Image correction method and device, computer device and storage medium

Abstract

The application relates to an image correction method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a fat distribution image of a scanned part, and a low-b-value scanning image and a high-b-value scanning image of the scanned part; performing image processing on the low-b-value scanning image based on the fat distribution image to obtain a low-b-value scanning image with inhibited fat components; determining main magnetic field distribution data according to the low-b-value scanning image with inhibited fat components and a preset estimation algorithm; and performing correction processing on the high-b-value scanning image through the main magnetic field distribution data. The application can improve the imaging effect.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of magnetic resonance imaging, and in particular to an image correction method and device, a computer device, and a storage medium. BACKGROUND

[0002] With the development of magnetic resonance technology, the way of magnetic resonance imaging is becoming more and more abundant. Among them, diffusion weighted imaging is one of the commonly used magnetic resonance imaging methods.

[0003] Diffusion weighted imaging is a magnetic resonance imaging method that can reflect the diffusion degree of water molecules in biological tissues, and has good sensitivity in clinical tumor detection. When imaging is performed using the diffusion weighted imaging method, the magnetic resonance imaging system scans the measured object according to the diffusion imaging sequence, then acquires planar echo data, and further reconstructs the scan image (i.e., the diffusion weighted image) of the measured object according to the acquired planar echo data and a preset reconstruction algorithm.

[0004] However, the magnetic sensitivity of biological tissues is different, resulting in uneven internal region of the main magnetic field of the tissue, thereby causing the diffusion weighted image to deform (such as signal stacking or stretching of the local region of the image), and the imaging effect is poor. SUMMARY

[0005] Therefore, it is necessary to provide an image correction method, device, computer device, and storage medium capable of improving the imaging effect in view of the above technical problems.

[0006] An image correction method, the method comprising:

[0007] obtaining a fat distribution image of a scanned part, and a low b-value scan image and a high b-value scan image of the scanned part;

[0008] performing image processing on the low b-value scan image based on the fat distribution image to obtain a low b-value scan image in which the fat component is suppressed;

[0009] determining main magnetic field distribution data according to the low b-value scan image in which the fat component is suppressed and a preset estimation algorithm;

[0010] performing correction processing on the high b-value scan image through the main magnetic field distribution data.

[0011] In one embodiment, the performing image processing on the low b-value scan image based on the fat distribution image to obtain a low b-value scan image in which the fat component is suppressed comprises:

[0012] estimating a fat displacement field according to a set fat chemical shift model;

[0013] mapping the fat distribution image to the low b-value scan image by using the fat displacement field to obtain a fat distribution correction image, the fat distribution correction image reflecting a fat component in the low b-value scan image;

[0014] performing suppression processing on the fat component in the low b-value scan image by using the fat distribution correction image to obtain a low b-value scan image with a suppressed fat component.

[0015] In one embodiment, the low b-value scan image includes two groups, and the two groups of low b-value scan images are determined by:

[0016] scanning a scanned site by using a preset low b-value diffusion imaging sequence to collect planar echo data of at least two groups of phase gradients in different directions;

[0017] reconstructing each group of collected planar echo data to obtain two groups of low b-value scan images of the scanned site.

[0018] In one embodiment, the correction processing on the high b-value scan image by using the main magnetic field distribution data includes:

[0019] performing image processing on the high b-value scan image based on the fat distribution correction image to obtain a high b-value scan image with a suppressed fat component;

[0020] performing correction processing on the high b-value scan image with a suppressed fat component by using the main magnetic field distribution data and a Jacobian algorithm.

[0021] In one embodiment, the image processing on the high b-value scan image based on the fat distribution correction image to obtain a high b-value scan image with a suppressed fat component includes:

[0022] multiplying pixel values of each pixel point in the fat distribution correction image by a preset scale factor to obtain fat pixel values of each pixel point in the fat distribution correction image;

[0023] subtracting the fat pixel values of each pixel point in the fat distribution correction image from pixel values of each pixel point in the high b-value scan image to obtain the high b-value scan image with a suppressed fat component.

[0024] In one embodiment, the method further includes:

[0025] performing correction processing on the low b-value scan image with a suppressed fat component by using the main magnetic field distribution data and a least square method.

[0026] An image correction method, the method includes:

[0027] Acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area;

[0028] Based on the fat distribution image, the low b-value scan image and the high b-value scan image are processed to obtain a low b-value scan image with suppressed fat components and a high b-value scan image with suppressed fat components.

[0029] Determine the main magnetic field distribution data of the magnetic field at the scanned location;

[0030] The low b-value scan image and / or high b-value scan image of the fat component that are suppressed are corrected by using the main magnetic field distribution data to obtain the corrected low b-value scan image and / or corrected high b-value scan image.

[0031] An image correction device, the device comprising:

[0032] The acquisition module is used to acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area.

[0033] The processing module is used to perform image processing on the low b-value scan image based on the fat distribution image to obtain a low b-value scan image in which fat components are suppressed.

