Method and device for constructing a susceptibility-weighted map

Abstract

The embodiment of the application discloses a method and device for constructing a magnetic susceptibility weighted map. The method comprises: acquiring initial magnetic resonance image data of a brain region of a target object based on a magnetic susceptibility weighted imaging technology, wherein the initial magnetic resonance image data comprises initial amplitude image data and initial phase image data; determining phase mask image data according to the initial phase image data, acquiring an initial value of N, multiplying the Nth power of the phase mask image data and the initial amplitude image data according to the initial value of N, and obtaining an initial magnetic susceptibility weighted map corresponding to the initial magnetic resonance image data; dividing the initial magnetic susceptibility weighted map into a plurality of regions of interest, and respectively determining a target value of N of the phase mask image data corresponding to each region of interest according to the initial value of N; and updating the initial magnetic susceptibility weighted map according to each region of interest and the target value of N of the phase mask image data corresponding to each region of interest.

Description

Technical Field

[0001] This invention relates to the field of magnetic susceptibility weighted imaging technology, and in particular to a method and apparatus for constructing a magnetic susceptibility weighted spectrum. Background Technology

[0002] Medical susceptibility-weighted imaging (SWI) has become an important detection method for vascular pathological features such as cerebral hemorrhage and venous vascular lesions. Constructing a high-quality whole-brain venous vascular network will provide important physical information for quantifying the vascular effects and metabolic regulation of brain diseases.

[0003] Currently, the SWI images constructed by related technologies often fail to adequately represent different brain tissues. For example, they may result in low signal intensity in small veins, which could lead to errors in the boundaries of brain sulci and gyri. Consequently, the quality of the obtained susceptibility-weighted images is poor and cannot accurately reflect the actual situation of brain tissue. Summary of the Invention

[0004] This invention provides a method and apparatus for constructing a magnetic susceptibility-weighted map, which enables the setting of corresponding N values ​​for different regions of interest, thereby improving imaging quality and better reflecting the actual situation of brain tissue structure.

[0005] In a first aspect, embodiments of the present invention provide a method for constructing a magnetic susceptibility-weighted spectrum, comprising:

[0006] Acquire initial magnetic resonance imaging data of the brain region of the target object based on magnetic susceptibility weighted imaging technology, wherein the initial magnetic resonance imaging data includes initial amplitude image data and initial phase image data;

[0007] Phase mask image data is determined based on the initial phase image data, and an initial value of N is obtained. The Nth power of the phase mask image data and the initial amplitude image data are multiplied based on the initial value of N to obtain the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data, where N is a positive integer greater than 0.

[0008] The initial magnetic susceptibility weighted spectrum is divided into multiple regions of interest, and the target value of N for the phase mask image data corresponding to each region of interest is determined according to the initial value of N.

[0009] The initial magnetic susceptibility weighted spectrum is updated based on the target value of N in each region of interest and the phase mask image data corresponding to each region of interest.

[0010] Secondly, embodiments of the present invention also provide an apparatus for constructing a magnetic susceptibility-weighted spectrum, the apparatus comprising:

[0011] The magnetic resonance data acquisition module is used to acquire initial magnetic resonance image data of the brain region of the target object based on magnetic susceptibility weighted imaging technology, wherein the initial magnetic resonance image data includes initial amplitude image data and initial phase image data;

[0012] The initial spectrum construction module is used to determine phase mask image data based on the initial phase image data, obtain an initial value of N, and multiply the Nth power of the phase mask image data and the initial amplitude image data based on the initial value of N to obtain an initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data, where N is a positive integer greater than 0;

[0013] The phase mask N value update module is used to divide the initial magnetic susceptibility weighted spectrum into multiple regions of interest, and determine the target value of N of the phase mask image data corresponding to each region of interest according to the initial value of N.

[0014] The magnetic susceptibility weighted spectrum update module is used to update the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data based on each region of interest and the target value of N in the phase mask image data corresponding to each region of interest.

[0015] This invention provides a method for constructing a magnetic susceptibility-weighted map. It acquires initial magnetic resonance imaging (MRI) data of a brain region of a target object using magnetic susceptibility-weighted imaging technology. The initial MRI data includes initial amplitude image data and initial phase image data. Phase mask image data can be determined from the initial phase image data. Based on the acquired initial value of N, the Nth power of the phase mask image data is multiplied by the initial amplitude image data to obtain an initial magnetic susceptibility-weighted map corresponding to the initial MRI data. By dividing the initial magnetic susceptibility-weighted map into multiple regions of interest (ROIs), the characteristics of each ROI are highlighted. Based on the initial value of N, a target value of N for the phase mask image data corresponding to each ROI is determined. For different ROIs, corresponding target values ​​of N are obtained. The initial magnetic susceptibility-weighted map is updated based on each ROI and the target value of N for the corresponding phase mask image data. This method solves the problem that using a uniform N value for complete phase mask image data is not applicable to the image presentation of different brain tissues. It allows for setting corresponding N values ​​for different ROIs, which is beneficial for improving imaging quality and better reflecting the actual situation of brain tissue structure.

[0016] Furthermore, the magnetic susceptibility weighted spectrum construction apparatus provided in this embodiment corresponds to the above method and has the same beneficial effects. Attached Figure Description

[0017] To more clearly illustrate the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a method for constructing a magnetic susceptibility weighted spectrum according to Embodiment 1 of the present invention;

[0019] Figure 2 The flowchart shows a method for constructing a magnetic susceptibility weighted spectrum according to Embodiment 2 of the present invention.

[0020] Figure 3 This is a schematic diagram of a magnetic susceptibility weighted spectrum of a prior art.

