resonance image.

实施例四Embodiment Four

参照图24，本实施例提供的卷褶视野磁共振图像的重建***在实施例三中的重建***的基础上增加了全视野点扩散函数获取模块103，即本实施例中的重建***包括获取模块100、全视野线圈敏感度图获取模块101、重建模块102、全视野点扩散函数获取模块103。Referring to FIG. 24 , the reconstruction system of the magnetic resonance image of the convoluted field of view provided in this embodiment adds a full field of view point spread function acquisition module 103 on the basis of the reconstruction system in the third embodiment, that is, the reconstruction system in this embodiment includes acquisition A module 100 , a full field of view coil sensitivity map acquisition module 101 , a reconstruction module 102 , and a full field of view point spread function acquisition module 103 .

获取模块100用于获取获取目标对象在第一脉冲序列激发下的卷褶视野欠采样数据、目标对象的全视野二维全采样数据以及目标对象在第二脉冲序列激发下的全视野自校准采样数据。全视野线圈敏感度图获取模块101用于基于全视野自校准采样数据计算全视野线圈敏感度图。全视野点扩散函数获取模块103用于根据目标对象的全视野二维全采样数据获得全视野点扩散函数，重建模块102用于根据卷褶视野欠采样数据、全视野线圈敏感度图、全视野点扩散函数进行图像重建，获得全视野磁共振图像。The acquiring module 100 is used to acquire under-sampling data of the convoluted field of view of the target object under the excitation of the first pulse sequence, full-field two-dimensional full-sampling data of the target object and self-calibration sampling of the full field of view of the target object under the excitation of the second pulse sequence. data. The full field of view coil sensitivity map acquisition module 101 is used to calculate the full field of view coil sensitivity map based on the full field of view self-calibration sampling data. The full field of view point spread function acquisition module 103 is used to obtain the full field of view point spread function according to the full field of view two-dimensional full sampling data of the target object, and the reconstruction module 102 is used to obtain the full field of view point spread function according to the folded field of view undersampling data, the full field of view coil sensitivity map, the full field of view The point spread function is used for image reconstruction to obtain full-field magnetic resonance images.

实施例五Embodiment five

参照图25，本实施例提供了一种计算机设备，包括处理器200、存储器201以及网络接口202，存储器201上存储有计算机程序，处理器200执行计算机程序以实现如实施例一～二所述的重建方法。Referring to FIG. 25, this embodiment provides a computer device, including a processor 200, a memory 201, and a network interface 202. A computer program is stored in the memory 201, and the processor 200 executes the computer program to realize the reconstruction method.

存储器201可以包括高速随机存取存储器(Random Access Memory，RAM)，也可能还包括非不稳定的存储器(non-volatile memory)，例如至少一个磁盘存储器。The memory 201 may include a high-speed random access memory (Random Access Memory, RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

处理器200可以是一种集成电路芯片，具有信号的处理能力。在实现过程中，实施例一～二所述的重建方法的各步骤可以通过处理器200中的硬件的集成逻辑电路或者软件形式的指令完成。处理器200也可以是通用处理器，包括中央处理器(Central Processing Unit，CPU)、网络处理器(Network Processor，NP)等，还可以是数字信号处理器(DSP)、专用集成电路(ASIC)、现成可编程门阵列(FPGA)或者其它可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。The processor 200 may be an integrated circuit chip and has a signal processing capability. During implementation, each step of the reconstruction method described in Embodiments 1 to 2 may be completed by an integrated logic circuit of hardware in the processor 200 or instructions in the form of software. The processor 200 can also be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc., and can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC) , off-the-shelf programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

存储器201用于存储计算机程序，处理器200在接收到执行指令后，执行该计算机程序以实现如实施例一～二所述的重建方法。The memory 201 is used to store a computer program, and the processor 200 executes the computer program after receiving an execution instruction to implement the reconstruction method described in Embodiments 1-2.

本实施例还提供了一种计算机存储介质，计算机存储介质中存储有计算机程序，处理器200用于读取并执行计算机存储介质中存储的计算机程序，以实现如实施例一～二所述的重建方法。This embodiment also provides a computer storage medium, in which a computer program is stored, and the processor 200 is used to read and execute the computer program stored in the computer storage medium, so as to realize the rebuild method.

