Image correction method, device, magnetic resonance apparatus, and readable storage medium

Abstract

The application relates to an image correction method and device, a magnetic resonance equipment and a readable storage medium. The method comprises the following steps: acquiring a scanning image to be corrected; the scanning image is collected by a receiving coil, and the receiving coil is provided with receiving channels; sensitivity calibration maps of the receiving coil are determined according to sensitivity distribution parameters of the receiving channels; the sensitivity distribution parameters are obtained by scanning a phantom; and the scanning image is corrected based on the sensitivity calibration maps to obtain a corrected image corresponding to the scanning image. By using the method, the influence of the nuclide concentration on the correction result can be avoided, and the accuracy of the image correction is improved.

Description

Technical Field

[0001] This application relates to the field of magnetic resonance scanning technology, and in particular to an image correction method, apparatus, magnetic resonance device, and readable storage medium. Background Technology

[0002] In magnetic resonance imaging (MRI), surface array coils (SACs) offer a significantly better signal-to-noise ratio than birdcage coils, and are frequently used as receiving coils in clinical multinuclear imaging (such as sodium-23 and potassium-39). However, SACs have limited receiving depth and uneven sensitivity distribution, resulting in poor image uniformity. Since multinuclear imaging relies on relative signal intensity for quantitative analysis, image uniformity correction is necessary.

[0003] Traditional calibration methods often employ the reference birdcage coil method, utilizing the near-uniform receiving field distribution of the birdcage coil to correct the surface array coil image. However, this method requires online scanning and real-time calculation on the subject. For multi-nucleus imaging such as sodium nuclei, the transverse relaxation time of the nuclei is a significant factor. Shorter scan lengths and lower concentrations within human tissues result in insufficient signal-to-noise ratios in the imaging signal, reducing the accuracy of calibration calculations. Furthermore, calibration scans require radial acquisition sequences based on free induction decay (FID) signals (zero-echo-time radial acquisition or ultra-short-echo-time radial acquisition), demanding a significantly higher number of scan axes compared to echo-based Cartesian acquisition sequences. This leads to longer single-cycle online calibration times and makes it difficult to ensure subject positional stability during clinical scanning.

[0004] Therefore, current magnetic resonance image correction techniques suffer from problems such as the correction results being easily affected by the concentration of multiple nuclides and insufficient calculation accuracy. Summary of the Invention

[0005] Therefore, it is necessary to provide an image correction method, apparatus, magnetic resonance device, computer-readable storage medium, and computer program product that can improve accuracy in addressing the aforementioned technical problems.

[0006] In a first aspect, this application provides an image correction method, comprising:

[0007] A scanned image of the sensitivity to be calibrated is acquired; the scanned image is acquired by a receiving coil, which is equipped with a receiving channel;

[0008] Based on the sensitivity distribution parameters of the receiving channel, a sensitivity calibration map of the receiving coil is determined; the sensitivity distribution parameters are obtained by scanning a phantom.

[0009] The scanned image is corrected based on the sensitivity calibration map to obtain the corrected image corresponding to the scanned image.

[0010] In one embodiment, the receiving coil is provided with a plurality of receiving channels;

[0011] Determining the sensitivity calibration map of the receiving coil based on the sensitivity distribution parameters of the receiving channel includes:

[0012] Based on the sensitivity distribution parameters of each receiving channel, determine the channel sensitivity distribution map of each receiving channel;

[0013] By merging the channel sensitivity distribution maps of each of the receiving channels, the sensitivity calibration map of the receiving coil is obtained.

[0014] In one embodiment, the sensitivity distribution parameters include sensitivity fitting parameters;

[0015] Determining the channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel includes:

[0016] Based on the sensitivity fitting parameters, the foreground region of the scanned image is fitted to obtain the channel sensitivity distribution map.

[0017] In one embodiment, the sensitivity distribution parameters include sensitivity fitting results;

[0018] Determining the channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel includes:

[0019] Based on the sensitivity fitting results, the channel sensitivity distribution map of the receiving channel is determined.

