Magnetic resonance Z-spectrum fat quantitative imaging method, system and equipment and storage medium

Abstract

The invention discloses a magnetic resonance Z-spectrum fat quantitative imaging method, system and device and a storage medium. The method comprises the steps that a human shoulder and neck T2 weighted pressurized water image and a Z-spectrum image which are matched in spatial position are collected; binarization threshold segmentation processing is carried out on the T2 weighted pressurized water image, adipose tissue and non-adipose tissue are segmented, and an adipose distribution diagram is obtained; z-spectrum main magnetic field non-uniformity correction is carried out on the segmented adipose tissue and non-adipose tissue areas according to different Z-spectrum spectral line distribution displayed by different tissues in the Z-spectrum image; and performing multi-pool Lorentz linear fitting on the Z spectrum subjected to main magnetic field non-uniformity correction, extracting corresponding water and fat signals, and calculating the relative fat content in a unit voxel according to the relative proportion of water and fat so as to realize fat quantitative imaging. According to the Z-spectrum fat quantitative imaging method, fat quantitative imaging is effectively achieved, meanwhile, the main magnetic field non-uniformity correction problem of the fat tissue area is solved, and the novel Z-spectrum fat quantitative imaging method is provided.

Description

Technical Field

[0001] The present invention belongs to the technical field of magnetic resonance imaging, and in particular relates to a magnetic resonance Z-spectroscopy fat quantitative imaging method, system, equipment and storage medium. Background Art

[0002] Adipose tissue is closely related to human metabolic diseases such as obesity, insulin resistance, type 2 diabetes, and cardiovascular disease, and has attracted increasing attention in recent years. Adipose tissue is mainly divided into white adipose tissue and brown adipose tissue, and their respective contents vary depending on age, gender, environment, and nutritional conditions. White adipose tissue has large and single lipids, which can be used to store energy and secrete leptin, which is involved in the regulation of fat and body weight. It is mainly distributed in subcutaneous tissue and around internal organs. White adipose tissue plays an important role in human growth and development. Its mass can more than double and then return to baseline levels. White adipose tissue effectively stores enough energy to free us from the constant search for food. Brown adipose tissue, on the other hand, has small and abundant lipids and can participate in energy consumption and heat production by consuming glucose and triglycerides. It is closely innervated by sympathetic nerves, has dense blood vessels, and is rich in iron-containing mitochondria. It is mainly distributed in the back of the neck, between the scapulae, axillae, around the aorta, and between the ribs. Long-term activation of brown adipose tissue has been shown to have a wide range of benefits for the health of various tissues such as the gastrointestinal tract, cardiovascular, and musculoskeletal systems.

[0003] In magnetic resonance fat quantitative imaging technology, magnetic resonance spectroscopy imaging technology ( 1 H-MRS) is a standard imaging method for fat quantification. Its higher spectral resolution can provide more accurate water and fat quantification results. 1 H-MRS is based on single-voxel acquisition, which has low spatial resolution, long signal acquisition time, and complex imaging and post-processing procedures, which limits the widespread use of this technology in clinical research related to fat quantification. In addition, Dixon water-fat separation technology, as a commonly used fat quantitative imaging technology in clinical practice, has the advantages of high spatial resolution and short acquisition time, and can efficiently and conveniently quantify the spatial distribution of fat content. However, Dixon water-fat separation technology is sensitive to field inhomogeneity, and the phase entanglement caused by it often produces water-fat exchange artifacts, and there are certain challenges in fat quantification in adipose tissue areas with short T2* values.

[0004] In summary, in order to more accurately quantify the body fat content and distribution and help us better monitor the body's lipid metabolism level, this application describes a magnetic resonance Z-spectroscopy fat quantitative imaging method. This method can provide additional detection means for clinical fat quantitative imaging. Summary of the invention

[0005] The main purpose of the present invention is to overcome the shortcomings and deficiencies of existing fat quantitative imaging technology, and provide a new method, system, device and storage medium for fat quantitative imaging based on magnetic resonance Z spectrum. The method is based on the direct saturation quantification capability of Z spectrum imaging for fat and water signals, and the advantage of Z spectrum imaging itself being insensitive to main magnetic field inhomogeneity, thereby achieving high-resolution fat quantitative imaging that is insensitive to field inhomogeneity.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for magnetic resonance Z-spectroscopy fat quantitative imaging, comprising the following steps:

