Coil sensitivity spectrum optimization method and device, equipment, storage medium and imaging method

Abstract

The invention relates to the technical field of magnetic resonance imaging, and discloses a coil sensitivity spectrum optimization method, device and equipment, a storage medium and an imaging method. The method comprises the following steps: firstly, acquiring first K space data which is acquired through general coil acquisition; and acquiring second K space data, wherein the second K space data is acquired through the phase control array coil. Then, a coil sensitivity spectrum for a first resolution and a coil sensitivity spectrum for a second resolution are determined based on the first K-space data and the second K-space data, where the first resolution is less than the second resolution. Finally, a fused sensitivity spectrum is determined based on the coil sensitivity spectrum for the first resolution and the coil sensitivity spectrum for the second resolution. By acquiring the high-resolution and low-resolution fused sensitivity spectrum, residual artifacts caused by insufficient accuracy of the coil sensitivity spectrum are reduced, and the problem that the coil sensitivity spectrum is not matched with the position of the to-be-reconstructed image due to breathing and image deformation can be solved.

Description

Technical Field

[0001] The present invention relates to the field of magnetic resonance imaging technology, and in particular to a coil sensitivity spectrum optimization method, device, equipment, storage medium and imaging method. Background Art

[0002] In order to improve the acceleration efficiency of magnetic resonance imaging (MRI), parallel imaging technology is used. This technology uses the sensitivity information of multiple receiving coils to restore the uncollected signal part, thereby accelerating the imaging process.

[0003] In the related art, the same imaging sequence is used to collect data twice through a multi-phased array coil and a body coil. Then, the images reconstructed from the two sets of data are ratio-calculated to obtain the coil sensitivity spectrum. However, the robustness of the coil sensitivity spectrum needs to be improved. Summary of the invention

[0004] The embodiments of this specification are intended to solve at least one of the technical problems in the related art to a certain extent. To this end, the embodiments of this specification propose a coil sensitivity spectrum optimization method, device, equipment, storage medium and imaging method.

[0005] The present specification provides a coil sensitivity spectrum optimization method, the method comprising:

[0006] Acquire first K-space data, where the first K-space data is acquired through a body coil;

[0007] Acquire second K-space data, where the second K-space data is acquired through phased array coil acquisition;

[0008] Determine a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution based on the first K-space data and the second K-space data, wherein the first resolution is smaller than the second resolution;

[0009] A fused sensitivity spectrum is determined based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution.

[0010] In one embodiment, the second K space data includes third K space data, the third K space is consistent with the first K space, and determining the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution based on the first K space data and the second K space data includes:

[0011] determining a coil sensitivity spectrum of the first resolution based on the third K-space data and the first K-space data;

[0012] A coil sensitivity spectrum at the second resolution is determined based on the second K-space data and the coil sensitivity spectrum at the first resolution.

[0013] In one embodiment, determining the coil sensitivity spectrum of the second resolution based on the second K-space data and the coil sensitivity spectrum of the first resolution includes:

[0014] Perform channel merging on the second K-space data based on the coil sensitivity spectrum of the first resolution to obtain global data;

[0015] A coil sensitivity spectrum of the second resolution is determined based on the second K-space data and the global data.

[0016] In one embodiment, the first K space is consistent with the second K space, the second K space data includes third K space data, the first K space data includes fourth K space data, the third K space is consistent with the fourth K space, and determining the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution based on the first K space data and the second K space data includes:

[0017] determining a coil sensitivity spectrum of the first resolution based on the third K-space data and the fourth K-space data;

[0018] A coil sensitivity spectrum of the second resolution is determined based on the first k-space data and the second k-space data.

[0019] In one embodiment, determining a fused sensitivity spectrum based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution includes:

[0020] The coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution are spliced ​​to obtain the fused sensitivity spectrum.

[0021] In one embodiment, the matrix sizes of the first K-space, the third K-space, and the fourth K-space are negatively correlated with the degree of motion of the target object to be scanned.