[0020] In one embodiment, the method further includes, prior to acquiring a scanned image of the sensitivity to be calibrated:

[0021] The pre-scanned image is obtained by scanning the phantom with a multi-flip angle sequence pulse.

[0022] Based on the pre-scanned image, the sensitivity amplitude diagrams of each receiving channel of the receiving coil under different flip angles are obtained;

[0023] Based on the sensitivity amplitude diagram, the sensitivity distribution parameters of each receiving channel are determined.

[0024] In one embodiment, the phantom comprises a multinucleoside ion solution with a nuclide concentration higher than a preset threshold, and the multi-flip angle sequence pulse includes a first pulse and a second pulse, wherein the flip angle of the first pulse is smaller than the flip angle of the second pulse.

[0025] In one embodiment, determining the sensitivity distribution parameters of each of the receiving channels based on the sensitivity amplitude map includes:

[0026] Based on the sensitivity amplitude diagram, determine the sensitivity distribution diagram of each of the receiving channels;

[0027] Based on the foreground region of the pre-scanned image, the sensitivity distribution map of each receiving channel is fitted to obtain the sensitivity fitting result and the sensitivity fitting parameter corresponding to the sensitivity fitting result;

[0028] Store the sensitivity fitting results and the sensitivity fitting parameters.

[0029] Secondly, this application also provides an image correction apparatus, comprising:

[0030] An acquisition module is used to acquire a scanned image of the sensitivity to be calibrated; the scanned image is acquired by a receiving coil, which is provided with a receiving channel;

[0031] The determination module is used to determine the sensitivity calibration map of the receiving coil based on the sensitivity distribution parameters of the receiving channel; the sensitivity distribution parameters are obtained by scanning the phantom.

[0032] The calibration module is used to calibrate the scanned image based on the sensitivity calibration map to obtain a calibrated image corresponding to the scanned image.

[0033] Thirdly, this application also provides a magnetic resonance device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any of the first aspects above.

[0034] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the first aspects above.

[0035] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in any of the first aspects above.

[0036] The aforementioned image correction method, apparatus, magnetic resonance imaging device, computer-readable storage medium, and computer program product acquire a scanned image of the sensitivity to be corrected. The scanned image is acquired by a receiving coil, which is equipped with a receiving channel. Based on the sensitivity distribution parameters of the receiving channel, a sensitivity calibration map of the receiving coil is determined. The sensitivity distribution parameters are obtained through a scanning phantom. The scanned image is corrected based on the sensitivity calibration map to obtain a corrected image corresponding to the scanned image. After acquiring the scanned image, the sensitivity calibration map can be obtained using the predetermined sensitivity distribution parameters. The scanned image can then be corrected using the sensitivity calibration map. Since the predetermined sensitivity distribution parameters are obtained by scanning a phantom with a high nuclide concentration, the correction result can be avoided due to the influence of nuclide concentration, thus improving the accuracy of image correction. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart illustrating an image correction method in one embodiment;

[0039] Figure 2 This is a flowchart illustrating the process of determining sensitivity fitting parameters in one embodiment;

[0040] Figure 3 This is a flowchart illustrating a method for correcting the receiving field sensitivity of a magnetic resonance multi-core scanning receiving coil in one embodiment.

[0041] Figure 4 This is a timing diagram of the pre-calibration scan sequence in one embodiment;

[0042] Figure 5 This is a schematic diagram of the signal amplitude of each receiving channel of a multi-core coil in one embodiment;

[0043] Figure 6 This is a schematic diagram of the multi-core coil merging channel sensitivity in one embodiment;

[0044] Figure 7 This is a flowchart illustrating the image correction method in another embodiment;

[0045] Figure 8 This is a structural block diagram of an image correction device in one embodiment. Detailed Implementation

[0046] 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.

[0047] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0048] In one exemplary embodiment, such as Figure 1 As shown, an image correction method is provided. This embodiment illustrates the application of this method to a magnetic resonance imaging (MRI) device. It is understood that this method can also be applied to other terminals or servers, and is not limited thereto. In this embodiment, the method includes the following steps:

[0049] Step S102: Obtain a scan image of the sensitivity to be calibrated; the scan image is acquired by a receiving coil, which is equipped with a receiving channel.