[0021] Figure 4 This is a schematic diagram of a target magnetic susceptibility weighted spectrum provided in Embodiment 2 of the present invention;

[0022] Figure 5 This is a structural diagram of a device for constructing a magnetic susceptibility weighted spectrum according to Embodiment 3 of the present invention;

[0023] Figure 6 This is a structural diagram of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0024] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0025] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but it may also have additional steps not included in the figures. The process may correspond to a method, function, procedure, subroutine, subroutine, etc.

[0026] To enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] Example 1

[0028] Figure 1 This is a flowchart illustrating a method for constructing a magnetic susceptibility-weighted spectrum according to an embodiment of the present invention. This method can be executed by a magnetic susceptibility-weighted spectrum construction device, which can be implemented by software and / or hardware and can be configured in a terminal and / or server to implement the magnetic susceptibility-weighted spectrum construction method of the present invention.

[0029] like Figure 1 As shown, the method in this embodiment may specifically include:

[0030] S110. Acquire initial magnetic resonance image data of the brain region of the target object based on magnetic susceptibility weighted imaging technology.

[0031] It should be noted that susceptibility-weighted imaging (SWI) is a novel imaging technique, also known as magnetic susceptibility-weighted imaging. SWI can be understood as acquiring data based on gradient echo sequences, and then performing special data processing and image construction to form a magnetic resonance imaging technique that is sensitive to the magnetic susceptibility of materials. It utilizes the differences in magnetic susceptibility of different tissues to generate image comparisons.

[0032] The target object can be understood as the object whose brain region will be imaged using magnetic resonance imaging (MRI) with magnetic susceptibility weighted imaging. The brain region can be understood as the entire brain region of the target object, and the initial MRI image data is the data obtained after imaging the brain region using magnetic susceptibility weighted imaging technology.

[0033] In this embodiment, the initial magnetic resonance image data includes initial amplitude image data and initial phase image data. Initial phase image data can be understood as magnetic resonance image phase data obtained by scanning the brain region of the target object using magnetic resonance imaging technology, forming an image contrast based on the phase data differences of different protons. This data can be used to reflect the initial phase information of different protons during the relaxation process. Initial amplitude image data can be used to reflect the initial amplitude information of different protons during the relaxation process.

[0034] S120. Determine the phase mask image data based on the initial phase image data, obtain the initial value of N, and multiply the Nth power of the phase mask image data and the initial amplitude image data based on the initial value of N to obtain the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data.

[0035] Phase mask image data can be understood as an image filtering template. Typically, morphological methods can be used to construct mask image data based on the initial phase image data to extract information of interest about the brain regions of the target object.

[0036] In this embodiment, the method for determining phase mask image data based on initial phase image data includes: determining brain image magnetic resonance data corresponding to the initial magnetic resonance image data, wherein the brain image magnetic resonance data includes original brain amplitude image data and original brain phase image data; preprocessing the original brain phase image data, and establishing phase mask image data based on the preprocessed original brain phase image data.

[0037] In practice, when acquiring images of the target brain region using SWI technology, two parts of data are obtained: brain region data and non-brain region data. The brain region includes internal brain areas such as cerebral sulci and venous areas, while the non-brain region includes external brain areas such as the skull. Therefore, the initial magnetic resonance imaging (MRI) data includes both brain and non-brain MRI data. To preserve the internal brain regions as the imaging research object, the non-brain MRI data needs to be filtered out from the initial MRI data to determine the corresponding brain MRI data. Image construction is then based on this brain MRI data, reducing unnecessary interference and improving the accuracy of the constructed susceptibility-weighted spectrum.

[0038] In this embodiment, the brain image magnetic resonance data includes raw brain amplitude image data, which reflects the amplitude information of brain tissue during the magnetic resonance process, and the brain image magnetic resonance data also includes raw brain phase image data, which reflects the phase information of brain tissue during the magnetic resonance process.

[0039] Specifically, the raw phase image data of the brain can be preprocessed, and phase mask image data can be established based on the preprocessed raw phase image data of the brain. Preprocessing includes phase unwinding and background field removal. Specifically, because the scanning time of the brain region by magnetic resonance imaging is relatively long, phase aliasing can occur in the phase images of magnetic susceptibility-weighted imaging. Therefore, it is necessary to unwind the raw phase image data of the brain. The raw phase image data of the brain can be parsed, and then phase aliasing estimation can be performed by combining the phase information of multiple voxels. The aliased phase can be solved inversely to obtain the true phase information, and the raw phase image data of the brain can be updated based on the true phase information. For example, the unwinding processing method can include linear unwinding and nonlinear unwinding, such as the least squares unwinding method or the weighted least squares unwinding method.

[0040] Furthermore, the background field of the raw brain phase image data can be understood as being caused by uneven magnetic field distribution, and the presence of the background field interferes with the calculation of the magnetic susceptibility of the brain region. In order to improve the accuracy of the calculation results, the background field component needs to be filtered out before determining the magnetic susceptibility. For example, the background field of the raw brain phase image data can be removed by dipole field projection. Those skilled in the art can also use other methods to remove the background field according to the actual application, and this embodiment of the invention does not limit this.

[0041] Optionally, phase mask image data is established based on the preprocessed original phase image data of the brain, including: adjusting the phase value corresponding to each pixel in the preprocessed original phase image data of the brain to enhance the contrast between the small vein region and the region other than the vein region in the original phase image data of the brain, and establishing phase mask image data based on the adjusted original phase image data of the brain.

[0042] In specific implementation, the method for adjusting the phase value corresponding to each pixel in the preprocessed raw brain phase image data includes: determining the phase value corresponding to each pixel in the raw brain phase image data; for each pixel, when the corresponding phase value is in the range of [-180°, 0), a first function can be used to determine the first adjusted phase value corresponding to the phase value; when the corresponding phase value is in the range of (0, 180°), a second function can be used to determine the second adjusted phase value corresponding to the phase value; and adjusting the phase value at each pixel in the raw brain phase image data according to the first adjusted phase value and the second adjusted phase value.