[0022] The present specification provides a magnetic resonance imaging method, comprising:

[0023] Acquire the downsampled K-space data of the target object;

[0024] Based on the fused sensitivity spectrum obtained by the coil sensitivity spectrum optimization method described in the above embodiment, compressed sensing reconstruction is performed on the downsampled K-space data to obtain a magnetic resonance image of the target object.

[0025] The embodiments of this specification provide a coil sensitivity spectrum optimization device, the device comprising:

[0026] A body coil data acquisition module, used to acquire first K-space data, wherein the first K-space data is acquired through body coil acquisition;

[0027] A phased array coil data acquisition module, used to acquire second K space data, where the second K space data is acquired through phased array coil acquisition;

[0028] a coil sensitivity spectrum determination module, configured to determine a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution based on the first K-space data and the second K-space data, wherein the first resolution is smaller than the second resolution;

[0029] The fused sensitivity spectrum determining module is used to determine a fused sensitivity spectrum based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution.

[0030] An embodiment of the present specification provides a medical imaging device, which includes: a memory, and one or more processors communicatively connected to the memory; the memory stores instructions executable by the one or more processors, and the instructions are executed by the one or more processors to enable the one or more processors to implement the steps of the method described in any of the above embodiments.

[0031] An embodiment of the present specification provides a computer device, which includes: a memory, and one or more processors communicatively connected to the memory; the memory stores instructions executable by the one or more processors, and the instructions are executed by the one or more processors to enable the one or more processors to implement the steps of the method described in any of the above embodiments.

[0032] The embodiments of this specification provide a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method described in any of the above embodiments are implemented.

[0033] An embodiment of the present specification provides a computer program product, wherein the computer program product includes instructions, and when the instructions are executed by a processor of a computer device, the computer device is enabled to perform the steps of the method described in any one of the above embodiments.

[0034] In the above-mentioned implementation of the specification, first, the first K-space data is obtained, and the first K-space data is obtained by collecting the general coil; the second K-space data is obtained by collecting the phased array coil. Then, based on the first K-space data and the second K-space data, the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution are determined, wherein the first resolution is less than the second resolution. Finally, based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution, a fused sensitivity spectrum is determined. By obtaining a fused sensitivity spectrum of high and low resolution fusion, the residual artifacts caused by the insufficient accuracy of the coil sensitivity spectrum are reduced, and the problem of mismatch between the coil sensitivity spectrum and the position of the image to be reconstructed caused by breathing and image deformation can be dealt with, thereby enhancing the robustness of reconstructing images using sensitivity spectra, reducing artifacts and black hole phenomena, and thus ensuring the quality and stability of image reconstruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1a A schematic diagram of a coil sensitivity spectrum corresponding to a 28-channel coil provided in an embodiment of this specification;

[0036] Figure 1b A schematic diagram of a CSM reconstruction result provided in an embodiment of this specification;

[0037] Figure 1c A schematic diagram of a coil sensitivity spectrum image provided in an embodiment of this specification;

[0038] Figure 2a A schematic diagram of a process flow of a coil sensitivity spectrum optimization method provided in an embodiment of this specification;

[0039] Figure 2b A schematic diagram of a black hole artifact when the breath holding is not aligned and after the black hole is eliminated provided in an embodiment of this specification;

[0040] Figure 2c A schematic diagram of residual artifacts of EPI distortion and artifact elimination provided in an embodiment of this specification;

[0041] Figure 3 A schematic diagram of a fusion sensitivity spectrum provided for an embodiment of this specification;

[0042] Figure 4a A schematic diagram of a process for determining a sensitivity spectrum provided in an embodiment of this specification;

[0043] Figure 4b A schematic diagram of a K-space acquisition area provided in an embodiment of this specification;

[0044] Figure 4c A schematic diagram of a K-space acquisition area provided in an embodiment of this specification;

[0045] Figure 5 A schematic diagram of a flow chart of determining a coil sensitivity spectrum of a second resolution provided in an embodiment of this specification;