[0008] Collect T2-weighted compressed water images and Z-spectrum images of the human shoulder and neck with matching spatial positions;

[0009] The T2-weighted compressed water image is subjected to histogram normalization and binarization threshold segmentation to segment the fat tissue and non-fat tissue and obtain the fat distribution map;

[0010] According to the different Z-spectral line distributions of different tissues in the Z-spectral image, the Z-spectral main magnetic field inhomogeneity correction is performed on the segmented fat tissue and non-fat tissue areas respectively;

[0011] Multi-pool Lorentz linear fitting was performed on the Z spectrum after main magnetic field inhomogeneity correction to extract the corresponding water and fat signals. The relative fat content per unit voxel was calculated based on the relative proportion of water and fat to achieve quantitative fat imaging.

[0012] As a preferred technical solution, the specific operation of T2-weighted compressed water image acquisition in the image acquisition module is as follows: a liquid attenuated inversion recovery magnetic resonance sequence is used to acquire T2-weighted compressed water image data of the human shoulder and neck area to obtain a water-fat distribution map, thereby providing a reference for the subsequent correction of the Z-spectrum main magnetic field inhomogeneity in the fat and non-fat areas.

[0013] As a preferred technical solution, the specific operation of Z spectrum image acquisition in the image acquisition module is as follows: acquire a Z spectrum image of the human shoulder and neck area that matches the spatial position of the T2-weighted compressed water image. Apply a pre-saturation excitation pulse before the fast spin echo sequence, and then acquire multiple saturation images M at different frequency offsets. z and a non-saturated image M0, each saturated image M collected at different frequency offsets z Normalize the non-saturated image M0 (Z = 1-M z / M0), and calculate the required Z spectrum.

[0014] The applied pre-saturation excitation pulse is a single continuous rectangular pulse, but is not limited to a rectangular pulse. The applied pre-saturation pulse is as short as possible, about 0.5s to 1.0s, to reduce the influence of chemical exchange saturation transfer effect on fat quantification results. Considering that the chemical frequency shifts of water and fat are observed to be 4.7ppm and 1.3ppm respectively in magnetic resonance spectroscopy imaging, the frequency shift interval between the two substances is about 3.4ppm. Therefore, in the Z spectrum imaging method, in order to more accurately quantify the fat content, it is necessary to collect multiple saturation image Mz data with a relative water proton resonance frequency offset of at least greater than -5.0ppm to +5.0ppm.

[0015] As a preferred technical solution, the specific operation of the fat segmentation module is as follows: grayscale value equalization processing is performed on the collected T2 weighted compressed water image to obtain an image with uniform grayscale distribution. Histogram processing is performed on the T2 weighted compressed water image with uniform grayscale distribution. Figure 2 The fat distribution map is obtained by threshold segmentation processing, which is used to prepare for the subsequent Z-spectrum main magnetic field inhomogeneity correction.

[0016] As a preferred technical solution, the specific operation of the main magnetic field inhomogeneity correction module is as follows: the human shoulder and neck fat distribution map and Z spectrum image with matching spatial positions are superimposed together. The entire scanning field is traversed in units of pixels, and whether the voxel belongs to the adipose tissue area is determined according to the fat distribution map results. Different main magnetic field correction processes are performed on the non-fat tissue area and the adipose tissue area.

[0017] For the non-fat tissue area, the Z spectrum (Z = 1-M z / M0) peak, find the highest point, the relative water proton frequency offset a corresponding to this point is the main magnetic field inhomogeneity offset that needs to be corrected. By correcting the entire Z spectrum by -a offset, the main magnetic field inhomogeneity correction can be completed; for the fat tissue area, identify the drawn Z spectrum (Z = 1-M z / M0) peaks, find out the highest peak and the second highest peak. According to the relative position of the frequency offset of the highest peak and the second highest peak, if the frequency offset of fat relative to water is -3.4ppm, the peak with relatively small frequency offset is identified as the fat peak, and the peak with relatively large frequency offset is identified as the water peak. At this time, the relative water proton frequency offset b of the fat peak is the main magnetic field inhomogeneity offset that needs to be corrected. By correcting the entire Z spectrum by -b-3.4 offset, the inhomogeneity correction of the main magnetic field can be completed.