[0043] Specifically, the first function and the second function can be first-order linear functions or constant functions, and the first function and the second function are not the same. Since the phase values ​​of the venous region and the region other than the venous region belong to different ranges, the contrast between the venous region and the region other than the venous region in the original phase image data of the brain is enhanced by adjusting the phase values ​​of the intervals [-180°, 0) and (0, 180°) respectively.

[0044] For example, the first and second functions can be set up in the following three ways:

[0045] 1. First function The second function can be ;

[0046] 2. The first function is y1=b, and the second function can be... ;

[0047] 3. The first function can be set as The second function is ;

[0048] Where x1 is the unadjusted phase value in the interval [-180°, 0), y1 is the first adjusted phase value, x2 is the unadjusted phase value in the interval (0, 180°), and y2 is the second adjusted phase value; k represents the slope, which is a positive integer and can be set to k=1, and b is a positive integer. It should be noted that those skilled in the art can also set the parameters in the first and second functions according to the actual application, and this embodiment of the invention does not limit this.

[0049] In practice, after adjusting the phase values ​​corresponding to each pixel in the original brain phase image data, phase mask image data is established based on the adjusted original brain phase data. Furthermore, an initial value of N can be obtained, and the Nth power of the phase mask image data is multiplied by the initial amplitude image data based on the initial value of N to obtain an initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data.

[0050] Where N is a positive integer greater than 0. The initial value of N can be understood as the value of N used in the prior art when multiplying the Nth power of the phase mask by the initial amplitude map. Specifically, the initial value of N can be obtained by sending an acquisition request to the work terminal; alternatively, the initial value of N can be stored in advance by the work terminal and obtained directly from the storage location.

[0051] S130. Divide the initial magnetic susceptibility weighted spectrum into multiple regions of interest, and determine the target value of N for the phase mask image data corresponding to each region of interest based on the initial value of N.

[0052] In practice, various partitioning methods can be used to divide the initial magnetic susceptibility weighted spectrum. These partitioning methods may include at least one of grid-like partitioning, strip-shaped partitioning, and random partitioning.

[0053] For example, for grid-like partitioning, each grid can be any shape among rectangles, circles, triangles, and trapezoids to obtain the region of interest corresponding to the grid shape. The shapes of the partitioned regions of interest can be the same or different. For strip-shaped partitioning, horizontal, vertical, and diagonal strip partitioning are possible, and each strip can be a straight line or a curved line. For random partitioning, different regions of interest can be partitioned according to the different components and structures of the brain tissue represented by each region.

[0054] Furthermore, the number of regions of interest can be determined based on the complexity of the initial magnetic susceptibility weighted map. If the brain tissue structure reflected in the initial magnetic susceptibility weighted map is complex, the initial magnetic susceptibility weighted map can be finely divided to improve the accuracy of the reconnected map. If the brain tissue structure reflected in the initial magnetic susceptibility weighted map is relatively simple, the initial magnetic susceptibility weighted map can be divided into a small number of regions of interest to ensure the accuracy of the constructed map while improving the calculation speed.

[0055] Optionally, the initial magnetic susceptibility weighted spectrum can be divided into multiple regions of interest, including: using a sliding window of preset width to divide the initial magnetic susceptibility weighted spectrum into multiple non-overlapping regions of interest.

[0056] The sliding window is a rectangular frame with a preset width. Its shape and size can be determined based on the preset width and different aspect ratios or step sizes. In specific implementations, the sliding window can be set to slide on the initial magnetic susceptibility weighted map in a preset order, such as from left to right or from top to bottom. During horizontal sliding, the length of the sliding window can be used as the sliding step size; during vertical sliding, the width of the sliding window can be used as the sliding step size. Each time, the ending position of the previous slide is used as the inspiration position for the next slide. The region corresponding to each sliding window is determined as the region of interest, and the initial magnetic susceptibility weighted map is divided into multiple non-overlapping regions of interest without overlap or omission.

[0057] Furthermore, when the sliding window moves to the edge of the initial magnetic susceptibility weighted spectrum, if some areas of the sliding window extend beyond the edge of the initial magnetic susceptibility weighted spectrum, the region of interest can be determined in the following two ways: 1. The extended areas can be discarded, and the area where the sliding window overlaps with the spectrum can be determined as the region of interest; 2. The extended areas can be interpolated with a magnetic susceptibility of 0, and the interpolated extended areas and the areas that do not extend together form the region of interest.

[0058] In practical implementation, for each defined region of interest (ROI), a target value for the corresponding phase mask image data N can be set based on the initial value of N. For example, the range of target values ​​for N for each ROI can be determined based on the initial value of N and a preset floating range, and the target value of N can be set based on this determined range. Furthermore, a condition for the target value of N can be set, and the values ​​that satisfy the condition can be determined as the target value of N. For example, the condition can be set as the average of the target values ​​of N for each ROI, equal to the initial value of N, and the target values ​​of N for each ROI are all within the determined range.

[0059] S140. Update the initial magnetic susceptibility weighted spectrum based on the target value of N in each region of interest and the phase mask image data corresponding to each region of interest.

[0060] In practice, the phase mask image data corresponding to each region of interest is determined based on the correspondence between the initial magnetic susceptibility weighted spectrum and the divided regions of interest.