[0046] Figure 6 A schematic diagram of a process for determining a coil sensitivity spectrum provided in an embodiment of this specification;

[0047] Figure 7 A schematic diagram of a general coil image provided for an embodiment of the present specification;

[0048] Figure 8 A schematic diagram of a coil sensitivity spectrum optimization device provided in an embodiment of this specification;

[0049] Fig. 9 An internal structural diagram of a computer device provided for an embodiment of this specification. DETAILED DESCRIPTION

[0050] Embodiments of the present invention are described in detail below, examples of which 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 invention, and should not be construed as limiting the present invention.

[0051] Magnetic resonance imaging (MRI) is a multi-parameter, multi-contrast imaging technology, widely used as one of the main imaging methods in medical imaging. It provides disease detection and diagnosis information by reflecting various characteristics of tissues such as T1, T2 relaxation time and proton density. The basic principle of magnetic resonance imaging is to use the magnetic resonance phenomenon to excite hydrogen protons in the human body through radio frequency excitation, use gradient fields for position encoding, then use receiving coils to receive electromagnetic signals with position information, and finally use Fourier transform to reconstruct the image.

[0052] However, MRI is slower than other medical imaging technologies (such as CT and X-ray). In related technologies, the acceleration methods used mainly include parallel imaging, compressed sensing and half-Fourier imaging.

[0053] Parallel imaging is achieved by using the sensitivity information of multiple coils to restore the data of the uncollected part, thereby achieving acceleration. The acceleration multiple is usually determined by the number of channels of the coil. There are two main methods of parallel imaging: one is SENSE (Sensitivity Encoding) based on the image domain, and the other is GRAPPA (GeneRalized Autocalibrating Partially Parallel Acquisitions) based on the K-space domain. In general, parallel imaging speeds up the speed of magnetic resonance scanning.

[0054] In parallel imaging, SENSE, as a parallel acceleration method in the image domain, has a higher signal-to-noise ratio (SNR) and faster reconstruction speed. However, the SENSE method is highly dependent on the accuracy of the coil sensitivity spectrum during the reconstruction process. Errors in the coil sensitivity spectrum often lead to the appearance of residual artifacts.

[0055] In the related art, the acquisition process of the coil sensitivity spectrum is usually as follows: In the case of the same sequence, a multi-channel phased array coil (Array Coil) is used to collect data to obtain the corresponding collected data Array. Then, a large body coil (QBC) is used to collect data to obtain the corresponding collected data QBC. Next, the Array data and the QBC data are reconstructed to remove the structural information and contrast of the image itself, and the coil sensitivity spectrum CSM (Coil Sensitivity Map) is obtained by dividing the reconstructed image of the Array data and the QBC data, that is, For example, see Figure 1a , Figure 1a The coil sensitivity spectrum corresponding to the 28-channel coil is shown.

[0056] Since the sensitivity spectrum of the same coil is fixed, it is usually only necessary to acquire the sensitivity spectrum once for one part and then use it for accelerated reconstruction in different clinical protocols. The GRE3D sequence is usually selected as the preferred option for obtaining the sensitivity spectrum due to its faster acquisition speed. The acquisition of the coil sensitivity spectrum as a pre-scan sequence requires the scanning time to be as short as possible, especially when scanning the abdomen, which is more critical because the patient needs to hold his breath. However, the scanning resolution of the coil sensitivity spectrum directly affects its accuracy. Improving the resolution can usually reduce residual artifacts, thereby improving the quality of the reconstructed image. For example, please refer to Figure 1b , Figure 1b The CSM reconstruction results at different resolutions are shown. Figure 1b The left side is the low-resolution CSM reconstruction result. Figure 1bOn the right is a high-resolution CSM reconstruction. Although higher resolution can improve image quality, the consistency requirements for the deconvolved image also increase, especially in the case of respiratory mismatch or deformation. In this case, higher resolution may lead to a decrease in image robustness. For example, see Figure 1c , Figure 1c This phenomenon is further demonstrated by Figure 1c The left side shows the image of the reconstruction result. Figure 1c On the right is the corresponding coil sensitivity spectrum image.