[0050] Here, a scanned image refers to the original image directly reconstructed by the magnetic resonance imaging (MRI) device without correction for coil sensitivity inhomogeneity. A receiving coil refers to the device in the MRI device used to receive the magnetic resonance signals generated by the relaxation of human tissue, including but not limited to surface array coils. A receiving coil can contain multiple coil units, and a receiving channel refers to an independent signal link that amplifies, acquires, and digitizes the output signal of a single coil unit.

[0051] Optionally, each receiving channel of the magnetic resonance device's receiving coil can independently acquire the magnetic resonance signal generated by the relaxation of human tissue. After image reconstruction, the magnetic resonance signals from each receiving channel can be finally synthesized into a scan image for coil sensitivity non-uniformity correction.

[0052] Step S104: Determine the sensitivity calibration map of the receiving coil based on the sensitivity distribution parameters of the receiving channel; the sensitivity distribution parameters are obtained by scanning the phantom.

[0053] The sensitivity distribution parameters can be predetermined model parameters or function parameters corresponding to the receiving channel, used to characterize the sensitivity distribution of the corresponding receiving channel. These parameters can be obtained through simulation, fitting, or measurement using a large phantom. For example, when using a polynomial fitting model, the sensitivity distribution parameters can be the coefficients of the polynomial fitting model, i.e., the sensitivity fitting parameters. In some embodiments, the sensitivity distribution parameters can also be the received channel sensitivity distribution map or sensitivity distribution matrix obtained after fitting, i.e., the sensitivity fitting result. The sensitivity calibration map can be an image used to correct coil sensitivity non-uniformity in the scanned image. The phantom refers to a simulation model capable of simulating the physicochemical and imaging characteristics of human tissue. The phantom can contain a multi-nucleon ion solution, including but not limited to sodium-23 and potassium-39 solutions. To ensure the accuracy of image correction, the nuclide concentration in the solution can be relatively high, and the nuclide concentration at each location of the phantom can be the same, i.e., the phantom is a homogeneous phantom.

[0054] Optionally, the sensitivity distribution parameters of each receiving channel of the magnetic resonance imaging (MRI) device can be determined in advance by scanning a phantom containing a solution of multinucleon ions, and these parameters can be stored in the MRI device. After acquiring the scanned image, the MRI device can obtain the sensitivity distribution parameters of the receiving channel used in the scanned image, determine the sensitivity distribution map of the corresponding receiving channel based on the sensitivity distribution parameters, and merge the sensitivity distribution maps of each receiving channel to obtain the sensitivity calibration map of the receiving coil.

[0055] Taking the use of a polynomial fitting model as an example, the sensitivity fitting parameters of each receiving channel of the receiving coil can be pre-stored in the magnetic resonance device. ,in For the receive channel index, This refers to the number of receiving channels. When correcting coil sensitivity inhomogeneities in clinical scan images, the corresponding values ​​can be read based on the receiving channels used in the clinical scan images. ,use A polynomial fitting model is constructed and used to fit the foreground region of the clinical scan image, obtaining the sensitivity distribution map of the corresponding receiving channel. For example, the clinical scan image can be binarized, and a threshold can be set to separate the foreground region, resulting in a binary mask image. For the receiving channel ,use Constructing a polynomial fitting model Then the receiving channel The sensitivity distribution map can be By merging, for example, the sensitivity distribution maps of the various receiving channels used in clinical scans, a sensitivity calibration map of the receiving coil can be obtained. .

[0056] In addition to pre-storing sensitivity fitting parameters Magnetic resonance imaging (MRI) devices can also pre-store the sensitivity fitting results of each receiving channel. When correcting coil sensitivity inhomogeneities in clinical scan images, MRI equipment can directly... The sensitivity distribution maps of each receiving channel used in the clinical scan images are obtained. These sensitivity distribution maps are then merged to obtain the sensitivity calibration map of the receiving coil. .