[0034] The determination module is used to determine the main magnetic field distribution data based on the low b-value scan image of the suppressed fat components and a preset estimation algorithm;

[0035] The correction module is used to correct the high b-value scan image using the main magnetic field distribution data.

[0036] In one embodiment, the processing module is specifically used for:

[0037] Based on the established fat chemical displacement model, estimate the fat displacement field;

[0038] The fat distribution image is mapped to the low b-value scan image using the fat displacement field to obtain a fat distribution corrected image, which reflects the fat composition in the low b-value scan image.

[0039] The fat component in the low b-value scan image is suppressed using the fat distribution correction image to obtain a low b-value scan image with suppressed fat component.

[0040] In one embodiment, the correction module is specifically used for:

[0041] Based on the fat distribution correction image, the high b-value scan image is processed to obtain a high b-value scan image in which fat components are suppressed.

[0042] The high b-value scan image of the fat component being suppressed is corrected using the distribution data of the main magnetic field and the Jacobi algorithm.

[0043] In one embodiment, the correction module is specifically used for:

[0044] The product of the pixel value of each pixel in the fat distribution correction image and the preset scaling factor is used as the fat pixel value of each pixel in the fat distribution correction image.

[0045] The pixel values ​​of each pixel in the high b-value scan image are subtracted from the corresponding fat pixel values ​​of each pixel in the fat distribution correction image to obtain the high b-value scan image in which the fat component is suppressed.

[0046] In one embodiment, the correction module is further configured to:

[0047] The low b-value scan image of the fat component being suppressed is corrected using the main magnetic field distribution data and the least squares method.

[0048] An image correction device, the device comprising:

[0049] The acquisition module is used to acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area.

[0050] The processing module is used to perform image processing on the low b-value scan image and the high b-value scan image based on the fat distribution image to obtain a low b-value scan image with suppressed fat components and a high b-value scan image with suppressed fat components.

[0051] The determination module is used to determine the main magnetic field distribution data of the magnetic field at the location of the scanned part.

[0052] The correction module is used to correct the low b-value scan image and / or the high b-value scan image of the fat component that is suppressed by the main magnetic field distribution data, so as to obtain the corrected low b-value scan image and / or the corrected high b-value scan image.

[0053] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program performing the following steps:

[0054] Acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area;

[0055] Based on the fat distribution image, the low b-value scan image is processed to obtain a low b-value scan image in which fat components are suppressed.

[0056] Based on the low b-value scan image of the suppressed fat components and the preset estimation algorithm, the main magnetic field distribution data is determined;

[0057] The high b-value scan image is corrected using the main magnetic field distribution data.

[0058] A computer-readable storage medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0059] Acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area;

[0060] Based on the fat distribution image, the low b-value scan image is processed to obtain a low b-value scan image in which fat components are suppressed.

[0061] Based on the low b-value scan image of the suppressed fat components and the preset estimation algorithm, the main magnetic field distribution data is determined;

[0062] The high b-value scan image is corrected using the main magnetic field distribution data.

[0063] The aforementioned image correction method, apparatus, computer equipment, and storage medium can acquire fat distribution images of the scanned area, as well as low-b-value and high-b-value scan images of the scanned area. Based on the fat distribution images, image processing is performed on the low-b-value scan images to obtain low-b-value scan images with suppressed fat components. Based on the low-b-value scan images with suppressed fat components and a preset estimation algorithm, the main magnetic field distribution data is determined. The high-b-value scan images are then corrected using the main magnetic field distribution data. In this scheme, determining the main magnetic field distribution data using low-b-value scan images with suppressed fat components reduces the influence of fat on the main magnetic field distribution data, improves the accuracy of the main magnetic field distribution data, and then corrects the high-b-value scan images of the scanned area based on this main magnetic field distribution data. This effectively improves the accuracy of image correction, thereby enhancing the imaging effect of the magnetic resonance imaging system. Attached Figure Description

[0064] Figure 1 This is a flowchart illustrating an image correction method in one embodiment;

[0065] Figure 2 This is a flowchart illustrating the steps for determining low b-value scan images where fat components are suppressed, as shown in one embodiment.

[0066] Figure 3 This is a schematic diagram of a fat scan image in one embodiment;

[0067] Figure 4a This is a schematic diagram of a scanning sequence of a positive phase gradient in one embodiment;

[0068] Figure 4b This is a schematic diagram of the scanning sequence of the anti-phase gradient in one embodiment;

[0069] Figure 5a This is a reconstructed image along the positive phase gradient direction in one embodiment;

[0070] Figure 5b This is a reconstructed image with the inverse phase gradient direction in one embodiment;

[0071] Figure 6 This is a flowchart illustrating the steps for correcting a high b-value scanned image in one embodiment;

[0072] Figure 7 This is a flowchart illustrating the image correction method in another embodiment;

[0073] Figure 8 This is a flowchart illustrating the image correction method in another embodiment;

[0074] Figure 9 This is a structural block diagram of an image correction device in one embodiment;