[0018] As a preferred technical solution, the specific operation of the image reconstruction module is as follows: multi-pool Lorentz linear fitting is performed on the Z spectrum after the main magnetic field inhomogeneity correction, and the corresponding water peak W and fat peak F are fitted. The relative fat content in the unit voxel can be calculated based on the relative proportion of water and fat signals. To achieve quantitative fat imaging.

[0019] The multi-cell Lorentz linear fitting model is:

[0020]

[0021] Among them, i = 1 is the direct saturated water pool, i = 2 is the methylene fat pool, and i = 3 is the asymmetric macromolecular proton pool. Z(ω) is a number of L i (ω) The entire Z spectrum formed after superposition; L i (ω) is a signal peak with a peak value of A, a center frequency offset of ω0, a frequency offset of ω, and a peak half-width of lω.

[0022] As a preferred technical solution, the relative water proton resonance frequency offset range of the saturated image collected by the Z spectrum imaging is from -10ppm to +10ppm, which must include 0ppm and -3.5ppm, plus an image with a frequency offset of +300ppm as a non-saturated image. Preferably, the relative water proton frequency offset of the Z spectrum collection is: +300ppm, ±10ppm, ±7.5ppm, ±5ppm, ±4ppm, ±3.5ppm, ±3.0ppm, ±2.0ppm, ±1.0ppm, ±0.5ppm, 0ppm.

[0023] As a preferred technical solution, considering that the human shoulder and neck area is close to the body surface air and the field inhomogeneity is more obvious, rice bags need to be placed on both sides of the shoulder and neck before T2-weighted pressure water imaging and Z-spectrum imaging to reduce the impact of the main magnetic field inhomogeneity on the imaging results.

[0024] In a second aspect, the present invention provides a magnetic resonance Z-spectrum fat quantitative imaging system, which is applied to the magnetic resonance Z-spectrum fat quantitative imaging method, and includes an image acquisition module, a fat segmentation module, a main magnetic field inhomogeneity correction module and an image reconstruction module;

[0025] The image acquisition module acquires a T2-weighted compressed water image of the human shoulder and neck that matches the spatial position, and acquires a Z-spectrum image of the human shoulder and neck region that matches the spatial position of the T2-weighted compressed water image;

[0026] The fat segmentation module is used to perform histogram normalization and binarization threshold segmentation processing on the T2 weighted compressed water image to segment fat tissue and non-fat tissue to obtain a fat distribution map;

[0027] The main magnetic field inhomogeneity correction module is used to perform Z spectrum main magnetic field inhomogeneity correction on the segmented fat tissue and non-fat tissue areas respectively according to the different Z spectrum line distributions shown by different tissues in the Z spectrum image;

[0028] The image reconstruction module is used to perform multi-pool Lorentz linear fitting on the Z spectrum after the main magnetic field inhomogeneity correction, fit the corresponding water peak W, fat peak F and magnetization vector, and calculate the relative fat content in the unit voxel according to the relative proportion of water and fat signals to achieve quantitative fat imaging.

[0029] In a third aspect, the present invention provides an electronic device, characterized in that the electronic device comprises:

[0030] at least one processor; and,

[0031] a memory communicatively connected to the at least one processor; wherein,

[0032] The memory stores computer program instructions that can be executed by the at least one processor, and the computer program instructions are executed by the at least one processor so that the at least one processor can perform the magnetic resonance Z-spectroscopy fat quantitative imaging method.

[0033] In a third aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more computer programs, which can be executed by one or more processors to implement the magnetic resonance Z-spectroscopy fat quantitative imaging method.

[0034] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0035] (1) Existing 1 The fat quantitative imaging method of H-MRS can accurately quantify the signals of fat and water per unit volume. 1 The H-MRS method is a single-pixel imaging method with low spatial resolution, long imaging time, and complex operation, which is not convenient for clinical promotion and use. The magnetic resonance Z-spectroscopy fat quantitative imaging method proposed in the present invention has outstanding spatial resolution advantages, simple imaging operation, simple post-processing process, and is easy for clinical promotion.