[0061] Optionally, based on each region of interest and the target value of N in the phase mask image data corresponding to each region of interest, the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data is updated, including: for each region of interest, multiplying the Nth power of the phase mask image data and the initial amplitude image data according to the target value of N corresponding to the region of interest to obtain the local magnetic susceptibility weighted spectrum corresponding to the region of interest; and determining the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data based on the local magnetic susceptibility weighted spectrum corresponding to each region of interest.

[0062] Specifically, initial amplitude image data corresponding to each region of interest (ROI) can be determined separately. For each ROI, the Nth power of the phase mask image data of that ROI is calculated, and the Nth power result is multiplied by the initial amplitude image data corresponding to that ROI to obtain a local magnetic susceptibility weighted spectrum. The local magnetic susceptibility weighted spectra of each ROI are then stitched together according to the positional relationship between the ROIs, and the initial magnetic susceptibility weighted spectrum is updated based on the stitched and combined spectrum.

[0063] This invention provides a method for constructing a magnetic susceptibility-weighted map. It acquires initial magnetic resonance imaging (MRI) data of a brain region of a target object using magnetic susceptibility-weighted imaging technology. The initial MRI data includes initial amplitude image data and initial phase image data. Phase mask image data can be determined from the initial phase image data. The initial amplitude image data is multiplied by the Nth power of the phase mask image data based on the acquired initial value of N to obtain an initial magnetic susceptibility-weighted map corresponding to the initial MRI data. By dividing the initial magnetic susceptibility-weighted map into multiple regions of interest (ROIs), the characteristics of each ROI are highlighted. A target value of N for the phase mask image data corresponding to each ROI is determined based on the initial value of N. For different ROIs, corresponding target values ​​of N are obtained. The initial magnetic susceptibility-weighted map is updated based on each ROI and the target value of N for the corresponding phase mask image data. This method solves the problem that using a uniform N value for complete phase mask image data is not applicable to the image presentation of different brain tissues. It allows for setting corresponding N values ​​for different ROIs, which is beneficial for improving imaging quality and better reflecting the actual situation of brain tissue structure.

[0064] Example 2

[0065] Figure 2 This is a flowchart illustrating a method for constructing a magnetic susceptibility weighted spectrum according to Embodiment 2 of the present invention. This embodiment is based on and optimized from the above-described technical solutions. Optionally, the target value of N for the phase mask image data corresponding to each region of interest is determined according to the initial value of N, including: calculating the variance of the magnetic susceptibility value corresponding to each region of interest as the regional variance of each region of interest, and calculating the average variance of the initial magnetic susceptibility weighted spectrum based on the regional variance of each region of interest; for each region of interest, adjusting the initial value of N according to the regional variance and average variance corresponding to the region of interest to obtain the target value of N for the phase mask image data corresponding to the region of interest. The explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0066] S210. Acquire initial magnetic resonance image data of the brain region of the target object based on magnetic susceptibility weighted imaging technology.

[0067] S220. Determine the phase mask image data based on the initial phase image data, obtain the initial value of N, and multiply the Nth power of the phase mask image data and the initial amplitude image data based on the initial value of N to obtain the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data.

[0068] S230. Divide the initial magnetic susceptibility weighted spectrum into multiple regions of interest, and calculate the variance of the magnetic susceptibility value corresponding to each region of interest as the regional variance of each region of interest. Calculate the average variance of the initial magnetic susceptibility weighted spectrum based on the regional variance of each region of interest.

[0069] In practical implementation, the voxel magnetic susceptibility values ​​corresponding to each voxel in each region of interest can be determined based on the initial weighted magnetic susceptibility spectrum. Then, the variance of the magnetic susceptibility values ​​corresponding to each region of interest is calculated based on these voxel magnetic susceptibility values. Specifically, the regional variance of each region of interest is the average of the squared differences between the magnetic susceptibility value of each voxel in that region of interest and the mean of all voxel magnetic susceptibility values. Furthermore, the average variance of each region can be calculated, and this average value determines the overall average variance of the initial weighted magnetic susceptibility spectrum.

[0070] S240. For each region of interest, adjust the initial value of N according to the regional variance and average variance corresponding to the region of interest to obtain the target value of N for the phase mask image data corresponding to the region of interest.

[0071] In practical implementation, the initial value of N can be adjusted based on the regional variance and average variance corresponding to the region of interest as follows: A variance fluctuation range is set based on the average variance; for each region of interest, if the regional variance is outside the fluctuation range, the initial value of N corresponding to that region of interest can be adjusted; if the regional variance is within the fluctuation range, the initial value of N corresponding to that region of interest remains unchanged. Furthermore, when the regional variance is outside the fluctuation range, it can be set that if the regional variance is greater than the maximum value of the fluctuation range, the initial value of N corresponding to that region of interest is decreased; and if the regional variance is less than the minimum value of the fluctuation range, the initial value of N corresponding to that region of interest is increased.

[0072] In this embodiment, the initial value of N can also be adjusted according to the regional variance and average variance corresponding to the region of interest as follows: if the regional variance corresponding to the region of interest is greater than the average variance, decrease the initial value of N; if the regional variance corresponding to the region of interest is less than the average variance, increase the initial value of N.

[0073] Specifically, the variance of the region of interest (ROI) can be compared with the mean variance. When the regional variance is greater than the mean variance, it indicates that the ROI may correspond to a non-venous region in the brain of the target subject, such as the cerebral sulci. In this case, there is no need to emphasize this region, and the initial value of N can be decreased to determine the target value, making the regional variance of the ROI closer to the mean variance. When the regional variance is less than the mean variance, it indicates that the ROI may correspond to a difficult-to-identify tissue structure in the brain of the target subject, such as a small venous region. For tissue structures in this ROI, the initial value of N can be increased. It should be noted that when the regional variance equals the mean variance, it means that the current initial value of N is well set for the ROI, and the initial value of N can be directly set as the target value of N without adjustment.