[0057] In the related art, the methods for optimizing the coil sensitivity spectrum are usually based on the optimization of the reconstruction process. These methods optimize the accuracy of the sensitivity spectrum while performing image reconstruction. Two common methods include the MAF SENSE method combined with SENSE reconstruction, and the Sparse Blip method combined with compressed sensing reconstruction. These two methods can reduce the errors caused by the coil sensitivity spectrum to a certain extent. However, the methods in the related art are closely integrated with specific reconstruction algorithms. For example, MAF SENSE is combined with SENSE reconstruction, while the Sparse Blip method is combined with compressed sensing reconstruction, which limits their versatility. In addition, the methods in the related art usually reduce the reconstruction speed, resulting in longer imaging time, and can only improve the accuracy of the coil sensitivity spectrum within a certain range.

[0058] Based on this, the embodiment of the present specification provides a method for optimizing the coil sensitivity spectrum. First, the first K-space data is obtained, and the first K-space data is obtained by collecting the general coil, and the second K-space data is obtained, and the second K-space data is obtained by collecting the phased array coil. Then, based on the first K-space data and the second K-space data, the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution are determined, wherein the first resolution is less than the second resolution. Finally, based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution, a fused sensitivity spectrum is determined. By obtaining a fused sensitivity spectrum of high and low resolution fusion, the residual artifacts caused by the insufficient accuracy of the coil sensitivity spectrum are reduced, and the problem of mismatch between the coil sensitivity spectrum and the position of the image to be reconstructed caused by breathing and image deformation can be dealt with, thereby enhancing the robustness of reconstructing the image using the sensitivity spectrum, reducing artifacts and black hole phenomena, and thus ensuring the quality and stability of image reconstruction.

[0059] This specification provides a coil sensitivity spectrum optimization method, please refer to Figure 2a , the coil sensitivity spectrum optimization method may include the following steps:

[0060] S210: Acquire first K-space data.

[0061] S220: Acquire second K-space data.

[0062] The first K-space data is acquired through a body coil, and the second K-space data is acquired through a phased array coil.

[0063] Specifically, during the magnetic resonance scanning process, the resolution of the acquired data is closely related to the size of the K-space matrix. The first K-space is acquired using the body coil to acquire the first K-space data associated with the first K-space. The second K-space is acquired using the phased array coil to acquire the second K-space data associated with the second K-space. There are multiple second K-spaces, each of which corresponds to a channel of the phased array coil.

[0064] S230 : Determine a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution based on the first K-space data and the second K-space data.

[0065] S240: Determine a fused sensitivity spectrum based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution.

[0066] The first resolution is smaller than the second resolution.

[0067] Specifically, the coil sensitivity spectra at two resolutions are calculated using the first K-space data and the second K-space data, respectively, to obtain the coil sensitivity spectrum at the first resolution and the coil sensitivity spectrum at the second resolution. The sensitivity spectrum is a function that describes the response strength of the coil to signals of different frequencies, and represents the coil's ability to capture signals of different regions. In this way, the performance difference of the two coils at different resolutions can be evaluated. The coil sensitivity spectrum at the first resolution and the coil sensitivity spectrum at the second resolution are fused to generate a fused sensitivity spectrum that integrates high and low resolution information. The matrix size of the K-space data determines the resolution of the K-space. The smaller the matrix of the K-space data, the lower the resolution of the K-space. Since the lower the resolution of the K-space, the more obvious the volume effect of the image, the more severe the image expansion, that is, the size of the image corresponding to the low-resolution K-space is larger than the size of the image corresponding to the high-resolution K-space. The resolution of the coil sensitivity spectrum depends on the resolution of the K-space, that is, the size of the coil sensitivity spectrum at the first resolution is larger than the size of the coil sensitivity spectrum at the second resolution. The fused coil sensitivity spectrum obtained by fusing the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution can reduce the residual artifacts caused by the insufficient accuracy of the coil sensitivity spectrum, and the low-resolution part can cope with the problem of mismatch between the coil sensitivity spectrum and the position of the image to be reconstructed caused by breathing and image deformation, thereby enhancing the robustness of image reconstruction using the sensitivity spectrum and reducing artifacts and black hole phenomena.