[0036] (2) The existing fat quantitative imaging method based on Dixon water-fat separation has good temporal and spatial resolution, and can quickly and effectively quantify the fat content of tissues within a certain spatial range. However, the Dixon water-fat separation method is easily affected by the inhomogeneity of the main magnetic field, and its application effect is not good in edge areas close to the air and short T2* tissues. The magnetic resonance Z spectrum fat quantitative imaging method proposed in the present invention has a higher spectral resolution and can more realistically reflect the actual fat content; and the fat quantitative results are not easily affected by the inhomogeneity of the main magnetic field, and have inherent advantages in tissue areas with complex structures and obvious field inhomogeneities. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0038] Figure 1 Schematic diagram of the process of the magnetic resonance Z-spectroscopy fat quantitative imaging method according to an embodiment of the present invention;

[0039] Figure 2 The T2-weighted image of the human shoulder and neck region and the T2-weighted image after water signal suppression according to the embodiment of the present invention;

[0040] Figure 3 A Z spectrum image formed by normalizing a plurality of Z spectrum images with different frequency offsets according to an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram of the fat segmentation process according to an embodiment of the present invention;

[0042] Figure 5 This is a schematic diagram of field image correction in an embodiment of the present invention, showing the correction effect of the main magnetic field inhomogeneity of muscle and fat tissue respectively;

[0043] Figure 6 This is the multi-cell Lorentz fitting result of the embodiment of the present invention;

[0044] Figure 7 This is a diagram of fat quantification results obtained by the magnetic resonance Z-spectroscopy fat quantification imaging method according to an embodiment of the present invention.

[0045] Figure 8 4 is a block diagram of a magnetic resonance Z-spectroscopy fat quantitative imaging system according to an embodiment of the present invention.

[0046] Fig. 9 4 is a structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0048] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0049] like Figure 1 As shown, the magnetic resonance Z spectrum fat quantitative imaging method of this embodiment includes the following steps:

[0050] S1. Image acquisition, i.e., acquiring a T2-weighted compressed water image of the human shoulder and neck that matches the spatial position, and acquiring a Z-spectrum image of the human shoulder and neck region that matches the spatial position of the T2-weighted compressed water image.

[0051] Furthermore, the image data of the human shoulder and neck area are collected using a liquid attenuated inversion recovery magnetic resonance sequence to obtain T2-weighted compressed water images, which provide a reference for the subsequent correction of the Z-spectrum main magnetic field inhomogeneity between fat and non-fat areas, such as Figure 2 In a specific embodiment, the acquisition parameters of the T2-weighted compressed water image are as follows: echo time (TE) = 80 ms, repetition time (TR) = 5000 ms, inversion recovery time (IR) = 1000 ms, scanning field (FOV) = 50×50 cm 2 , in-plane resolution = 2 × 2 mm 2 , layer thickness = 5 mm.

[0052] Furthermore, a Z-spectrum image of the human shoulder and neck region matching the spatial position of the T2-weighted compressed water image is collected, such as Figure 3 In a specific embodiment, the acquisition parameters of the Z spectrum image are as follows: a pre-saturation excitation pulse (pulse duration is about 0.5s to 1.0s, saturation pulse intensity is about 0.5 to 1.0μT) is applied before the fast spin echo sequence, and then multiple saturation images M at different frequency offsets are acquired. z(±10ppm, ±7.5ppm, ±5ppm, ±4ppm, ±3.5ppm, ±3.0ppm, ±2.0ppm, ±1.0ppm, ±0.5ppm, 0ppm) and a non-saturated image M0 (+300ppm). Each saturated image M collected at different frequency offsets z Normalize the non-saturated image M0 (Z = 1-M z / M0), and calculate the required Z spectrum.