[0075] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0076] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0077] First, before introducing the technical solutions of the embodiments of this application in detail, the technical background or evolution of the embodiments of this application will be introduced. In the field of magnetic resonance imaging technology, magnetic resonance imaging systems perform magnetic resonance imaging using diffusion-weighted imaging. Based on this background, through long-term model simulation research and development, as well as the collection, demonstration, and verification of experimental data, the applicant discovered that due to the differences in magnetic susceptibility of biological tissues, the distribution of the main magnetic field within the tissue is uneven, causing distortion of high-b-value and low-b-value scan images of the scanned area, such as signal stacking or stretching in local image regions, thus severely affecting the imaging effect. Therefore, how to correct the scanned images has become an urgent problem to be solved. In addition, it should be noted that the applicant has devoted a great deal of creative effort to the discovery of the technical problems in the embodiments of this application and the technical solutions described in the following embodiments.

[0078] In one embodiment, such as Figure 1 As shown, an image correction method is provided. This embodiment uses the application of this method to a terminal of a magnetic resonance imaging system as an example for illustration. It can be understood that this method can also be applied to the server of a magnetic resonance imaging system, and can also be applied to a system including a terminal and a server, and implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0079] Step 101: Obtain the fat distribution image of the scanned area, as well as the low b-value scan image and the high b-value scan image of the scanned area.

[0080] Optionally, diffusion can be represented as the random motion of water molecules within a medium. When a gradient magnetic field is present, the diffusion of water molecules causes a phase decoupling in the transverse magnetization vector, leading to attenuation of the magnetic resonance signal. Taking a gradient recalled echo (GRE) sequence as an example, when a diffusion-sensitive gradient is applied, the diffusion of water molecules causes attenuation of the magnetic resonance signal. The degree of attenuation depends on the apparent diffusion coefficient ADC(mm) of the water molecules. 2 The magnitude of b value (s / mm) and b value 2 The larger the b-value, the more sensitive diffusion-weighted imaging (DWI) is to the motion of water molecules. Optionally, b = γ. 2 G 2 δ 2 (Δ-δ / 3), where γ is the gyrometry ratio; G, δ, and Δ represent the amplitude, duration, and time interval of the applied diffusion-sensitive gradient field, respectively.

[0081] In implementation, the terminal can scan the area to be scanned using a preset fat imaging sequence and acquire echo data. Then, based on the acquired echo data and a preset reconstruction algorithm, a fat scan image of the scanned area is reconstructed. For example, the fat distribution image can reflect the fat distribution in the scanned area. Optionally, the fat distribution image can be acquired using at least one of the two-point Dixon method, the three-point Dixon method, and the multi-point Dixon method.

[0082] Furthermore, the terminal can scan the scanned area using a preset low b-value diffusion imaging sequence, and then acquire data to obtain a low b-value scan image. The processes of acquiring the fat distribution image of the scanned area and acquiring the low b-value scan image of the scanned area are not sequential and can be performed simultaneously. Similarly, the terminal can also scan the scanned area using a preset high b-value diffusion imaging sequence and acquire magnetic resonance diffusion-weighted signals in one or more diffusion gradient directions. The terminal can acquire only one diffusion gradient direction magnetic resonance diffusion-weighted signal, or it can select to acquire multiple diffusion gradient directions magnetic resonance diffusion-weighted signals according to actual needs; this embodiment does not limit this. The terminal can perform image reconstruction on the acquired magnetic resonance diffusion-weighted signals to obtain a high b-value scan image of the scanned area.

[0083] Optionally, low-b-value diffusion imaging sequences and high-b-value diffusion imaging sequences can be fusion sequences formed by diffusion-sensitive gradients and conventional spin echo (SE) sequences, spin echo-echo plane imaging (SE-EPI) sequences, fast spin echo (RARE) sequences, STEAM (stimulated echo acquisition mode), steady-state free precession (SSFP), spiral, or gradient-spin echo (GRASE) sequences. Optionally, the range of low b-values ​​can be 0-200 s / mm. 2 Any value of b; the range of b values ​​can be greater than 1500 s / mm 2 The value can be, for example, 1700-4500 s / mm 2 Any value.

[0084] Step 102: Perform image processing on the low b-value scan image based on the fat distribution image to obtain a low b-value scan image in which the fat component is suppressed.

[0085] In implementation, the terminal can subtract the fat distribution image from the low b-value scan image to obtain a low b-value scan image with suppressed fat components. Specifically, the terminal can subtract the corresponding fat pixel values ​​of each pixel in the low b-value scan image from the fat pixel values ​​of each pixel in the corrected fat distribution image (fat distribution correction image) to obtain the low b-value scan image with suppressed fat components. In one example, if the pixel value of pixel (x1, y1) in the low b-value scan image is 'a' and the pixel value of pixel (x1, y1) in the fat distribution correction image is 'b', then the pixel value of pixel (x1, y1) in the low b-value scan image with suppressed fat components is 'ab'.