[0057] Step S106: Correct the scanned image based on the sensitivity calibration map to obtain the corrected image corresponding to the scanned image.

[0058] The corrected image refers to the image that has been corrected for coil sensitivity non-uniformity.

[0059] Optionally, the magnetic resonance imaging (MRI) device can correct for coil sensitivity inhomogeneities in the scanned images based on a determined sensitivity calibration map of the receiving coil, resulting in a corrected image. For example, a clinical scan image might be denoted as... The clinical scan images were compared with the sensitivity calibration diagram of the receiving coil. Dividing by this phase yields a uniform clinical image. The calculation formula is:

[0060] .

[0061] The above-described image correction method acquires a scanned image of the sensitivity to be corrected. The scanned image is obtained by a receiving coil, which is equipped with a receiving channel. Based on the sensitivity distribution parameters of the receiving channel, a sensitivity calibration map of the receiving coil is determined. The sensitivity distribution parameters are obtained through scanning a phantom. The scanned image is then corrected based on the sensitivity calibration map to obtain a corrected image corresponding to the scanned image. Alternatively, after acquiring the scanned image, a sensitivity calibration map can be obtained using the pre-determined sensitivity distribution parameters. The scanned image can then be corrected using the sensitivity calibration map. Since the pre-determined sensitivity distribution parameters are obtained by scanning a phantom with a high nuclide concentration, the correction result can be avoided due to the influence of nuclide concentration, thus improving the accuracy of image correction.

[0062] In an exemplary embodiment, the receiving coil is provided with multiple receiving channels; step S104 above may specifically include: determining the channel sensitivity distribution map of each receiving channel according to the sensitivity distribution parameters of each receiving channel; merging the channel sensitivity distribution maps of each receiving channel to obtain the sensitivity calibration map of the receiving coil.

[0063] Among them, the channel sensitivity distribution map refers to the sensitivity distribution map corresponding to the receiving channel of the receiving coil. The sensitivity distribution map is an image that reflects the distribution of signal strength at different spatial locations of the receiving channel.

[0064] Optionally, the magnetic resonance imaging (MRI) device can obtain the sensitivity distribution parameters of each receiving channel of the receiving coil from pre-stored sensitivity distribution parameters, obtain a channel sensitivity distribution map for each receiving channel based on the sensitivity distribution parameters, and merge the channel sensitivity distribution maps of all receiving channels to obtain a sensitivity calibration map of the receiving coil. For example, in some embodiments, the pre-stored sensitivity distribution parameters can be sensitivity fitting parameters. When correcting clinical scan images, the images can be binarized, and a threshold can be set to separate the foreground region, resulting in a binary mask image. For the receiving channel Using sensitivity fitting parameters Constructing a polynomial fitting model Then the receiving channel The channel sensitivity distribution map can be used to By combining the channel sensitivity distribution maps of each receiving channel, the sensitivity calibration map of the receiving coil can be obtained. The fitting model is not limited to a polynomial fitting model; it can also be a spherical harmonic function fitting model, a Gaussian fitting model, etc., and is not limited here. In other embodiments, the pre-stored sensitivity distribution parameters can also be the sensitivity fitting results. When correcting clinical scan images, magnetic resonance imaging (MRI) devices can determine the binary mask image of the clinical scan image. Then, the sensitivity fitting results were used directly. The channel sensitivity distribution maps of each receiving channel are obtained, and these maps are then merged to obtain the sensitivity calibration map of the receiving coil. .

[0065] In this embodiment, by determining the channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel, and merging the channel sensitivity distribution maps of each receiving channel, a sensitivity calibration map of the receiving coil is obtained. The pre-saved sensitivity distribution parameters can be read during human body scanning calibration, and the coil sensitivity non-uniformity can be directly corrected based on these parameters, avoiding rescanning and avoiding the problem of time-consuming human body scanning calibration caused by excessive scanning time of the RADIAL sequence acquired by FID.