[0074] S250. Update the initial magnetic susceptibility weighted spectrum based on the target value of N in each region of interest and the phase mask image data corresponding to each region of interest.

[0075] Optionally, after updating the initial magnetic susceptibility weighted spectrum, the method further includes: recalculating the regional variance and average variance of each region of interest based on the updated initial magnetic susceptibility weighted spectrum; and determining whether to use the updated initial magnetic susceptibility weighted spectrum as the target magnetic susceptibility weighted spectrum based on the relationship between the regional variance and average variance of the region of interest before the update, and the relationship between the regional variance and average variance of the region of interest after the update.

[0076] To ensure that the updated initial magnetic susceptibility-weighted map accurately and effectively reflects the true state of the target subject's brain regions, the updated initial magnetic susceptibility-weighted map can be validated.

[0077] Specifically, the regional variance and mean variance of each region of interest can be recalculated based on the updated initial magnetic susceptibility weighted spectrum, and the relationship between the regional variance and mean variance of each region of interest can be determined. Based on the relationship between the variances before and after the update for each region of interest, it can be determined whether the value of N for that region of interest needs to be adjusted again. For regions of interest that need adjustment, the adjustment is performed again according to the previous increase or decrease trend, and the initial magnetic susceptibility weighted spectrum is updated again based on the adjusted N value. This process is repeated to determine whether the N value corresponding to each region of interest in the updated initial magnetic susceptibility weighted spectrum needs adjustment. If adjustment is still required, the above steps are repeated until the N value corresponding to all regions of interest has been adjusted. Then, the initial magnetic susceptibility weighted spectrum is updated based on the adjusted N value, and this updated initial magnetic susceptibility weighted spectrum is determined as the target magnetic susceptibility weighted spectrum.

[0078] Optionally, based on the relationship between the regional variance and the mean variance of the region of interest before the update, and the relationship between the regional variance and the mean variance of the region of interest after the update, it is determined whether to use the updated initial magnetic susceptibility weighted spectrum as the target magnetic susceptibility weighted spectrum. This includes: if the relationship between the regional variance and the mean variance of the region of interest before the update is opposite to the previous relationship between the regional variance and the mean variance of the region of interest after the update, then the updated initial magnetic susceptibility weighted spectrum is used as the target magnetic susceptibility weighted spectrum.

[0079] In practice, the relationship between the regional variance and the mean variance before and after the update can be determined separately. When the relationship between the regional variance and the mean variance corresponding to the region of interest before the update is opposite to the relationship between the regional variance and the mean variance corresponding to the region of interest after the update, it indicates that the adjustment result for the region of interest has achieved the preset effect. The updated initial magnetic susceptibility weighted spectrum can highlight the region of interest that needs to be highlighted more and can balance the tissue characteristics of each region of interest for magnetic resonance imaging. Therefore, the updated initial magnetic susceptibility weighted spectrum can be determined as the target magnetic susceptibility weighted spectrum.

[0080] If the relationship between the variance and mean variance of the region of interest before the update is the same as the relationship between the variance and mean variance of the region of interest after the update, it means that the effect after the update has not yet achieved the preset effect. It is still necessary to continue to adjust the value of N and update the initial magnetic susceptibility weighted spectrum based on the adjusted value of N until the relationship between the variance and mean variance of the region of interest after the update is opposite to the relationship between the variance and mean variance of the region of interest before the update. Then the updated initial magnetic susceptibility weighted spectrum can be determined as the target magnetic susceptibility weighted spectrum.

[0081] For example, to verify the effect of the target magnetic susceptibility weighted spectrum obtained by the embodiments of the invention, head magnetic resonance imaging data can be collected from several volunteers based on magnetic susceptibility weighted imaging technology. The specific operation includes the following steps:

[0082] 1. Data acquisition: A Siemens 7.0T magnetic resonance imaging system and a 32-channel phased array head coil were used. The main imaging parameters were TR / TE 23 / 15ms, FA 12°, matrix=768×696, and voxel size 0.28mm×0.28mm×2mm.

[0083] 2. Initialization calculation: The initial value of N can be set to 3. Multiply the original phase map Nth power with the amplitude map to obtain the initial magnetic susceptibility weighted spectrum.

[0084] 3. Adjusting the initial value of N: Using a sliding window with a width of 30 voxels, the initial magnetic susceptibility weighted spectrum is divided into multiple regions of interest. According to the method described above in the embodiments of the present invention, the initial value of N is adjusted based on the average variance of each region of interest. The magnetic susceptibility weighted vein spectrum is reconstructed using the modified initial value of N. The target magnetic susceptibility weighted vein spectrum is determined based on the reconstructed magnetic susceptibility weighted vein spectrum.

[0085] Figure 3 This is a schematic diagram of a magnetic susceptibility weighted spectrum in the prior art. Figure 4 This is a schematic diagram of a target magnetic susceptibility weighted spectrum provided in Embodiment 2 of the present invention; Figure 3 , 4 A comparison with the second image shows that the embodiments of the present invention can reduce prominent brain sulci and gyri signals; Figure 3 , 4 As can be seen from the comparison with the third image in the figure, the embodiment of the present invention can enhance the microvenous signal in the brain, thus ensuring the imaging quality of the atlas.

[0086] In this embodiment of the invention, an initial value of N is adjusted based on the relationship between the regional variance of the magnetic susceptibility corresponding to the region of interest and the average variance of the initial magnetic susceptibility weighted spectrum. This ensures that the value of N is more applicable to the corresponding region of interest, improving the accuracy of determining the value of N. Furthermore, the initial magnetic susceptibility weighted spectrum is updated based on the adjusted initial value of N. The updated initial magnetic susceptibility weighted spectrum is then verified to ensure that the obtained target magnetic susceptibility weighted spectrum can balance the tissue characteristics corresponding to each region of interest, which is beneficial to improving imaging quality and better reflecting the actual situation of brain tissue structure.