[0086] Step 103: Determine the main magnetic field distribution data based on the low b-value scan image of suppressed fat components and the preset estimation algorithm.

[0087] Among them, the main magnetic field distribution data can reflect the non-uniform distribution of the main magnetic field.

[0088] In practice, after the terminal obtains a low b-value scan image showing suppressed fat components, it can determine the main magnetic field distribution data based on the low b-value scan image and a preset estimation algorithm. For example, the estimation algorithm can use the least squares method, and the main magnetic field distribution data can be obtained by solving a system of equations.

[0089] Step 104: Correct the high b-value scan image using the main magnetic field distribution data.

[0090] In practice, since the terminal calculates the main magnetic field distribution data, after acquiring the high b-value scan image of the scanned part, the terminal can use the main magnetic field distribution data and the preset correction algorithm to correct the high b-value scan image of the scanned part.

[0091] In the above image correction method, the main magnetic field distribution data is determined by the low b-value scan image with suppressed fat components, which reduces the influence of fat on the main magnetic field distribution data and improves the accuracy of the main magnetic field distribution data. Then, based on the main magnetic field distribution data, the high b-value scan image of the scanned area is corrected, which improves the accuracy of image correction and thus improves the imaging effect of the magnetic resonance system.

[0092] Optionally, the terminal can scan the target area using a preset fat imaging sequence. This fat imaging sequence can be a low-resolution fat imaging sequence, such as a dioxin (DIXON) sequence or a derived sequence. The terminal can acquire planar echo data and then perform image reconstruction based on the acquired planar echo data to obtain an image of the fat distribution or a fat scan image of the scanned area. Figure 3 The image shown is a fat distribution image obtained by scanning with a DIXON sequence.

[0093] For example, a fat distribution image can be obtained as follows: Two separate magnetic resonance images are acquired using a spin echo pulse sequence. One image is a conventional spin echo image with in-phase water and fat signals. The other image is obtained by modifying the readout gradient in the spin echo pulse sequence so that the water and fat signals are 180° out of phase. Based on these two images, a water image and a fat image can be generated; the fat image is the fat distribution image.

[0094] Alternatively, the fat distribution image can be obtained as follows: First, a planar field echo sequence is excited, and three different echo signals S1, S2, and S3 are acquired, where the precession phase difference between the water and fat signals of the first echo signal S1 and the third echo signal S3 is 2nπ, where n is a natural number; second, the acquired k-space signal is converted into an image signal through Fourier transform; third, effective image signal pixels are extracted in the image domain, and the phase map of the composite signal of the effective image signal pixels is obtained; the phase map is expanded to obtain the static magnetic field distribution map; finally, the water image and fat image in the echo signal are separated using the static magnetic field distribution map, and the fat image is the fat distribution image.

[0095] For example, image processing of low b-value scan images based on fat distribution images to obtain low b-value scan images with suppressed fat components may include:

[0096] Step 201: Estimate the fat displacement field based on the established fat chemical displacement model.

[0097] In this embodiment, the water component and the fat component have different precession frequencies, namely γ water and γ oil Therefore, the frequency difference between the fat signal and the water signal during spatial encoding leads to a displacement of the fat distribution in space. Since the bandwidth in the phase encoding direction is much smaller than that in the frequency encoding direction, generally only the chemical displacement in the phase encoding direction is considered. Assume the magnetic field strength is B, the bandwidth in the phase encoding direction is BW, and the encoding range is FOV. pe Then, the relative chemical shift of fat in the phase encoding direction By setting the aforementioned formula to the established fat chemical displacement model, the fat displacement field can be calculated.

[0098] Step 202: The fat distribution image is mapped to the low b-value scan image using the fat displacement field to obtain a fat distribution correction image, which reflects the fat components in the low b-value scan image.

[0099] In this embodiment, the fat distribution image reflects the approximate spatial distribution of fat. Each pixel in the fat distribution image corresponds to an actual physical spatial location I(x,y), where the phase encoding is in the x-direction. Based on the aforementioned fat chemical displacement model, the displacement field of the fat component in the diffuse image can be obtained as Δ. Therefore, the spatial location of the fat component in the low b-value image can be estimated as I(x+Δ,y), thereby determining the fat distribution correction image, which reflects the fat component in the low b-value scan image.

[0100] Step 203: Use the fat distribution correction image to suppress the fat components in the low b-value scan image to obtain a low b-value scan image with suppressed fat components.

[0101] Similar to the aforementioned method, high b-value scan images can also be processed based on fat distribution images to obtain high b-value scan images with suppressed fat components: the fat distribution image is mapped to the high b-value scan image using a fat displacement field to obtain a fat distribution correction image, which can reflect the fat components in the high b-value scan image; the fat components in the high b-value scan image are suppressed to obtain a high b-value scan image with suppressed fat components.