[0066] In an exemplary embodiment, the sensitivity distribution parameters include sensitivity fitting parameters; the step of determining the channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel may specifically include: performing fitting processing on the foreground region of the scanned image based on the sensitivity fitting parameters to obtain the channel sensitivity distribution map.

[0067] Among them, the sensitivity fitting parameter refers to the parameter used to fit the sensitivity distribution of the receiving channel.

[0068] Optionally, the magnetic resonance imaging (MRI) device can pre-store the sensitivity fitting parameters for each receiving channel. After acquiring the scanned image, the MRI device can obtain the foreground region of the scanned image and perform fitting processing on the foreground region of the scanned image according to the sensitivity fitting parameters to obtain the channel sensitivity distribution map of each receiving channel. For example, the MRI device can pre-store the sensitivity fitting parameters for each receiving channel of the receiving coil. When performing coil sensitivity non-uniformity correction on clinical scan images, the corresponding data can be read from the receiving channel used for the clinical scan images. ,use A polynomial fitting model is constructed, and the constructed polynomial fitting model is used to fit the foreground region of the clinical scan image to obtain the sensitivity distribution map of the corresponding receiving channel.

[0069] In this embodiment, by fitting the foreground region of the scanned image according to the sensitivity fitting parameters, a channel sensitivity distribution map is obtained. Extrapolation can be performed based on polynomial fitting to obtain the sensitivity distribution parameters of all receiving channels of the receiving coil, thereby improving the reliability of image correction.

[0070] In an exemplary embodiment, the sensitivity distribution parameters include sensitivity fitting results; the step of determining the channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel may specifically include: determining the channel sensitivity distribution map of the receiving channel based on the sensitivity fitting results.

[0071] The sensitivity fitting result can be the sensitivity distribution of the receiving channel obtained by fitting the sensitivity fitting parameters.

[0072] Optionally, the magnetic resonance imaging (MRI) device can pre-store the sensitivity fitting results for each receiving channel. After acquiring the scanned image, the MRI device can directly obtain the channel sensitivity distribution map of each receiving channel of the receiving coil based on the sensitivity fitting results. For example, the MRI device can pre-store the sensitivity fitting results for each receiving channel of the receiving coil. When correcting coil sensitivity inhomogeneities in clinical scan images, the MRI equipment can directly... The sensitivity distribution map of each receiving channel used in clinical scan images was obtained.

[0073] In this embodiment, by determining the channel sensitivity distribution map of the receiving channel based on the sensitivity fitting results, the reliability of image correction can be improved, while also improving the efficiency of image correction.

[0074] In practical applications, in order to read the sensitivity distribution parameters during human body scanning calibration and directly correct coil sensitivity non-uniformity based on these parameters, it is necessary to pre-determine the sensitivity distribution parameters of each receiving channel of the receiving coil. In an exemplary embodiment, such as... Figure 2 As shown, prior to step S102 above, the procedure may further include:

[0075] Step S202: Obtain a pre-scanned image by scanning the phantom with a multi-flip angle sequence pulse.

[0076] Step S204: Based on the pre-scanned image, obtain the sensitivity amplitude diagram of each receiving channel of the receiving coil under different flip angles;

[0077] Step S206: Determine the sensitivity distribution parameters of each receiving channel based on the sensitivity amplitude diagram.

[0078] In this context, a multi-flip-angle sequence pulse refers to two or more radio frequency (RF) pulses with different flip angles. For example, a multi-flip-angle sequence pulse could be RF1 and RF2, where RF1 has a flip angle of 45 degrees and RF2 has a flip angle of 90 degrees. The pre-scan image can be a reconstructed image. For instance, the receiving coil acquires the FID signal obtained from RF1 and the FID signal obtained from RF2, and reconstructs the two FID signals to obtain the pre-scan image. A sensitivity amplitude map is an image reflecting the distribution of sensitivity amplitudes.

[0079] In an exemplary embodiment, the phantom contains a multinucleoside ion solution with a nuclide concentration higher than a preset threshold, and the multi-flip angle sequence pulse includes a first pulse and a second pulse, wherein the flip angle of the first pulse is smaller than the flip angle of the second pulse.