[0087] Example 3

[0088] Figure 5 This is a structural diagram of a magnetic susceptibility weighted spectrum construction apparatus according to Embodiment 3 of the present invention. This apparatus is used to execute the magnetic susceptibility weighted spectrum construction method provided in any of the above embodiments. This apparatus and the magnetic susceptibility weighted spectrum construction methods of the above embodiments belong to the same inventive concept. Details not described in detail in the embodiments of the magnetic susceptibility weighted spectrum construction apparatus can be found in the embodiments of the magnetic susceptibility weighted spectrum construction methods described above. Specifically, the apparatus may include:

[0089] The magnetic resonance data acquisition module 10 is used to acquire initial magnetic resonance image data of the brain region of the target object based on magnetic susceptibility weighted imaging technology, wherein the initial magnetic resonance image data includes initial amplitude image data and initial phase image data;

[0090] The initial spectrum construction module 11 is used to determine phase mask image data based on the initial phase image data, obtain an initial value of N, and multiply the Nth power of the phase mask image data and the initial amplitude image data based on the initial value of N to obtain an initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data, wherein N is a positive integer greater than 0;

[0091] The phase mask N value update module 12 is used to divide the initial magnetic susceptibility weighted spectrum into multiple regions of interest, and determine the target value of N of the phase mask image data corresponding to each region of interest according to the initial value of N.

[0092] The magnetic susceptibility weighted spectrum update module 13 is used to update the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data based on each region of interest and the target value of N in the phase mask image data corresponding to each region of interest.

[0093] Based on any optional technical solution in the embodiments of the present invention, optionally, the phase mask N value update module 12 includes:

[0094] The average variance calculation unit is used to calculate the variance of the magnetic susceptibility value corresponding to each region of interest, which is used as the regional variance of each region of interest, and to calculate the average variance of the initial magnetic susceptibility weighted spectrum based on the regional variance of each region of interest.

[0095] An initial value adjustment unit is used to adjust the initial value of N for each region of interest based on the region variance and the average variance corresponding to the region of interest, so as to obtain the target value of N of the phase mask image data corresponding to the region of interest.

[0096] Based on any optional technical solution in the embodiments of the present invention, optionally, the initial value adjustment unit includes:

[0097] The first adjustment subunit is used to reduce the initial value of N if the variance of the region corresponding to the region of interest is greater than the average variance.

[0098] The second adjustment subunit is used to increase the initial value of N if the regional variance corresponding to the region of interest is less than the average variance.

[0099] In addition to any of the optional technical solutions in the embodiments of the present invention, the invention may also include:

[0100] The variance calculation unit is used to recalculate the regional variance and average variance of each region of interest based on the updated initial magnetic susceptibility weighted spectrum after the initial magnetic susceptibility weighted spectrum is updated; and to determine whether to use the updated initial magnetic susceptibility weighted spectrum as the target magnetic susceptibility weighted spectrum based on the relationship between the regional variance and the average variance of the region of interest before the update, and the relationship between the regional variance and the average variance of the region of interest after the update.

[0101] Based on any optional technical solution in the embodiments of the present invention, the variance calculation unit may optionally include:

[0102] The target magnetic susceptibility weighted spectrum determination subunit is used to take the updated initial magnetic susceptibility weighted spectrum as the target magnetic susceptibility weighted spectrum if the relationship between the regional variance and the average variance corresponding to the region of interest before the update is opposite to the relationship between the regional variance and the average variance corresponding to the region of interest after the update.

[0103] Based on any optional technical solution in the embodiments of the present invention, optionally, the phase mask N value update module 12 includes:

[0104] The region of interest (ROI) division unit is used to divide the initial magnetic susceptibility weighted spectrum into multiple non-overlapping ROIs using a sliding window of preset width.

[0105] Based on any optional technical solution in the embodiments of the present invention, optionally, the magnetic susceptibility weighted spectrum update module 13 includes:

[0106] The local magnetic susceptibility weighted spectrum determination unit is used to, for each region of interest, multiply the Nth power of the phase mask image data and the initial amplitude image data according to the target value N corresponding to the region of interest to obtain the local magnetic susceptibility weighted spectrum corresponding to the region of interest; and determine the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data based on the local magnetic susceptibility weighted spectrum corresponding to each region of interest.

[0107] Based on any optional technical solution in the embodiments of the present invention, optionally, the initial map construction module 11 includes:

[0108] A brain image magnetic resonance data determination unit is used to determine brain image magnetic resonance data corresponding to the initial magnetic resonance image data, wherein the brain image magnetic resonance data includes original brain amplitude image data and original brain phase image data; preprocessing the original brain phase image data, and establishing phase mask image data based on the preprocessed original brain phase image data, wherein the preprocessing includes phase unwinding processing and background field removal processing.

[0109] Based on any optional technical solution in the embodiments of the present invention, the optional brain image magnetic resonance data determination unit includes:

[0110] The phase value adjustment subunit is used to adjust the phase value corresponding to each pixel in the preprocessed original brain phase image data to enhance the contrast between the small vein region and the region other than the vein region in the original brain phase image data, and to establish phase mask image data based on the adjusted original brain phase image data.