[0068] Please note that Figure 2b , Figure 2b The right image in the middle shows the black hole artifact when the breath is not aligned. Figure 2b The image on the right side of the image is taken to get the image with the black hole artifacts eliminated, that is, Figure 2b Center left image.

[0069] See also Figure 2c , Figure 2c The right image in the middle shows the residual artifacts of the EPI distortion. Figure 2c The right image in the middle is used to obtain the image after removing the artifacts, that is, Figure 2c Center left image.

[0070] In the above embodiment, during the scanning process, first, the first K-space data is acquired, and the first K-space data is acquired by collecting the general coil; the second K-space data is acquired, and the second K-space data is acquired by collecting the phased array coil. Then, based on the first K-space data and the second K-space data, the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution are determined, wherein the first resolution is less than the second resolution. Finally, based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution, a fused sensitivity spectrum is determined. By acquiring a fused sensitivity spectrum of high and low resolution fusion, the residual artifacts caused by the insufficient accuracy of the coil sensitivity spectrum are reduced, and the problem of mismatch between the coil sensitivity spectrum and the position of the image to be reconstructed caused by breathing and image deformation can be dealt with, thereby enhancing the robustness of reconstructing images using sensitivity spectra, reducing artifacts and black hole phenomena, and thus ensuring the quality and stability of image reconstruction.

[0071] In some embodiments, determining a fused sensitivity spectrum based on a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution may include: splicing the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution to obtain a fused sensitivity spectrum.

[0072] Specifically, the coil sensitivity spectrum CSM_2 of the second resolution is placed in the middle of the image so that the coil sensitivity spectrum CSM_2 of the second resolution covers its corresponding area. Usually, the area covered by the coil sensitivity spectrum CSM_2 of the second resolution helps to improve the clarity and accuracy of the image. However, since the coil sensitivity spectrum CSM_2 of the second resolution is not enough to completely cover the entire image, especially the edge area of ​​the image. In order to supplement the area that the coil sensitivity spectrum CSM_2 of the second resolution does not cover, the coil sensitivity spectrum CSM_1 of the first resolution is used to cover it, which effectively reduces noise and maintains basic imaging quality, thereby improving robustness. Finally, the image covered with the coil sensitivity spectrum CSM_1 of the first resolution and the coil sensitivity spectrum CSM_2 of the second resolution is used as the fused sensitivity spectrum CSM_3.

[0073] For example, the volume effect may cause the size of the sensitivity spectrum of different regions to change. The coil sensitivity spectrum CSM_1 of the first resolution is larger than the coil sensitivity spectrum CSM_2 of the second resolution. The coil sensitivity spectrum CSM_1 of the first resolution and the coil sensitivity spectrum CSM_2 of the second resolution are spliced ​​to obtain a fused sensitivity spectrum CSM_3. Figure 3 , Figure 3 The fused sensitivity spectrum CSM_3 is presented and can be applied to accelerate the computation of clinical protocols.

[0074] In the above implementation, the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution are spliced ​​to obtain a fused sensitivity spectrum, thereby reducing residual artifacts caused by insufficient precision. In clinical applications, it is possible to cope with distortion or respiratory synchronization problems, enhance the robustness of image reconstruction using sensitivity spectra, reduce artifacts and black hole phenomena, and thus ensure the quality and stability of image reconstruction.

[0075] In some embodiments, see Figure 4a The second K space data includes third K space data, the third K space is consistent with the first K space, and based on the first K space data and the second K space data, a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution are determined, including:

[0076] S410 : Determine a coil sensitivity spectrum of a first resolution based on the third K-space data and the first K-space data.