[0053] It is understandable that the applied pre-saturation excitation pulse is a single continuous rectangular pulse, but is not limited to a rectangular pulse. The applied pre-saturation pulse duration is as short as possible, between about 50ms and 500ms, to avoid the generation of additional chemical exchange saturation transfer phenomena that affect the accuracy of fat quantification. Considering that the chemical frequency offsets of water and fat observed in magnetic resonance spectroscopy imaging are 4.7ppm and 1.3ppm, respectively, the frequency offset interval of the two substances is about 3.4ppm. Therefore, in the Z spectrum imaging method, in order to better and accurately quantify the fat content, it is necessary to collect multiple saturation images M with a relative water proton resonance frequency offset of at least greater than -5.0ppm to +5.0ppm. z data.

[0054] S2. Fat segmentation: performing histogram normalization and binarization threshold segmentation processing on the T2 weighted compressed water image to segment the fat tissue and non-fat tissue to obtain a fat distribution map.

[0055] Further, such as Figure 4 As shown, step S2 is specifically as follows:

[0056] The grayscale value of the T2-weighted compressed water image is equalized to correct the grayscale value of the entire image, obtain an image with uniform grayscale distribution, and improve the image contrast. Figure 2 The image is binarized and the fat and other tissues are segmented to obtain the fat distribution map.

[0057] Furthermore, the binary threshold segmentation process is the maximum inter-class variance method. The specific method is as follows: Assume that T is the segmentation threshold of fat and non-fat tissue, the fat area accounts for the image ratio I1, and the average grayscale is H1; the non-fat area accounts for the image ratio I2, and the average grayscale is H2. Then the total average grayscale of the image is I1×H1+I2×H2, and the variance of the fat area and the non-fat area is I1×I2×(H1-H2) 2The above variance formula is iteratively solved to find the maximum variance value. It can be considered that the difference between the fat and non-fat areas is the largest at this time, thus obtaining the threshold T for fat segmentation. According to the threshold T, the T2 weighted compressed water image is binarized, the fat area is assigned a value of 1, and the non-fat area is assigned a value of 0, and the fat distribution map is obtained.

[0058] S3. Main magnetic field inhomogeneity correction, that is, according to the different Z spectrum line distributions of different tissues in the Z spectrum image, the Z spectrum main magnetic field inhomogeneity correction is performed on the segmented fat tissue and non-fat tissue areas respectively.

[0059] like Figure 5 As shown, step S5 specifically includes: superimposing the fat distribution map and the Z spectrum image together, traversing the entire scanning field in units of pixels, and judging whether the voxel belongs to the fat tissue area according to the fat distribution map result; performing different main magnetic field correction processing on the non-fat tissue area and the fat tissue area respectively.

[0060] For the non-fat tissue area, the Z spectrum (Z = 1-M z / M0) peak, find the only highest point, the relative water proton frequency offset a corresponding to this point is the main magnetic field inhomogeneity offset that needs to be corrected. By correcting the entire Z spectrum by -a offset, the inhomogeneity correction of the main magnetic field can be completed.

[0061] For the adipose tissue area, identify the Z spectrum (Z = 1-M z / M0) peaks, find out the highest peak and the second highest peak. According to the relative position of the frequency offset of the highest peak and the second highest peak, if the frequency offset of fat relative to water is -3.4ppm, the peak with relatively small frequency offset is identified as the fat peak, and the peak with relatively large frequency offset is identified as the water peak. At this time, the relative water proton frequency offset b of the fat peak is the main magnetic field inhomogeneity offset that needs to be corrected. By correcting the entire Z spectrum by -b-3.4 offset, the inhomogeneity correction of the main magnetic field can be completed.

[0062] S4, image reconstruction, such as Figure 6 As shown, the entire scanning field is traversed in units of pixels, and the Z spectrum after the main magnetic field inhomogeneity correction is subjected to multi-pool Lorentz linear fitting to fit the corresponding water peak W, fat peak F and magnetization vector. The relative fat content in the unit voxel can be calculated based on the relative proportion of water and fat signals. To generate fat quantification maps, such as Figure 7 shown.

[0063] The multi-cell Lorentz linear fitting model is:

[0064]

[0065] Among them, i = 1 is the direct saturated water pool, i = 2 is the methylene fat pool, and i = 3 is the asymmetric macromolecular proton pool. Z(ω) is a number of L i (ω) The entire Z spectrum formed after superposition; L i (ω) is a signal peak with a peak value of A, a center frequency offset of ω0, a frequency offset of ω, and a peak half-width of lω.