[0102] In practice, since the diffusion-weighted images (such as low b-value scan images) acquired in reality often exhibit deformation and displacement, it is necessary to apply corresponding deformation and displacement to the fat scan image or fat distribution image using a fat chemical shift model to obtain a fat distribution correction image that matches the diffusion-weighted image. In one implementation, the terminal can input the fat distribution image of the scanned area into a pre-stored fat chemical shift model and output the fat distribution correction image of the scanned area, i.e., the fat distribution image corresponding to the low b-value scan image and / or the fat distribution image corresponding to the high b-value scan image.

[0103] Based on the above process, the obtained fat distribution corrected image and the low b-value scan image and high b-value scan image have the same pixel position corresponding to the same position of the scanned part, so as to accurately restore the fat distribution in the diffusion-weighted image for subsequent processing.

[0104] Optionally, the low b-value scan images include two sets. The specific process of obtaining the two sets of low b-value scan images is as follows: the scanned area is scanned by a preset low b-value diffusion imaging sequence, and two sets of planar echo data with phase gradients in different directions are collected; image reconstruction is performed on each set of collected planar echo data to obtain two sets of low b-value scan images of the scanned area.

[0105] In one example, the terminal can store a scan sequence with phase gradients in both positive and negative directions, such as... Figure 4aThe image shows a schematic diagram of a scanning sequence with a positive phase gradient. Figure 4b The diagram shows a schematic of a scanning sequence with inverse phase gradients. The terminal can scan the area being scanned using a preset low-b-value diffusion imaging sequence, acquiring planar echo data of phase gradients in both positive and negative directions (the spike pulses in the diagram correspond to the phase-encoded gradients), and reconstructing two sets of low-b-value scan images of the scanned area. The reconstructed images are shown below. Figure 5a and Figure 5b As shown. Among them, Figure 5a The reconstructed image is in the positive phase gradient direction. Figure 5b The reconstructed image is in the opposite phase gradient direction.

[0106] In another example, the terminal can also acquire planar echo data of phase gradients in two other different directions for image reconstruction. The embodiments of this application do not limit the direction of the phase gradient.

[0107] Optionally, the specific processing steps for determining low b-value scan images where fat components are suppressed include:

[0108] Step 1: Multiply the pixel value of each pixel in the fat distribution correction image of the scanned area by the first scaling factor, and use the product as the first fat pixel value of each pixel in the fat distribution correction image.

[0109] In implementation, the terminal can pre-store a first scaling factor, the specific value of which can be set by technicians according to actual needs. For each pixel in the fat distribution correction image of the scanned area, the terminal can calculate the product of the pixel value and the first scaling factor, and use this product as the first fat pixel value for that pixel. In this way, the terminal can calculate the first fat pixel value for each pixel in the fat distribution correction image.

[0110] Step 2: Subtract the pixel value of each pixel in the low b-value scan image from the first fat pixel value of each pixel in the fat distribution correction image to obtain a low b-value scan image in which fat components are suppressed.

[0111] In implementation, since pixels at the same position in the fat distribution correction image and the acquired diffusion-weighted image correspond to the same location of the scanned area, for any pixel in the low b-value scan image, the terminal can obtain the pixel value (i.e., the first fat pixel value) of the pixel at the same position in the fat distribution correction image. Then, the first fat pixel value is subtracted from the pixel value of the low b-value scan image to obtain the pixel value after fat removal. By performing this process on each pixel in the low b-value scan image, a low b-value scan image with suppressed fat components can be obtained. It is understood that the terminal performs the above processing on each set of low b-value scan images to obtain each set of low b-value scan images with suppressed fat components.

[0112] In one example, the pixel value of pixel (x1, y1) in the low b-value scan image is a, the pixel value of pixel (x1, y1) in the fat distribution corrected image is b, and the first scaling factor is m. Then the pixel value of pixel (x1, y1) in the low b-value scan image where fat components are suppressed is (am*b).

[0113] Based on the above processing, image correction can be performed on low b-value scan images where fat components are suppressed, effectively solving the problem of fat images interfering with the imaging process and improving the imaging effect.

[0114] Optionally, the image correction process for low b-value scan images is as follows: using the main magnetic field distribution data and the least squares method, the low b-value scan images with suppressed fat components are corrected.

[0115] In this scheme, since the main magnetic field distribution data is determined based on low b-value scan images with suppressed fat components, the influence of fat on the main magnetic field distribution data is reduced, improving the accuracy of the main magnetic field distribution data. Therefore, image correction based on this main magnetic field distribution data can effectively improve the accuracy of correction and enhance imaging results. Moreover, this scheme corrects low b-value scan images with suppressed fat components, solving the interference problem of fat in the image and further improving imaging results.

[0116] Optional, such as Figure 6 As shown, the image correction process for high b-value scanned images is as follows:

[0117] Step 601: Based on the fat distribution correction image, perform image processing on the high b-value scan image to obtain a high b-value scan image in which fat components are suppressed.