[0080] To ensure the accuracy of image correction, the nuclide concentration in the multinucleon ion solution within the phantom can be relatively high, meaning the nuclide concentration can exceed a preset threshold. The first pulse and the second pulse refer to two radio frequency pulses with different flip angles, where the flip angle of the first pulse is smaller than that of the second pulse. For example, the first pulse could be RF1 with a flip angle of 45 degrees, and the second pulse could be RF2 with a flip angle of 90 degrees.

[0081] Optionally, the magnetic resonance device can use two or more excitation pulses with different flip angles to scan a phantom containing a solution of multinucleonium ions and reconstruct the FID signal acquired by the receiving coil to obtain a pre-scan image. The magnetic resonance device can obtain the sensitivity amplitude map corresponding to each receiving channel of the receiving coil based on the pre-scan image. Based on the sensitivity amplitude map and the ideal magnetic resonance signal distribution estimated based on the emission field distribution map, the standard sensitivity distribution map of each receiving channel of the receiving coil can be obtained. Then, the sensitivity distribution parameters of each receiving channel of the receiving coil can be determined based on the standard sensitivity distribution map.

[0082] For example, suppose the flip angle of excitation pulse RF1 is 45 degrees and the flip angle of excitation pulse RF2 is 90 degrees. The free induction decay signals FID1 and FID2 obtained from RF1 and RF2 excitations are acquired respectively. The image matrix is ​​obtained by image reconstruction from FID1. The image matrix is ​​obtained by FID2 image reconstruction. , and This is a combined image of all receiving channels of the receiving coil, where The sensitivity amplitude diagram for each receiving channel is as follows: ,in For the receive channel index, This represents the number of receive channels.

[0083] Based on methods such as double flip angle or phase sensitivity, and In comparison, the launch field distribution is then calculated, for example, the launch field distribution matrix (launch field distribution map). The calculation formula can be:

[0084] .

[0085] Sensitivity amplitude diagram for each receiving channel This can be viewed as an image of the actual receiving channel. This can represent the ideal magnetic resonance signal distribution estimated using the transmit field distribution map, and therefore the standard sensitivity distribution map of each receiving channel of the receiving coil. It can be represented as:

[0086] .

[0087] right Binarization is performed and a threshold is set to select the foreground region, resulting in a binary mask. ,according to Data from the mid-foreground region were subjected to polynomial fitting to smooth the standard sensitivity distribution map for each receiving channel. The parameters obtained from the polynomial fitting are used as the sensitivity fitting parameters for the corresponding receiving channel. Alternatively, the result of the polynomial fitting (the sensitivity distribution map obtained from the fitting) can be directly used as the sensitivity fitting result of the corresponding receiving channel. ,Will and / or The sensitivity distribution parameters of the receiving channel were determined.

[0088] In this embodiment, the phantom is scanned by acquiring multi-flip angle sequence pulses, and the resulting pre-scan image is used to obtain the sensitivity amplitude map of each receiving channel of the receiving coil under different flip angles. Based on the sensitivity amplitude map, the sensitivity distribution parameters of each receiving channel are determined. The sensitivity distribution parameters can be predetermined. After acquiring the scan image, the sensitivity calibration map of the receiving coil can be directly determined based on the sensitivity distribution parameters. The scan image is then corrected using the sensitivity calibration map, saving the calibration time of the magnetic resonance image.

[0089] In an exemplary embodiment, step S206 may specifically include: determining the sensitivity distribution map of each receiving channel based on the sensitivity amplitude map; performing a fitting process on the sensitivity distribution map of each receiving channel based on the foreground region of the pre-scanned image to obtain the sensitivity fitting result and the sensitivity fitting parameter corresponding to the sensitivity fitting result; and storing the sensitivity fitting result and the sensitivity fitting parameter.