[0066] Compared with the traditional Dixon water-fat separation technology, the magnetic resonance Z-spectroscopy fat quantitative imaging method in this embodiment is insensitive to field inhomogeneity, has a stronger field inhomogeneity correction capability, and has good fat quantitative imaging performance in tissue areas with complex structures and close to the air.

[0067] It should be noted that, for the sake of convenience, the aforementioned method embodiments are all expressed as a series of action combinations, but those skilled in the art should know that the present invention is not limited to the described order of actions, because according to the present invention, certain steps can be performed in other orders or simultaneously.

[0068] Based on the same concept as the magnetic resonance Z spectrum fat quantitative imaging method in the above embodiment, the present invention also provides a magnetic resonance Z spectrum fat quantitative imaging system, which can be used to perform the above magnetic resonance Z spectrum fat quantitative imaging method. For ease of explanation, the structural schematic diagram of the magnetic resonance Z spectrum fat quantitative imaging system embodiment only shows the parts related to the embodiment of the present invention. Those skilled in the art can understand that the illustrated structure does not constitute a limitation on the device, and may include more or fewer components than shown in the diagram, or combine certain components, or arrange the components differently.

[0069] See also Figure 8 In another embodiment of the present application, a magnetic resonance Z-spectroscopy fat quantitative imaging system 100 is provided, the system comprising an image acquisition module 101, a fat segmentation module 102, a main magnetic field inhomogeneity correction module 103 and an image reconstruction module 104;

[0070] The image acquisition module 104 acquires a T2 weighted compressed water image of the human shoulder and neck that matches the spatial position, and acquires a Z spectrum image of the human shoulder and neck region that matches the spatial position of the T2 weighted compressed water image;

[0071] The fat segmentation module 102 is used to perform histogram normalization and binarization threshold segmentation processing on the T2 weighted compressed water image to segment fat tissue and non-fat tissue to obtain a fat distribution map;

[0072] The main magnetic field inhomogeneity correction module 103 is used to perform Z spectrum main magnetic field inhomogeneity correction on the segmented fat tissue and non-fat tissue regions respectively according to the different Z spectrum line distributions shown by different tissues in the Z spectrum image;

[0073] The image reconstruction module 104 is used to perform multi-pool Lorentz linear fitting on the Z spectrum after the main magnetic field inhomogeneity correction, fit the corresponding water peak W, fat peak F and magnetization vector, and calculate the relative fat content in the unit voxel according to the relative proportion of water and fat signals to achieve quantitative fat imaging.

[0074] It should be noted that the magnetic resonance Z-spectroscopy fat quantitative imaging system of the present invention corresponds one-to-one to the magnetic resonance Z-spectroscopy fat quantitative imaging method of the present invention. The technical features and beneficial effects described in the embodiment of the above-mentioned magnetic resonance Z-spectroscopy fat quantitative imaging method are all applicable to the embodiment of magnetic resonance Z-spectroscopy fat quantitative imaging. For specific contents, please refer to the description in the embodiment of the method of the present invention, and will not be repeated here. This is hereby declared.

[0075] In addition, in the implementation of the magnetic resonance Z-spectroscopy fat quantitative imaging system in the above-mentioned embodiment, the logical division of each program module is only an example. In actual application, the above-mentioned functions can be assigned to different program modules as needed, for example, for the convenience of corresponding hardware configuration requirements or software implementation. That is, the internal structure of the magnetic resonance Z-spectroscopy fat quantitative imaging system is divided into different program modules to complete all or part of the functions described above.

[0076] See also Fig. 9 In one embodiment, an electronic device for implementing a magnetic resonance Z-spectroscopy fat quantitative imaging method is provided. The electronic device 200 may include a first processor 201, a first memory 202 and a bus, and may also include a computer program stored in the first memory 202 and executable on the first processor 201, such as a magnetic resonance Z-spectroscopy fat quantitative imaging program 203.