[0118] In implementation, the terminal can subtract the fat distribution correction image from the high-b value scanned image to obtain a high-b value scanned image with suppressed fat components. Specifically, the terminal can subtract the pixel value of each pixel point in the high-b value scanned image from the fat pixel value of each pixel point in the fat distribution correction image to obtain a high-b value scanned image with suppressed fat components. In an example, if the pixel value of the pixel point (x2, y2) in the high-b value scanned image is x, and the pixel value of the pixel point (x2, y2) in the fat distribution correction image is y, then the pixel value of the pixel point (x2, y2) in the high-b value scanned image with suppressed fat components is x - y.

[0119] Step 602: Perform correction processing on the high-b value scanned image with suppressed fat components based on the distribution data of the main magnetic field and the Jacobi algorithm.

[0120] Optionally, the specific process of determining the high-b value scanned image with suppressed fat components is as follows: Multiply the pixel value of each pixel point in the fat distribution correction image by a preset scaling factor to obtain the fat pixel value of each pixel point in the fat distribution correction image; Subtract the fat pixel value of each pixel point in the fat distribution correction image from the pixel value of each pixel point in the high-b value scanned image to obtain a high-b value scanned image with suppressed fat components.

[0121] In implementation, a preset scaling factor (which can be referred to as the second scaling factor) can be pre-stored in the terminal. The value of the second scaling factor can be the same as or different from that of the first scaling factor, and the specific value of the second scaling factor can be set by technicians according to actual needs. For each pixel point in the fat distribution correction image of the scanned part, the terminal can calculate the product of the pixel value of this pixel point and the second scaling factor, and use this product as the fat pixel value (which can be referred to as the second fat pixel value) of this pixel point. In this way, the terminal can calculate the second fat pixel value of each pixel point in the fat distribution correction image.

[0122] Since the pixel points at the same pixel position in the fat distribution correction image and the acquired diffusion-weighted image correspond to the same position of the scanned part, for any pixel point in the high-b value scanned image, the terminal can obtain the pixel value (i.e., the second fat pixel value) of the pixel point with the same position as this pixel point in the fat distribution correction image, and then subtract the obtained second fat pixel value from the pixel value of this pixel point to obtain the pixel value of this pixel point after fat removal. In this way, after performing the above processing on each pixel point in the high-b value scanned image, a high-b value scanned image with suppressed fat components can be obtained.

[0123] In one example, the pixel value of the pixel (x2, y2) in the high b-value scan image is x, the pixel value of the pixel (x2, y2) in the fat distribution correction image is y, and the second scaling factor is n. Then the pixel value of the pixel (x2, y2) in the high b-value scan image where fat components are suppressed is (xn*y).

[0124] In this scheme, since the main magnetic field distribution data is determined from low b-value scan images with suppressed fat components, the influence of fat on the main magnetic field distribution data is reduced, improving the accuracy of the main magnetic field distribution data. Therefore, image correction based on this main magnetic field distribution data can effectively improve the accuracy of correction and enhance imaging results. Furthermore, this scheme corrects high b-value scan images with suppressed fat components, resolving the interference problem of fat in the image and further improving imaging performance.

[0125] This application also provides an example of an image correction method, such as... Figure 7 As shown, it includes the following steps:

[0126] Step 701: Scan the area to be scanned using a preset fat imaging sequence to obtain a fat scan image of the area to be scanned.

[0127] Step 702: Input the fat scan image of the scanned area into the pre-stored fat chemical shift model to obtain the fat distribution correction image of the scanned area.

[0128] Step 703: The scanned area is scanned using a preset low b-value diffusion imaging sequence to obtain two sets of low b-value scan images of the scanned area. Optionally, the two sets of low b-value scan images have the same b-value parameter, differing only in the opposite polarity of the phase encoding gradient.

[0129] Step 704: The product of the pixel value of each pixel in the fat distribution correction image of the scanned area and the first scaling factor is used as the first fat pixel value of each pixel in the fat distribution correction image.

[0130] Step 705: Subtract the pixel value of each pixel in each low b-value scan image from the first fat pixel value of each pixel in the fat correction distribution image to obtain two sets of low b-value scan images in which fat components are suppressed.

[0131] Step 706: Determine the main magnetic field distribution data based on the low b-value scan image of suppressed fat components and the preset estimation algorithm.

[0132] Step 707: Correct the low b-value scan image of the scanned area where the fat component is suppressed by using the main magnetic field distribution data and the least squares method.

[0133] Step 708: Based on the fat distribution correction image of the scanned area, perform image processing on the high b-value scan image to obtain a high b-value scan image in which fat components are suppressed.

[0134] Step 709: Correct the high b-value scan image where fat components are suppressed by using the main magnetic field distribution data and the Jacobi algorithm.

[0135] In one embodiment, such as Figure 8 As shown, another image correction method is provided. This embodiment uses the application of this method to a terminal of a magnetic resonance imaging system as an example for illustration. It can be understood that this method can also be applied to the server of a magnetic resonance imaging system, and can also be applied to a system that includes both a terminal and a server.