在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。所述计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行所述计算机程序指令时，全部或部分地产生按照本发明实施例所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在计算机存储介质中，或者从一个计算机存储介质向另一个计算机存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线(DSL))或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘(solid state disk，SSD))等。In the above embodiments, all or part of them may be implemented by software, hardware, firmware or any combination thereof. When implemented using software, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions according to the embodiments of the present invention will be generated in whole or in part. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in or transmitted from one computer storage medium to another, for example, from a website, computer, server, or data center via a wired (e.g., coaxial Cable, optical fiber, digital subscriber line (DSL)) or wireless (eg, infrared, wireless, microwave, etc.) to another website site, computer, server, or data center. The computer storage medium may be any available medium that can be accessed by a computer, or a data storage device such as a server or a data center integrated with one or more available media. The available medium may be a magnetic medium (such as a floppy disk, a hard disk, or a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (solid state disk, SSD)), etc.

本发明实施例是参照根据本发明实施例的方法、装置、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。Embodiments of the present invention are described with reference to flowcharts and/or block diagrams of methods, apparatuses, and computer program products according to embodiments of the present invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

以上所述仅是本申请的具体实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本申请原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本申请的保护范围。The above description is only the specific implementation of the present application. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present application, some improvements and modifications can also be made. It should be regarded as the protection scope of this application.

Claims

一种卷褶视野磁共振图像的重建方法，其中，所述重建方法包括：A method for reconstructing a magnetic resonance image of a convoluted field of view, wherein the reconstruction method includes:

获取目标对象在第一脉冲序列激发下的卷褶视野欠采样数据；Obtain undersampling data of the target object under the excitation of the first pulse sequence;

获取目标对象在第二脉冲序列激发下的全视野自校准采样数据；Acquiring the full field of view self-calibration sampling data of the target object under the excitation of the second pulse sequence;

基于所述全视野自校准采样数据计算全视野线圈敏感度图；calculating a full-field coil sensitivity map based on the full-field self-calibration sampling data;

根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像。Image reconstruction is performed according to the undersampled data of the convoluted field of view and the sensitivity map of the full field of view to obtain a full field of view magnetic resonance image.
根据权利要求1所述的重建方法，其中，若所述卷褶视野欠采样数据为采用笛卡尔采样轨迹模式获得的欠采样数据，所述第一脉冲序列和所述第二脉冲序列相同。The reconstruction method according to claim 1, wherein, if the convoluted field of view under-sampled data is under-sampled data obtained by adopting a Cartesian sampling trajectory mode, the first pulse sequence and the second pulse sequence are the same.
根据权利要求2所述的重建方法，其中，所述根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得磁共振图像，包括：The reconstruction method according to claim 2, wherein the image reconstruction is performed according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map to obtain a magnetic resonance image, comprising:

将所述全视野线圈敏感度图分解成第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图；Decomposing the full field of view coil sensitivity map into a first convoluted field of view coil sensitivity map and a second convoluted field of view coil sensitivity map;

根据所述卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图建立优化模型；Establishing an optimization model according to the undersampled data of the pleat field of view, the sensitivity map of the first pleat field of view coil, and the sensitivity map of the second pleat field of view coil;

求解所述优化模型的最小值，获得两个卷褶视野磁共振图像；Solving the minimum value of the optimization model to obtain two magnetic resonance images of the convoluted field of view;

将所述两个卷褶视野磁共振图像进行拼接获得全视野磁共振图像。The two folded field of view magnetic resonance images are spliced to obtain a full field of view magnetic resonance image.
根据权利要求1所述的重建方法，其中，若所述卷褶视野欠采样数据为采用波浪可控混叠编码采样轨迹模式获得的欠采样数据，所述第一脉冲序列是由所述第二脉冲序列增加正弦梯度场获得，在根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像之前，所述重建方法还包括：The reconstruction method according to claim 1, wherein, if the undersampled data of the convoluted field of view is the undersampled data obtained by adopting the waveform controllable aliasing coding sampling trajectory mode, the first pulse sequence is obtained by the second The pulse sequence is obtained by adding a sinusoidal gradient field. Before performing image reconstruction according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, and obtaining a full field of view magnetic resonance image, the reconstruction method further includes:

根据目标对象的全视野二维全采样数据获得全视野点扩散函数；Obtain the full-view point spread function according to the full-view two-dimensional full-sampling data of the target object;

相应的，根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像具体为：Correspondingly, image reconstruction is performed according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, and the full field of view magnetic resonance image is specifically obtained as follows:

根据所述卷褶视野欠采样数据、全视野线圈敏感度图、全视野点扩散函数进行图像重建，获得全视野磁共振图像。Image reconstruction is performed according to the undersampled data of the convoluted field of view, the full field of view coil sensitivity map, and the full field of view point spread function, and a full field of view magnetic resonance image is obtained.
根据权利要求4所述的重建方法，其中，所述根据目标对象的全视野二维全采样数据获得全视野点扩散函数，包括：The reconstruction method according to claim 4, wherein said obtaining the full-view point spread function according to the full-view two-dimensional full sampling data of the target object comprises:

获取目标对象在第三脉冲序列激发下的第一全视野二维全采样数据；Acquiring the first full field of view two-dimensional full sampling data of the target object under the excitation of the third pulse sequence;

获取目标对象在第四脉冲序列激发下的第二全视野二维全采样数据，所述第四脉冲序列是由所述第三脉冲序列增加正弦梯度场获得；Acquiring the second full-field two-dimensional full sampling data of the target object excited by the fourth pulse sequence, the fourth pulse sequence is obtained by adding a sinusoidal gradient field to the third pulse sequence;

将所述第二全视野二维全采样数据除以所述第一全视野二维全采样数据得到全视野点扩散函数。dividing the second full-view two-dimensional full-sampling data by the first full-view two-dimensional full-sampling data to obtain a full-view point spread function.
根据权利要求5所述的重建方法，其中，所述将所述第二全视野二维全采样数据除以所述第一全视野二维全采样数据得到全视野点扩散函数，包括：The reconstruction method according to claim 5, wherein said dividing said second full-view two-dimensional full-sampling data by said first full-view two-dimensional full-sampling data to obtain a full-view point spread function comprises:

将所述第二全视野二维全采样数据除以所述第一全视野二维全采样数据得到初始点扩散函数；dividing the second full-field two-dimensional full-sampling data by the first full-field two-dimensional full-sampling data to obtain an initial point spread function;

将所述初始点扩散函数在K空间沿着频率编码方向进行线性拟合获得全视野点扩散函数。The initial point spread function is linearly fitted along the frequency encoding direction in K space to obtain a point spread function of the whole field of view.
根据权利要求4所述的重建方法，其中，所述根据所述卷褶视野欠采样数据、全视野线圈敏感度图、全视野点扩散函数进行图像重建，获得全视野磁共振图像，包括：The reconstruction method according to claim 4, wherein the image reconstruction is performed according to the undersampled data of the convoluted field of view, the full field of view coil sensitivity map, and the full field of view point spread function to obtain a full field of view magnetic resonance image, comprising:

将所述全视野线圈敏感度图分解成第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图；Decomposing the full field of view coil sensitivity map into a first convoluted field of view coil sensitivity map and a second convoluted field of view coil sensitivity map;

将所述全视野点扩散函数分解成第一卷褶视野点扩散函数、第二卷褶视野点扩散函数；Decomposing the full view point spread function into a first convoluted view point spread function and a second convoluted view point spread function;

根据所述卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图、第一卷褶视野点扩散函数、第二卷褶视野点扩散函数建立优化模型；An optimization model is established according to the undersampled data of the pleat field of view, the coil sensitivity map of the first pleat field of view, the coil sensitivity map of the second pleat field of view, the point spread function of the first pleat field of view, and the point spread function of the second pleat field of view ;

求解所述优化模型的最小值，获得两个卷褶视野磁共振图像；Solving the minimum value of the optimization model to obtain two magnetic resonance images of the convoluted field of view;

将所述两个卷褶视野磁共振图像进行拼接获得全视野磁共振图像。The two folded field of view magnetic resonance images are spliced to obtain a full field of view magnetic resonance image.
根据权利要求1所述的重建方法，其中，所述基于所述全视野自校准采样数据计算全视野线圈敏感度图，包括：The reconstruction method according to claim 1, wherein said calculating a full-field coil sensitivity map based on said full-field self-calibration sampling data comprises:

获取所述全视野自校准采样数据的特征值；Obtaining the eigenvalues of the full field of view self-calibration sampling data;

求解所述特征值中最大的特征值对应的特征向量并将所述特征向量作为全视野线圈敏感度图。Solving the eigenvector corresponding to the largest eigenvalue among the eigenvalues and using the eigenvector as a sensitivity map of the full field of view coil.
根据权利要求2所述的重建方法，其中，所述基于所述全视野自校准采样数据计算全视野线圈敏感度图，包括：The reconstruction method according to claim 2, wherein said calculating a full-field coil sensitivity map based on said full-field self-calibration sampling data comprises:

获取所述全视野自校准采样数据的特征值；Obtaining the eigenvalues of the full field of view self-calibration sampling data;