[0077] The first memory 202 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the first memory 202 can be an internal storage unit of the electronic device 200, such as a mobile hard disk of the electronic device 200. In other embodiments, the first memory 202 can also be an external storage device of the electronic device 200, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 200. Further, the first memory 202 can also include both an internal storage unit of the electronic device 200 and an external storage device. The first memory 202 can not only be used to store application software and various types of data installed in the electronic device 200, such as the code of the magnetic resonance Z spectrum fat quantitative imaging program 203, but also can be used to temporarily store data that has been output or is to be output.

[0078] In some embodiments, the first processor 201 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The first processor 201 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes various functions and processes data of the electronic device 200 by running or executing programs or modules stored in the first memory 202, and calling data stored in the first memory 202.

[0079] Fig. 9 Only an electronic device with components is shown, and those skilled in the art will understand that Fig. 9 The structure shown does not constitute a limitation on the electronic device 200 , and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0080] The magnetic resonance Z-spectroscopy fat quantitative imaging program 203 stored in the first memory 202 in the electronic device 200 is a combination of multiple instructions, and when executed in the first processor 201, it can achieve:

[0081] Acquire a T2-weighted compressed water image of the human shoulder and neck that matches the spatial position, and acquire a Z-spectrum image of the human shoulder and neck region that matches the spatial position of the T2-weighted compressed water image;

[0082] The T2-weighted compressed water image is subjected to histogram normalization and binarization threshold segmentation to segment the fat tissue and non-fat tissue and obtain the fat distribution map;

[0083] According to the different Z-spectral line distributions of different tissues in the Z-spectral image, the Z-spectral main magnetic field inhomogeneity correction is performed on the segmented fat tissue and non-fat tissue areas respectively;

[0084] After the main magnetic field inhomogeneity is corrected, the Z spectrum is subjected to multi-pool Lorentz linear fitting to fit the corresponding water peak W, fat peak F and magnetization vector. The relative fat content per unit voxel is calculated based on the relative proportion of water and fat signals to achieve quantitative fat imaging.

[0085] Furthermore, if the module / unit integrated in the electronic device 200 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0086] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0087] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0088] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. A magnetic resonance Z-spectroscopy fat quantitative imaging method, characterized in that: The steps include: Acquire a T2-weighted compressed water image of the human shoulder and neck that matches the spatial position, and acquire a Z-spectrum image of the human shoulder and neck region that matches the spatial position of the T2-weighted compressed water image; The T2-weighted compressed water image is subjected to histogram normalization and binarization threshold segmentation to segment the fat tissue and non-fat tissue and obtain the fat distribution map; According to the different Z-spectral line distributions of different tissues in the Z-spectral image, the Z-spectral main magnetic field inhomogeneity correction is performed on the segmented fat tissue and non-fat tissue areas respectively; After the main magnetic field inhomogeneity is corrected, the Z spectrum is subjected to multi-pool Lorentz linear fitting to fit the corresponding water peak W, fat peak F and magnetization vector. The relative fat content per unit voxel is calculated based on the relative proportion of water and fat signals to achieve quantitative fat imaging.

2. The magnetic resonance Z-spectroscopy fat quantitative imaging method according to claim 1, characterized in that: The T2-weighted compressed water image is collected in the following manner: The imaging data of the human shoulder and neck region were collected using a fluid-attenuated inversion recovery magnetic resonance sequence to obtain T2-weighted compressed water images.

3. The magnetic resonance Z-spectroscopy fat quantitative imaging method according to claim 1, characterized in that: The Z spectrum image is collected by the following method: A pre-saturation excitation pulse is applied before the fast spin echo sequence, and then multiple saturation images M at different frequency offsets are acquired. z and a non-saturated image M0, each saturated image M collected at different frequency offsets z The unsaturated image M0 is normalized to obtain the required Z spectrum image.

4. The magnetic resonance Z-spectroscopy fat quantitative imaging method according to claim 3, characterized in that: The saturated image M z The relative water proton resonance frequency offset is in the range of -10 ppm to +10 ppm and must include 0 ppm and -3.5 ppm.