[0090] The foreground region refers to the imaging region within the magnetic resonance imaging field of view that contains the examined tissue, organ, or region of interest and can generate an effective magnetic resonance signal. Fitting processing refers to a data processing method that uses a selected mathematical function or model to optimally match and approximate the sensitivity distribution map obtained from actual measurements, including but not limited to at least one of polynomial fitting, spherical harmonic function fitting, and Gaussian fitting.

[0091] Optionally, in determining the sensitivity amplitude map corresponding to each receiving channel. Afterwards, the magnetic resonance imaging (MRI) device can... and In comparison, calculate the launch site distribution map. :

[0092] ;

[0093] Then, the standard sensitivity distribution diagram of each receiving channel of the receiving coil is calculated. :

[0094] ;

[0095] Magnetic resonance equipment can be used from Select the foreground region in the middle, and then... The corresponding foreground region is fitted, and the resulting sensitivity distribution map is used as the sensitivity fitting result. The parameters used in the fitting process are used as sensitivity fitting parameters. and to and The data is stored. It is understandable that, since the actual mod used typically cannot completely fill the entire area within the receiving coil volume, extrapolation can be performed through fitting. The fitted data... and It can cover areas that cannot be covered by the inner mold of the receiving coil.

[0096] In this embodiment, the sensitivity distribution map of each receiving channel is determined based on the sensitivity amplitude map. Based on the foreground region of the pre-scanned image, the sensitivity distribution map of each receiving channel is fitted to obtain the sensitivity fitting result and the corresponding sensitivity fitting parameter. The sensitivity fitting result and the sensitivity fitting parameter are stored. The sensitivity fitting parameter and sensitivity fitting result of each receiving channel of the receiving coil can be obtained by fitting, ensuring the reliability of the coil sensitivity non-uniformity correction.

[0097] To facilitate a deeper understanding of the embodiments of this application by those skilled in the art, a specific example will be used for illustration below.

[0098] To effectively reduce the time for dynamic measurements during scanning and avoid the impact of low signal-to-noise ratio in multi-core imaging on the accuracy of calibration calculations, this application provides a method for correcting the receiving field sensitivity of a receiving coil using magnetic resonance multi-core scanning. This method estimates the sensitivity distribution of the coil by measuring a high-concentration phantom during pre-calibration scanning, avoiding the difficulty of accurate calculation due to low signal-to-noise ratio in multi-core imaging during human body scanning. Moreover, during human body scanning, only the calibration results saved from the pre-calibration scan need to be read, eliminating the need for re-scanning and avoiding the problem of long calibration time for human body scanning caused by excessively long scanning time of the RADIAL sequence acquired by FID. In addition, this method uses data from a uniform phantom for measurement and calculation, which also avoids the influence of nuclide ion concentration distribution that may occur when using human body data for calculation.

[0099] In one exemplary embodiment, such as Figure 3 As shown, the method includes the following steps:

[0100] Step 1: Scan the phantom containing a solution of multiple nuclide ions to obtain a pre-calibrated image (pre-scanned image). The sequence used for pre-calibration scanning is a 3D RADIAL sequence with multiple flip angles (FA). The sequence scanning parameters are determined by the relaxation time of the solution within the phantom. The repetition time (TR) of the sequence acquisition needs to be much greater than the longitudinal relaxation time (T1) of the solution so that the signal can be approximated as sin(FA). In this embodiment, the following settings are made: , Where TE represents Echo Time, the number of flip angles is selected as 2, and the angles are selected as 45 degrees and 90 degrees. This sequence is as follows: Figure 4 As shown, RF1 and RF2 correspond to two different flip angles. During scanning, RF1 and RF2 are excited alternately and the same coding gradient (Gradient Readout, GRO) is used. ADC1 and ADC2 respectively acquire the FID signals obtained by RF1 and RF2. Here, ADC represents the Apparent Diffusion Coefficient.

[0101] Step 2: Reconstruct the pre-scanned image obtained in Step 1. Reconstruct an independent image magnitude matrix for each flip angle and save it as an image matrix. and image matrix The image matrix The corresponding flip angle is 45 degrees, image matrix The corresponding flip angle is 90 degrees. Image matrix. and This is a merged image of all receiving channels of the coil, where The amplitude diagram corresponding to all receiving channels is as follows , This refers to the number of channels. For example... Figure 5 As shown, an amplitude map corresponding to all received channels obtained from the reconstruction is provided. .