[0077] S420 : Determine a coil sensitivity spectrum with a second resolution based on the second K-space data and the coil sensitivity spectrum with the first resolution.

[0078] Specifically, the second K space is larger than the first K space, the third K space is a subset of the second K space, and the third K space is consistent with the first K space. The second K space and the first K space refer to the matrix of K space data, and the consistency of the third K space and the first K space means that the matrix size and the position of the matrix in the K space are consistent. The first K space is relatively small, which can reduce the acquisition time and is suitable for obtaining relatively rough overall anatomical structure information. The first K space is acquired using a body coil to obtain the first K space data QBC_b associated with the first K space. The second K space is larger than the first K space and completely contains the third K space consistent with the first K space, thereby providing higher spatial resolution and capturing more detailed structural information. The second K space is acquired using a phased array coil to obtain the second K space data Array_r associated with the second K space. The scanned second K space data Array_r contains the third K space data Array_b. It should be noted that the matrix size of the first K space, the third K space and the fourth K space is negatively correlated with the degree of motion of the target object to be scanned. The greater the degree of motion of the target object, the smaller the matrix of the first K space and the third K space, so that the expansion of the low-resolution coil sensitivity spectrum is more severe.

[0079] In order to analyze the resolution difference between different K spaces, the third K space data Array_b and the image corresponding to the first K space data QBC_b are divided to eliminate the common background influence and obtain the coil sensitivity spectrum CSM_1 of the first resolution, that is, Next, data processing is performed using the coil sensitivity spectrum CSM_1 of the first resolution and the second K-space data Array_r to obtain a coil sensitivity spectrum CSM_2 of a second resolution greater than the first resolution.

[0080] In some embodiments, the sensitivity spectrum acquisition strategy is elliptical acquisition, see Figure 4b The phased array coil acquires a second K space 402 , the body coil acquires a first K space 404 , and the second K space 402 includes the first K space 404 .

[0081] The sensitivity spectrum acquisition strategy is conventional acquisition, see Figure 4c The phased array coil acquires a second K space 406 , the body coil acquires a first K space 408 , and the second K space 406 includes the first K space 408 .

[0082] In the above implementation, the coil sensitivity spectrum of the first resolution is determined based on the third K space data and the first K space data, and the coil sensitivity spectrum of the second resolution is determined based on the second K space data and the coil sensitivity spectrum of the first resolution, thereby providing a data basis for the subsequent determination of the fused sensitivity spectrum.

[0083] In some embodiments, see Figure 5 , determining a coil sensitivity spectrum of a second resolution based on the second K-space data and the coil sensitivity spectrum of the first resolution may include the following steps:

[0084] S510 , performing channel merging on the second K-space data based on the coil sensitivity spectrum of the first resolution to obtain global data.

[0085] S520: Determine a coil sensitivity spectrum of a second resolution according to the second K-space data and the global data.

[0086] Specifically, the coil sensitivity spectrum CSM_1 of the first resolution is used to synthesize the second K-space data Array_r to reduce the signal difference between different channels, that is, by solving SENSE=1, the signal of each receiving channel can be effectively matched in space, and the channels are merged to obtain the global data SENSE_r. Next, since the second K-space data Array_r and the global data SENSE_r can be signals corresponding to the same area, the second K-space data Array_r and the global data SENSE_r can be divided by the image corresponding to the global data SENSE_r to eliminate the common background influence, and obtain the coil sensitivity spectrum CSM_2 of the second resolution, that is, It should be noted that the solution for SENSE=1 may be obtained by using relevant technical means in the art, which will not be described in detail here.

[0087] In the above implementation, the second K-space data is channel-merged based on the coil sensitivity spectrum of the first resolution to obtain global data, and the coil sensitivity spectrum of the second resolution is determined based on the second K-space data and the global data, providing a data basis for the subsequent determination of the fused sensitivity spectrum of the low-resolution fusion.