求解所述特征值中最大的特征值对应的特征向量并将所述特征向量作为全视野线圈敏感度图。Solving the eigenvector corresponding to the largest eigenvalue among the eigenvalues and using the eigenvector as a sensitivity map of the full field of view coil.
根据权利要求3所述的重建方法，其中，所述基于所述全视野自校准采样数据计算全视野线圈敏感度图，包括：The reconstruction method according to claim 3, wherein said calculating a full-field coil sensitivity map based on said full-field self-calibration sampling data comprises:

获取所述全视野自校准采样数据的特征值；Obtaining the eigenvalues of the full field of view self-calibration sampling data;

求解所述特征值中最大的特征值对应的特征向量并将所述特征向量作为全视野线圈敏感度图。Solving the eigenvector corresponding to the largest eigenvalue among the eigenvalues and using the eigenvector as a sensitivity map of the full field of view coil.
根据权利要求4所述的重建方法，其中，所述基于所述全视野自校准采样数据计算全视野线圈敏感度图，包括：The reconstruction method according to claim 4, wherein said calculating a full-field coil sensitivity map based on said full-field self-calibration sampling data comprises:

获取所述全视野自校准采样数据的特征值；Obtaining the eigenvalues of the full field of view self-calibration sampling data;

求解所述特征值中最大的特征值对应的特征向量并将所述特征向量作为全视野线圈敏感度图。Solving the eigenvector corresponding to the largest eigenvalue among the eigenvalues and using the eigenvector as a sensitivity map of the full field of view coil.
根据权利要求5所述的重建方法，其中，所述基于所述全视野自校准采样数据计算全视野线圈敏感度图，包括：The reconstruction method according to claim 5, wherein said calculating a full-field coil sensitivity map based on said full-field self-calibration sampling data comprises:

获取所述全视野自校准采样数据的特征值；Obtaining the eigenvalues of the full field of view self-calibration sampling data;

求解所述特征值中最大的特征值对应的特征向量并将所述特征向量作为全视野线圈敏感度图。Solving the eigenvector corresponding to the largest eigenvalue among the eigenvalues and using the eigenvector as a sensitivity map of the full field of view coil.
根据权利要求6所述的重建方法，其中，所述基于所述全视野自校准采样数据计算全视野线圈敏感度图，包括：The reconstruction method according to claim 6, wherein said calculating a full-field coil sensitivity map based on said full-field self-calibration sampling data comprises:

获取所述全视野自校准采样数据的特征值；Obtaining the eigenvalues of the full field of view self-calibration sampling data;

求解所述特征值中最大的特征值对应的特征向量并将所述特征向量作为全视野线圈敏感度图。Solving the eigenvector corresponding to the largest eigenvalue among the eigenvalues and using the eigenvector as a sensitivity map of the full field of view coil.
根据权利要求7所述的重建方法，其中，所述基于所述全视野自校准采样数据计算全视野线圈敏感度图，包括：The reconstruction method according to claim 7, wherein said calculating a full-field coil sensitivity map based on said full-field self-calibration sampling data comprises:

获取所述全视野自校准采样数据的特征值；Obtaining the eigenvalues of the full field of view self-calibration sampling data;

求解所述特征值中最大的特征值对应的特征向量并将所述特征向量作为全视野线圈敏感度图。Solving the eigenvector corresponding to the largest eigenvalue among the eigenvalues and using the eigenvector as a sensitivity map of the full field of view coil.
一种计算机设备，包括存储器、处理器及存储在存储器上的计算机程序，其中，所述处理器执行所述计算机程序以实现卷褶视野磁共振图像的重建方法，其中，所述重建方法包括：A computer device, comprising a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement a method for reconstructing a magnetic resonance image of a convoluted field of view, wherein the reconstruction method includes:

获取目标对象在第一脉冲序列激发下的卷褶视野欠采样数据；Obtain undersampling data of the target object under the excitation of the first pulse sequence;

获取目标对象在第二脉冲序列激发下的全视野自校准采样数据；Acquiring the full field of view self-calibration sampling data of the target object under the excitation of the second pulse sequence;

基于所述全视野自校准采样数据计算全视野线圈敏感度图；calculating a full-field coil sensitivity map based on the full-field self-calibration sampling data;

根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像。Image reconstruction is performed according to the undersampled data of the convoluted field of view and the sensitivity map of the full field of view to obtain a full field of view magnetic resonance image.
根据权利要求15所述的计算机设备，其中，若所述卷褶视野欠采样数据为采用笛卡尔采样轨迹模式获得的欠采样数据，所述第一脉冲序列和所述第二脉冲序列相同。The computer device according to claim 15, wherein if the convoluted view undersampled data is undersampled data obtained by adopting a Cartesian sampling trajectory mode, the first pulse sequence and the second pulse sequence are the same.
根据权利要求16所述的计算机设备，其中，所述根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得磁共振图像，包括：The computer device according to claim 16, wherein the performing image reconstruction according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map to obtain a magnetic resonance image comprises:

将所述全视野线圈敏感度图分解成第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图；Decomposing the full field of view coil sensitivity map into a first convoluted field of view coil sensitivity map and a second convoluted field of view coil sensitivity map;

根据所述卷褶视野欠采样数据、第一卷褶视野线圈敏感度图、第二卷褶视野线圈敏感度图建立优化模型；Establishing an optimization model according to the undersampled data of the pleat field of view, the sensitivity map of the first pleat field of view coil, and the sensitivity map of the second pleat field of view coil;

求解所述优化模型的最小值，获得两个卷褶视野磁共振图像；Solving the minimum value of the optimization model to obtain two magnetic resonance images of the convoluted field of view;

将所述两个卷褶视野磁共振图像进行拼接获得全视野磁共振图像。The two folded field of view magnetic resonance images are spliced to obtain a full field of view magnetic resonance image.
根据权利要求15所述的计算机设备，其中，若所述卷褶视野欠采样数据为采用波浪可控混叠编码采样轨迹模式获得的欠采样数据，所述第一脉冲序列是由所述第二脉冲序列增加正弦梯度场获得，在根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像之前，所述重建方法还包括：The computer device according to claim 15, wherein if the under-sampled data of the convolution field of view is the under-sampled data obtained by adopting the waveform controllable aliasing coding sampling trace mode, the first pulse sequence is obtained by the second The pulse sequence is obtained by adding a sinusoidal gradient field. Before performing image reconstruction according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, and obtaining a full field of view magnetic resonance image, the reconstruction method further includes:

根据目标对象的全视野二维全采样数据获得全视野点扩散函数；Obtain the full-view point spread function according to the full-view two-dimensional full-sampling data of the target object;

相应的，根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像具体为：Correspondingly, image reconstruction is performed according to the undersampled data of the convoluted field of view and the full field of view coil sensitivity map, and the full field of view magnetic resonance image is specifically obtained as follows:

根据所述卷褶视野欠采样数据、全视野线圈敏感度图、全视野点扩散函数进行图像重建，获得全视野磁共振图像。Image reconstruction is performed according to the undersampled data of the convoluted field of view, the full field of view coil sensitivity map, and the full field of view point spread function, and a full field of view magnetic resonance image is obtained.
根据权利要求18所述的计算机设备，其中，所述根据目标对象的全视野二维全采样数据获得全视野点扩散函数，包括：The computer device according to claim 18, wherein said obtaining the full-view point spread function according to the full-view two-dimensional full sampling data of the target object comprises:

获取目标对象在第三脉冲序列激发下的第一全视野二维全采样数据；Acquiring the first full field of view two-dimensional full sampling data of the target object under the excitation of the third pulse sequence;

获取目标对象在第四脉冲序列激发下的第二全视野二维全采样数据，所述第四脉冲序列是由所述第三脉冲序列增加正弦梯度场获得；Acquiring the second full-field two-dimensional full sampling data of the target object excited by the fourth pulse sequence, the fourth pulse sequence is obtained by adding a sinusoidal gradient field to the third pulse sequence;

将所述第二全视野二维全采样数据除以所述第一全视野二维全采样数据得到全视野点扩散函数。dividing the second full-view two-dimensional full-sampling data by the first full-view two-dimensional full-sampling data to obtain a full-view point spread function.
一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机指令，其中，所述计算机指令被处理器执行时实现卷褶视野磁共振图像的重建方法，其中，所述重建方法包括：A computer-readable storage medium, where computer instructions are stored on the computer-readable storage medium, wherein when the computer instructions are executed by a processor, a method for reconstructing a magnetic resonance image of a convoluted field of view is implemented, wherein the reconstruction method includes :

获取目标对象在第一脉冲序列激发下的卷褶视野欠采样数据；Obtain undersampling data of the target object under the excitation of the first pulse sequence;

获取目标对象在第二脉冲序列激发下的全视野自校准采样数据；Acquiring the full field of view self-calibration sampling data of the target object under the excitation of the second pulse sequence;

基于所述全视野自校准采样数据计算全视野线圈敏感度图；calculating a full-field coil sensitivity map based on the full-field self-calibration sampling data;

根据所述卷褶视野欠采样数据、全视野线圈敏感度图进行图像重建，获得全视野磁共振图像。Image reconstruction is performed according to the undersampled data of the convoluted field of view and the sensitivity map of the full field of view to obtain a full field of view magnetic resonance image.