[0111] The magnetic susceptibility-weighted map construction apparatus provided in this embodiment of the invention can perform the following method: acquiring initial magnetic resonance imaging data of the brain region of the target object based on magnetic susceptibility-weighted imaging technology, wherein the initial magnetic resonance imaging data includes initial amplitude image data and initial phase image data; determining phase mask image data based on the initial phase image data, obtaining an initial value of N, multiplying the Nth power of the phase mask image data and the initial amplitude image data based on the initial value of N to obtain an initial magnetic susceptibility-weighted map corresponding to the initial magnetic resonance imaging data, wherein N is a positive integer greater than 0; dividing the initial magnetic susceptibility-weighted map into multiple regions of interest, and determining the target value of N of the phase mask image data corresponding to each region of interest based on the initial value of N; updating the initial magnetic susceptibility-weighted map based on each region of interest and the target value of N of the phase mask image data corresponding to each region of interest. This embodiment of the invention solves the problem that using a uniform N value for complete phase mask image data cannot be applied to the image presentation of different brain tissues, and realizes the setting of corresponding N values ​​for different regions of interest, which is beneficial to improving imaging quality and can better reflect the actual situation of brain tissue structure.

[0112] It is worth noting that in the embodiments of the above-mentioned magnetic susceptibility weighted spectrum construction device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0113] Example 4

[0114] Figure 6 This is a structural diagram of an electronic device provided in Embodiment 4 of the present invention. Figure 6 A block diagram of an exemplary electronic device 20 suitable for implementing embodiments of the present invention is shown. The illustrated electronic device 20 is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0115] like Figure 6 As shown, the electronic device 20 is presented in the form of a general-purpose computing device. The components of the electronic device 20 may include, but are not limited to: one or more processors or processing units 201, system memory 202, and bus 203 connecting different system components (including system memory 202 and processing unit 201).

[0116] Bus 203 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0117] Electronic device 20 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 20, including volatile and non-volatile media, removable and non-removable media.

[0118] System memory 202 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 204 and / or cache memory 205. Electronic device 20 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 206 may be used to read and write non-removable, non-volatile magnetic media. Disk drives for reading and writing to removable non-volatile disks (e.g., "floppy disks") and optical disk drives for reading and writing to removable non-volatile optical disks (e.g., CD-ROMs, DVD-ROMs, or other optical media) may be provided. In these cases, each drive may be connected to bus 203 via one or more data media interfaces. Memory 202 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0119] A program / utility 208 having a set (at least one) of program modules 207 may be stored, for example, in memory 202. Such program modules 207 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 207 typically perform the functions and / or methods described in the embodiments of the present invention.

[0120] Electronic device 20 can also communicate with one or more external devices 209 (e.g., keyboard, pointing device, display 210, etc.), and with one or more devices that enable a user to interact with electronic device 20, and / or with any device that enables electronic device 20 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 211. Furthermore, electronic device 20 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 212. As shown, network adapter 212 communicates with other modules of electronic device 20 via bus 203. It should be understood that other hardware and / or software modules can be used in conjunction with electronic device 20, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0121] The processing unit 201 executes various functional applications and data processing by running programs stored in the system memory 202.

[0122] The present invention provides an electronic device capable of performing the following method: acquiring initial magnetic resonance imaging data of a brain region of a target object based on magnetic susceptibility-weighted imaging technology, wherein the initial magnetic resonance imaging data includes initial amplitude image data and initial phase image data; determining phase mask image data based on the initial phase image data, obtaining an initial value of N, multiplying the Nth power of the phase mask image data and the initial amplitude image data based on the initial value of N to obtain an initial magnetic susceptibility-weighted spectrum corresponding to the initial magnetic resonance imaging data, wherein N is a positive integer greater than 0; dividing the initial magnetic susceptibility-weighted spectrum into multiple regions of interest, and determining a target value of N for the phase mask image data corresponding to each region of interest based on the initial value of N; updating the initial magnetic susceptibility-weighted spectrum based on each region of interest and the target value of N for the phase mask image data corresponding to each region of interest. This invention solves the problem that using a uniform N value for complete phase mask image data is not applicable to the image presentation of different brain tissues, and enables the setting of corresponding N values ​​for different regions of interest, which is beneficial to improving imaging quality and better reflecting the actual situation of brain tissue structure.

[0123] Example 5

[0124] This invention provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform a method for constructing a magnetic susceptibility-weighted spectrum, the method comprising:

[0125] This invention acquires initial magnetic resonance imaging (MRI) data of the brain region of a target object using magnetic susceptibility-weighted imaging technology. The initial MRI data includes initial amplitude image data and initial phase image data. Phase mask image data is determined based on the initial phase image data, and an initial value of N is obtained. The Nth power of the phase mask image data is multiplied by the initial amplitude image data based on the initial value of N to obtain an initial magnetic susceptibility-weighted spectrum corresponding to the initial MRI data, where N is a positive integer greater than 0. The initial magnetic susceptibility-weighted spectrum is divided into multiple regions of interest (ROIs), and a target value of N for the phase mask image data corresponding to each ROI is determined based on the initial value of N. The initial magnetic susceptibility-weighted spectrum is updated based on each ROI and the target value of N for the corresponding phase mask image data. This invention solves the problem that using a uniform N value for complete phase mask image data is not applicable to the image presentation of different brain tissues. It enables the setting of corresponding N values ​​for different ROIs, which is beneficial for improving imaging quality and better reflecting the actual situation of brain tissue structure.

[0126] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the method operations described above, but can also execute related operations in the method for constructing the magnetic susceptibility weighted spectrum provided in any embodiment of the present invention.