[0088] In some embodiments, see Figure 6 , the first K space is consistent with the second K space, the second K space data includes the third K space data, the first K space data includes the fourth K space data, the third K space is consistent with the fourth K space, the third K space is a subset of the first K space, the fourth K space is a subset of the second K space, the first K space is consistent with the second K space and the third K space is consistent with the fourth K space means that the matrix size and the matrix position in the K space are consistent. Based on the first K space data and the second K space data, determining the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution includes:

[0089] S610 : Determine a coil sensitivity spectrum of a first resolution based on the third K-space data and the fourth K-space data.

[0090] S620 : Determine a coil sensitivity spectrum of a second resolution based on the first K-space data and the second K-space data.

[0091] Specifically, the third K space is consistent with the fourth K space. Therefore, the images corresponding to the third K space data and the fourth K space data are divided to eliminate the common background influence, and the coil sensitivity spectrum CSM_1 of the first resolution is obtained. Since the first K space is consistent with the second K space, the images corresponding to the first K space data and the second K space data are divided to eliminate the common background influence, and the coil sensitivity spectrum CSM_2 of the second resolution is obtained. Since the second K space data includes the third K space data and the first K space data includes the fourth K space data, the first K space and the second K space have higher resolutions than the third K space and the fourth K space, so the second resolution is greater than the first resolution. It should be noted that the matrix size of the third K space and the fourth K space is negatively correlated with the degree of motion of the target object to be scanned. The greater the degree of motion of the target object, the smaller the matrix of the third K space and the fourth K space, so the expansion of the low-resolution coil sensitivity spectrum is more severe.

[0092] In the above implementation, the coil sensitivity spectrum of the first resolution is determined based on the third K space data and the fourth K space data, and the coil sensitivity spectrum of the second resolution is determined based on the first K space data and the second K space data, providing a data basis for the subsequent determination of the fused sensitivity spectrum.

[0093] In some embodiments, the method may further include determining a general body coil image based on the first K-space data and the global data.

[0094] Specifically, the first K-space data QBC_b is data collected by the general body coil, and the global data SENSE_r can also be understood as data corresponding to a whole body coil. Therefore, the image corresponding to the first K-space data QBC_b and the global data SENSE_r is divided to obtain a general body coil image. For example, please refer to Figure 7 , Figure 7 Gross coil images are shown.

[0095] In the above implementation, a general body coil image is determined based on the first K-space data and the global data, which provides a data basis for the subsequent determination of the fused sensitivity spectrum.

[0096] An embodiment of the present specification provides a magnetic resonance imaging method, including: acquiring downsampled K-space data of a target object; performing compressed sensing reconstruction on the downsampled K-space data based on a fused sensitivity spectrum acquired by a coil sensitivity spectrum optimization method provided in an embodiment of the present specification, to acquire a magnetic resonance image of the target object.

[0097] Specifically, the downsampled K-space data of the target object can be obtained by using a parallel acquisition technology. Then, the compressed sensing model is solved based on the downsampled K-space data and the fused sensitivity spectrum to obtain the magnetic resonance image of the target object. The compressed sensing model can adopt a model in the relevant technology, which will not be described here.

[0098] This specification provides a coil sensitivity spectrum optimization device 800, see Figure 8 The coil sensitivity spectrum optimization device 800 includes: a body coil data acquisition module 810 , a phased array coil data acquisition module 820 , a coil sensitivity spectrum determination module 830 , and a fused sensitivity spectrum determination module 840 .

[0099] A body coil data acquisition module 810 is used to acquire first K-space data, where the first K-space data is acquired through body coil acquisition;

[0100] The phased array coil data acquisition module 820 is used to acquire second K space data, where the second K space data is acquired through phased array coil acquisition;

[0101] A coil sensitivity spectrum determination module 830, configured to determine a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution based on the first K-space data and the second K-space data, wherein the first resolution is smaller than the second resolution;

[0102] The fused sensitivity spectrum determining module 840 is configured to determine a fused sensitivity spectrum based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution.