5. The magnetic resonance Z-spectroscopy fat quantitative imaging method according to claim 1, characterized in that: The binary threshold segmentation process is specifically as follows: Assume T is the segmentation threshold of fat and non-fat tissue, the proportion of fat area in the image is I1, and the average grayscale is H1; the proportion of non-fat area in the image is I2, and the average grayscale is H2; then the total average grayscale of the image is I1×H1+I2×H2, and the variance between fat area and non-fat area is I1×I2×(H1-H2) 2 ; The above variance formula is iteratively solved to find the maximum variance value, at which point the difference between the fat and non-fat areas is the largest, thereby obtaining the threshold T for fat segmentation; based on the threshold T, the T2 weighted compressed water image is binarized, the fat area is assigned a value of 1, and the non-fat area is assigned a value of 0, to obtain a fat distribution map.

6. The magnetic resonance Z-spectroscopy fat quantitative imaging method according to claim 1, characterized in that: The Z spectrum main magnetic field inhomogeneity correction is specifically: The fat distribution map and the Z spectrum image are superimposed together, and the entire scanning field is traversed in units of pixels. According to the fat distribution map results, it is determined whether the voxel belongs to the fat tissue area; Different main magnetic field correction treatments are performed on non-fat tissue areas and fat tissue areas respectively; Among them, for the non-fat tissue area, the peak of the drawn Z spectrum is identified, and the only highest point is found. The relative water proton frequency offset a corresponding to this point is the main magnetic field inhomogeneity offset that needs to be corrected; by correcting the entire Z spectrum by -a offset, the inhomogeneity correction of the main magnetic field is completed; For the fat tissue area, identify the peaks of the drawn Z spectrum and find the highest peak and the second highest peak; according to the relative position of the frequency offset of the highest peak and the second highest peak, identify the peak with a relatively small frequency offset as the fat peak, and the peak with a relatively large frequency offset as the water peak; at this time, the relative water proton frequency offset b of the fat peak is the main magnetic field inhomogeneity offset that needs to be corrected; by correcting the entire Z spectrum by -b-3.4 offset, the main magnetic field inhomogeneity correction is completed.

7. The magnetic resonance Z-spectroscopy fat quantitative imaging method according to claim 1, characterized in that: The multi-cell Lorentz linear fitting model is: Among them, i = 1 is the direct saturated water pool, i = 2 is the methylene fat pool, and i = 3 is the asymmetric macromolecular proton pool; Z (ω) is a number of L i (ω) The entire Z spectrum formed after superposition; L i (ω) is a signal peak with a peak value of A, a center frequency offset of ω0, a frequency offset of ω, and a peak half-width of lω.

8. Magnetic resonance Z-spectroscopy fat quantitative imaging system, characterized in that: The magnetic resonance Z-spectroscopy fat quantitative imaging method applied to any one of claims 1 to 7 comprises an image acquisition module, a fat segmentation module, a main magnetic field inhomogeneity correction module and an image reconstruction module; The image acquisition module acquires a T2-weighted compressed water image of the human shoulder and neck that matches the spatial position, and acquires a Z-spectrum image of the human shoulder and neck region that matches the spatial position of the T2-weighted compressed water image; The fat segmentation module is used to perform histogram normalization and binarization threshold segmentation processing on the T2 weighted compressed water image to segment fat tissue and non-fat tissue to obtain a fat distribution map; The main magnetic field inhomogeneity correction module is used to perform Z spectrum main magnetic field inhomogeneity correction on the segmented fat tissue and non-fat tissue areas respectively according to the different Z spectrum line distributions shown by different tissues in the Z spectrum image; The image reconstruction module is used to perform multi-pool Lorentz linear fitting on the Z spectrum after the main magnetic field inhomogeneity correction, fit the corresponding water peak W, fat peak F and magnetization vector, and calculate the relative fat content in the unit voxel according to the relative proportion of water and fat signals to achieve quantitative fat imaging.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores computer program instructions executable by the at least one processor, and the computer program instructions are executed by the at least one processor so that the at least one processor can perform the magnetic resonance Z-spectroscopy fat quantitative imaging method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a program, characterized in that: When the program is executed by a processor, the magnetic resonance Z-spectroscopy fat quantitative imaging method according to any one of claims 1 to 7 is implemented.

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