[0136] Step 801: Obtain the fat distribution image of the scanned area, as well as the low b-value scan image and the high b-value scan image of the scanned area.

[0137] The specific processing procedure for this step can be referred to the above. Figures 1-6 Explanation of the relevant steps.

[0138] Step 802: Based on the fat distribution image, perform image processing on the low b-value scan image and the high b-value scan image respectively to obtain the low b-value scan image with suppressed fat components and the high b-value scan image with suppressed fat components.

[0139] The specific processing procedure for this step can be referred to the above. Figures 1-6 Explanation of the relevant steps.

[0140] Step 803: Determine the main magnetic field distribution data of the magnetic field at the scanned location.

[0141] In one implementation, the processing steps provided by the image correction method described above can be used to determine the main magnetic field distribution data.

[0142] In another implementation, a measuring instrument can be used to measure the distribution of the main magnetic field within a certain area. The measured main magnetic field is then expanded using Legendre polynomials in spherical coordinates. The expanded polynomial is:

[0143]

[0144] Among them, B z R0 is the main magnetic field of the magnet, and R0 is the radius of the reference sphere used for the Legendre polynomial expansion. For Legendre polynomials, A nm B nmTo expand the polynomial coefficients, also known as harmonic coefficients, they can be represented by A(n,m) and B(n,m), respectively. n and m can be called the orders of the harmonic functions. From the properties of polynomials, we know that A(0,0) is the average value of the main magnetic field, and the other terms are the non-uniform terms of the main magnetic field (i.e., the distribution data of the main magnetic field).

[0145] In another implementation, the object being scanned can be excited to generate a measurement magnetic resonance signal corresponding to the imaging magnetic field. This measurement magnetic resonance signal is then acquired, and the actual magnetic field strength is obtained based on the principle of magnetic resonance. The measurement magnetic resonance signal includes both frequency and phase information. The actual magnetic field strength can be obtained from the frequency information, as follows:

[0146]

[0147] Where (γ,θ, t) represents the spatial coordinates of a point in polar coordinates, and f represents the frequency.

[0148] Alternatively, the instantaneous actual magnetic field strength can also be obtained through phase. The accumulated phase change within the time interval τ of the measured signal acquisition is: If τ is short enough, the actual magnetic field strength can be estimated using the following formula:

[0149]

[0150] Step 804: Correct the low b-value scan image and / or high b-value scan image with suppressed fat components using the main magnetic field distribution data to obtain the corrected low b-value scan image and / or corrected high b-value scan image.

[0151] The specific processing procedure for this step can be referred to the above. Figures 1-6 Explanation of the relevant steps.

[0152] In this scheme, the high b-value scan image with suppressed fat components is corrected by using the main magnetic field distribution data, which solves the problem of fat interference in the image and improves the imaging effect.

[0153] It should be understood that, although Figures 1-8 The steps in the flowchart are shown sequentially according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. For example, Figure 7 The execution order of step 703 is not specific to the execution order of steps 701-702; they can be executed simultaneously. Unless otherwise explicitly stated herein, there are no strict order restrictions on the execution of these steps; they can be executed in any other order. Furthermore, Figures 1-8At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0154] In one embodiment, such as Figure 9 As shown, an image correction device is provided, including: an acquisition module 910, a processing module 920, a determination module 930, and a correction module 940, wherein:

[0155] The acquisition module 910 is used to acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area.

[0156] Processing module 920 is used to perform image processing on the low b-value scan image based on the fat distribution image to obtain a low b-value scan image in which fat components are suppressed.

[0157] The determination module 930 is used to determine the main magnetic field distribution data based on the low b-value scan image of the suppressed fat components and a preset estimation algorithm;

[0158] The correction module 940 is used to correct the high b-value scan image using the main magnetic field distribution data.

[0159] In one embodiment, the processing module 920 is specifically used for:

[0160] Based on the established fat chemical displacement model, estimate the fat displacement field;

[0161] By using the fat displacement field to map the fat distribution image onto the low b-value scan image, a fat distribution correction image is obtained, which reflects the fat composition in the low b-value scan image.

[0162] Fat components in low b-value scan images are suppressed using fat distribution correction images to obtain low b-value scan images with suppressed fat components.

[0163] Alternatively, the fat distribution image can be mapped to a high b-value scan image using a fat displacement field to obtain a fat distribution correction image, which reflects the fat composition in the high b-value scan image.

[0164] Fat components in high b-value scan images are suppressed using fat distribution correction images to obtain high b-value scan images with suppressed fat components.

[0165] In one embodiment, the acquisition module 910 is specifically used for:

[0166] The scanned area is scanned using a preset low b-value diffusion imaging sequence, and at least two sets of planar echo data of phase gradients in different directions are acquired.

[0167] Image reconstruction was performed on each set of acquired planar echo data to obtain two sets of low b-value scan images of the scanned area.

[0168] In one embodiment, the correction module 940 is specifically used for:

[0169] Based on the fat distribution correction image, the high b-value scan image is processed to obtain a high b-value scan image in which fat components are suppressed.