[0127] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0128] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0129] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0130] Computer program code for performing the operations of embodiments of the present invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0131] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for constructing a magnetic susceptibility weighted spectrum, characterized in that, include: Acquire initial magnetic resonance imaging data of the brain region of the target object based on magnetic susceptibility weighted imaging technology, wherein the initial magnetic resonance imaging data includes initial amplitude image data and initial phase image data; Phase mask image data is determined based on the initial phase image data, and an initial value of N is obtained. The Nth power of the phase mask image data and the initial amplitude image data are multiplied based on the initial value of N to obtain the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data, where N is a positive integer greater than 0. The initial magnetic susceptibility weighted spectrum is divided into multiple regions of interest, and the target value of N for the phase mask image data corresponding to each region of interest is determined according to the initial value of N. The initial magnetic susceptibility weighted spectrum is updated based on the target value of N in each region of interest and the phase mask image data corresponding to each region of interest. The step of determining the target value of N for the phase mask image data corresponding to each region of interest based on the initial value of N includes: The variance of the magnetic susceptibility value corresponding to each region of interest is calculated separately and used as the regional variance of each region of interest. The average variance of the initial magnetic susceptibility weighted spectrum is then calculated based on the regional variance of each region of interest. For each region of interest, the initial value of N is adjusted according to the region variance and the average variance corresponding to the region of interest to obtain the target value of N for the phase mask image data corresponding to the region of interest. The step of adjusting the initial value of N based on the regional variance corresponding to the region of interest and the average variance includes: If the variance of the region corresponding to the region of interest is greater than the average variance, decrease the initial value of N; If the variance of the region corresponding to the region of interest is less than the average variance, increase the initial value of N.

2. The method according to claim 1, characterized in that, After updating the initial magnetic susceptibility weighted spectrum, the method further includes: The regional variance and average variance of each region of interest are recalculated based on the updated initial magnetic susceptibility weighted spectrum. Based on the relationship between the regional variance and the average variance of the region of interest before the update, and the relationship between the regional variance and the average variance of the region of interest after the update, it is determined whether to use the updated initial magnetic susceptibility weighted spectrum as the target magnetic susceptibility weighted spectrum.

3. The method according to claim 2, characterized in that, The step of determining whether to use the updated initial magnetic susceptibility weighted spectrum as the target magnetic susceptibility weighted spectrum based on the relationship between the region variance and the average variance corresponding to the region of interest before the update, and the relationship between the region variance and the average variance corresponding to the region of interest after the update, includes: If the relationship between the regional variance and the average variance of the region of interest before the update is opposite to the relationship between the regional variance and the average variance of the region of interest after the update, then the updated initial magnetic susceptibility weighted spectrum will be used as the target magnetic susceptibility weighted spectrum.

4. The method according to claim 1, characterized in that, The process of dividing the initial magnetic susceptibility weighted spectrum into multiple regions of interest includes: The initial magnetic susceptibility weighted spectrum is divided into multiple non-overlapping regions of interest using a sliding window of preset width.

5. The method according to claim 1, characterized in that, The step of updating the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data based on each region of interest and the target value of N in the phase mask image data corresponding to each region of interest includes: For each region of interest, the Nth power of the phase mask image data and the initial amplitude image data are multiplied according to the target value N corresponding to the region of interest to obtain the local magnetic susceptibility weighted spectrum corresponding to the region of interest; The initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data is determined based on the local magnetic susceptibility weighted spectrum corresponding to each region of interest.

6. The method according to claim 1, characterized in that, The step of determining the phase mask image data based on the initial phase image data includes: Determine the brain image magnetic resonance data corresponding to the initial magnetic resonance image data, wherein the brain image magnetic resonance data includes raw brain amplitude image data and raw brain phase image data; The raw phase image data of the brain is preprocessed, and phase mask image data is established based on the preprocessed raw phase image data of the brain. The preprocessing includes phase unwinding processing and background field removal processing.

7. The method according to claim 6, characterized in that, The step of establishing phase mask image data based on preprocessed raw brain phase image data includes: The phase values ​​corresponding to each pixel in the preprocessed raw brain phase image data are adjusted to enhance the contrast between the small vein region and the region other than the vein region in the raw brain phase image data. Phase mask image data is then established based on the adjusted raw brain phase image data.

8. An apparatus for constructing a magnetic susceptibility weighted spectrum, characterized in that, include: The magnetic resonance data acquisition module is used to acquire initial magnetic resonance image data of the brain region of the target object based on magnetic susceptibility weighted imaging technology, wherein the initial magnetic resonance image data includes initial amplitude image data and initial phase image data; The initial spectrum construction module is used to determine phase mask image data based on the initial phase image data, obtain an initial value of N, and multiply the Nth power of the phase mask image data and the initial amplitude image data based on the initial value of N to obtain an initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data, where N is a positive integer greater than 0; The phase mask N value update module is used to divide the initial magnetic susceptibility weighted spectrum into multiple regions of interest, and determine the target value of N of the phase mask image data corresponding to each region of interest according to the initial value of N. The magnetic susceptibility weighted spectrum update module is used to update the initial magnetic susceptibility weighted spectrum corresponding to the initial magnetic resonance image data based on each region of interest and the target value of N in the phase mask image data corresponding to each region of interest. The phase mask N-value update module includes: The average variance calculation unit is used to calculate the variance of the magnetic susceptibility value corresponding to each region of interest, which is used as the regional variance of each region of interest, and to calculate the average variance of the initial magnetic susceptibility weighted spectrum based on the regional variance of each region of interest. An initial value adjustment unit is used to adjust the initial value of N for each region of interest based on the region variance and the average variance corresponding to the region of interest, so as to obtain the target value of N of the phase mask image data corresponding to the region of interest. The initial value adjustment unit includes: The first adjustment subunit is used to reduce the initial value of N if the variance of the region corresponding to the region of interest is greater than the average variance. The second adjustment subunit is used to increase the initial value of N if the regional variance corresponding to the region of interest is less than the average variance.

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