[0103] For a detailed description of the coil sensitivity spectrum optimization device, reference may be made to the above description of the coil sensitivity spectrum optimization method, which will not be repeated here.

[0104] An embodiment of the present specification provides a medical imaging device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the method steps in the above embodiment when executing the computer program.

[0105] In some embodiments, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in FIG. Fig. 9As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for optimizing the coil sensitivity spectrum is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0106] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution disclosed in this specification, and does not constitute a limitation on the computer device to which the solution disclosed in this specification is applied. Specifically, the computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0107] In some embodiments, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the method steps in the above embodiments when executing the computer program.

[0108] An embodiment of the present specification provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method in any of the above embodiments are implemented.

[0109] One embodiment of the present specification provides a computer program product, which includes instructions. When the instructions are executed by a processor of a computer device, the computer device can perform the steps of the method of any of the above embodiments.

[0110] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

Claims

1. A coil sensitivity spectrum optimization method, characterized in that: The method comprises: Acquire first K-space data, where the first K-space data is acquired through a body coil; Acquire second K-space data, where the second K-space data is acquired through phased array coil acquisition; Determine a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution based on the first K-space data and the second K-space data, wherein the first resolution is smaller than the second resolution; A fused sensitivity spectrum is determined based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution.

2. The method according to claim 1, characterized in that The second K space data includes third K space data, the third K space is consistent with the first K space, and determining a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution based on the first K space data and the second K space data includes: determining a coil sensitivity spectrum of the first resolution based on the third K-space data and the first K-space data; A coil sensitivity spectrum at the second resolution is determined based on the second K-space data and the coil sensitivity spectrum at the first resolution.

3. The method according to claim 2, characterized in that The step of determining the coil sensitivity spectrum of the second resolution based on the second K-space data and the coil sensitivity spectrum of the first resolution includes: Perform channel merging on the second K-space data based on the coil sensitivity spectrum of the first resolution to obtain global data; A coil sensitivity spectrum of the second resolution is determined based on the second K-space data and the global data.

4. The method according to claim 1, characterized in that: The first K space is consistent with the second K space, the second K space data includes third K space data, the first K space data includes fourth K space data, the third K space is consistent with the fourth K space, and determining the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution based on the first K space data and the second K space data includes: determining a coil sensitivity spectrum of the first resolution based on the third K-space data and the fourth K-space data; A coil sensitivity spectrum of the second resolution is determined based on the first k-space data and the second k-space data.

5. The method according to claim 1, characterized in that The determining a fused sensitivity spectrum based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution includes: The coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution are spliced ​​to obtain the fused sensitivity spectrum.

6. The method according to claim 2 or 4, characterized in that: The matrix sizes of the first K space, the third K space, and the fourth K space are negatively correlated with the degree of motion of the target object to be scanned.

7. A magnetic resonance imaging method, characterized in that: include: Acquire the downsampled K-space data of the target object; Based on the fused sensitivity spectrum obtained by the coil sensitivity spectrum optimization method according to any one of claims 1 to 6, compressed sensing reconstruction is performed on the downsampled K-space data to obtain a magnetic resonance image of the target object.

8. A coil sensitivity spectrum optimization device, characterized in that: The device comprises: A body coil data acquisition module, used to acquire first K-space data, wherein the first K-space data is acquired through body coil acquisition; A phased array coil data acquisition module, used to acquire second K space data, where the second K space data is acquired through phased array coil acquisition; a coil sensitivity spectrum determination module, configured to determine a coil sensitivity spectrum of a first resolution and a coil sensitivity spectrum of a second resolution based on the first K-space data and the second K-space data, wherein the first resolution is smaller than the second resolution; The fused sensitivity spectrum determining module is used to determine a fused sensitivity spectrum based on the coil sensitivity spectrum of the first resolution and the coil sensitivity spectrum of the second resolution.

9. A medical imaging device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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