[0170] The high b-value scan image of the fat component being suppressed is corrected using the distribution data of the main magnetic field and the Jacobi algorithm.

[0171] In one embodiment, the correction module 940 is specifically used for:

[0172] The product of the pixel value of each pixel in the fat distribution correction image and the preset scaling factor is used as the fat pixel value of each pixel in the fat distribution correction image.

[0173] The pixel values ​​of each pixel in the high b-value scan image are subtracted from the corresponding fat pixel values ​​of each pixel in the fat distribution correction image to obtain the high b-value scan image in which the fat component is suppressed.

[0174] In one embodiment, the correction module 940 is further configured to:

[0175] The low b-value scan image of the fat component being suppressed is corrected using the main magnetic field distribution data and the least squares method.

[0176] It is understandable that the image correction device can achieve the above-mentioned functions. Figures 1-7 The image correction method steps shown can also achieve Figure 8 The image correction method steps shown are described above. Specific limitations on the image correction device can be found in the limitations of the image correction method described above, and will not be repeated here. Each module in the above-described image correction device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0177] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 10As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements an image correction method. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0178] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0179] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method steps.

[0180] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described method steps.

[0181] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0182] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0183] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. An image correction method, characterized in that, The method includes: Acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area; Based on the fat distribution image, the low b-value scan image is processed to obtain a low b-value scan image in which fat components are suppressed. Based on the low b-value scan image of the suppressed fat components and the preset estimation algorithm, the main magnetic field distribution data of the magnetic field at the scanned site is determined. The high b-value scan image is corrected using the main magnetic field distribution data and the fat distribution correction image; the fat distribution correction image is obtained by mapping the fat distribution image to the low b-value scan image.

2. The method according to claim 1, characterized in that, The step of processing the low b-value scan image based on the fat distribution image to obtain a low b-value scan image with suppressed fat components includes: Based on the established fat chemical displacement model, estimate the fat displacement field; The fat distribution image is mapped to the low b-value scan image using the fat displacement field to obtain the fat distribution corrected image, which reflects the fat composition in the low b-value scan image. The fat component in the low b-value scan image is suppressed using the fat distribution correction image to obtain a low b-value scan image with suppressed fat component.

3. The method according to claim 1, characterized in that, The low b-value scan images comprise two sets, and the two sets of low b-value scan images are determined in the following manner: The scanned area is scanned using a preset low b-value diffusion imaging sequence, and two sets of planar echo data of phase gradient in different directions are acquired. Image reconstruction was performed on each set of acquired planar echo data to obtain two sets of low b-value scan images of the scanned area.

4. The method according to claim 2, characterized in that, The correction process for the high b-value scan image using the main magnetic field distribution data includes: Based on the fat distribution correction image, the high b-value scan image is processed to obtain a high b-value scan image in which fat components are suppressed. The high b-value scan image of the fat component that is suppressed is corrected using the main magnetic field distribution data and the Jacobi algorithm.

5. The method according to claim 4, characterized in that, The step of processing the high b-value scan image based on the fat distribution correction image to obtain a high b-value scan image with suppressed fat components includes: The product of the pixel value of each pixel in the fat distribution correction image and the preset scaling factor is used as the fat pixel value of each pixel in the fat distribution correction image. The pixel values ​​of each pixel in the high b-value scan image are subtracted from the corresponding fat pixel values ​​of each pixel in the fat distribution correction image to obtain the high b-value scan image in which the fat component is suppressed.

6. The method according to claim 1, characterized in that, The method further includes: The low b-value scan image of the fat component being suppressed is corrected using the main magnetic field distribution data and the least squares method.

7. An image correction method, characterized in that, The method includes: Acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area; Based on the fat distribution image, the low b-value scan image and the high b-value scan image are processed to obtain a low b-value scan image with suppressed fat components and a high b-value scan image with suppressed fat components. Determine the main magnetic field distribution data of the magnetic field at the scanned location; The low b-value scan image and / or high b-value scan image of the suppressed fat component are corrected using the main magnetic field distribution data to obtain corrected low b-value scan images and / or corrected high b-value scan images; the corrected high b-value scan images are then corrected using the main magnetic field distribution data and the fat distribution correction image; the fat distribution correction image is obtained by mapping the fat distribution image to the low b-value scan image.

8. An image correction device, characterized in that, The device includes: The acquisition module is used to acquire fat distribution images of the scanned area, as well as low b-value scan images and high b-value scan images of the scanned area. The processing module is used to perform image processing on the low b-value scan image based on the fat distribution image to obtain a low b-value scan image in which fat components are suppressed. The determination module is used to determine the main magnetic field distribution data of the magnetic field at the scanned site based on the low b-value scan image of the suppressed fat component and a preset estimation algorithm. The correction module is used to correct the high b-value scan image using the main magnetic field distribution data and the fat distribution correction image; the fat distribution correction image is obtained by mapping the fat distribution image to the low b-value scan image.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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