[0102] Step 3: According to the formula The launch site map is calculated, and the launch site distribution matrix is ​​saved as B1Map.

[0103] Step 4: According to the formula , The sensitivity distribution of each coil channel was calculated. Save the amplitude matrix as .in This represents the ideal magnetic resonance signal distribution estimated using the B1Map transmission field map, and the actual receiving channel image. The ratio of the curve to the ideal magnetic resonance signal distribution is the spatial distribution of the coil sensitivity.

[0104] Step 5: Binarization is performed and a threshold is set to select the foreground region of the pre-corrected image; the binary mask is then saved. ,according to Data from the inner foreground region was used for polynomial fitting to smooth the sensitivity distribution map of each channel. Save the fitted channel sensitivity distribution results as follows (like Figure 5 As shown), the parameter results of the polynomial fitting are saved as a vector. In practice, the mold used usually cannot completely fill all areas within the coil volume, so extrapolation can be performed using polynomial fitting.

[0105] Step 6: Process clinical scan images Sensitivity calibration includes:

[0106] ① The original image obtained from the clinical scan is binarized, and a threshold is set to separate the foreground region of the image. The binary mask of the clinical image is saved as follows. ;

[0107] ② Read the corresponding data based on the receiving coil channel used in the clinical scan image. and ;

[0108] ③ Use the fitted parameters to... The sensitivity distribution map of each receiving channel is calculated in the foreground region. The sensitivity distribution maps of all channels are then merged to obtain the sensitivity calibration map (e.g., ...). Figure 6 (as shown), save as According to the formula Correcting the coil sensitivity distribution of clinical images yields uniform clinical images. .

[0109] In one exemplary embodiment, such as Figure 7 As shown, an image correction method is provided, which includes the following steps:

[0110] Step S301: Obtain a pre-scanned image by scanning the phantom with a multi-flip angle sequence pulse.

[0111] Step S302: Based on the pre-scanned image, obtain the sensitivity amplitude diagram of each receiving channel of the receiving coil under different flip angles;

[0112] Step S303: Determine the sensitivity distribution map of each receiving channel based on the sensitivity amplitude map;

[0113] Step S304: Based on the foreground region of the pre-scanned image, the sensitivity distribution map of each receiving channel is fitted to obtain the sensitivity fitting result and the sensitivity fitting parameters corresponding to the sensitivity fitting result.

[0114] Step S305: Store the sensitivity fitting results and sensitivity fitting parameters;

[0115] Step S306: Obtain a scan image of the sensitivity to be calibrated; the scan image is acquired by a receiving coil, which is equipped with a receiving channel.

[0116] Step S307: Determine the channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel;

[0117] Step S308: Merge the channel sensitivity distribution maps of each receiving channel to obtain the sensitivity calibration map of the receiving coil;

[0118] Step S309: Correct the scanned image based on the sensitivity calibration map to obtain the corrected image corresponding to the scanned image.

[0119] Optionally, the magnetic resonance imaging (MRI) device can use multi-flip-angle sequence pulse scanning with different flip angles to scan a phantom containing a solution of multi-nucleonium ions, obtaining multiple FID signals. Image reconstruction is performed on each FID signal to obtain a pre-scan image. The amplitude map corresponding to all receiving channels in one of the pre-scan images is used as a sensitivity amplitude map. Based on the sensitivity amplitude map and the ideal magnetic resonance signal distribution map estimated based on the emission field distribution map, the sensitivity distribution map of each receiving channel of the receiving coil is obtained. The sensitivity distribution map is fitted based on the foreground region of the pre-scan image to obtain the sensitivity fitting result and sensitivity fitting parameters for each receiving channel of the receiving coil. The MRI device can store the sensitivity fitting result and sensitivity fitting parameters as sensitivity distribution parameters. After acquiring the scan image, the MRI device can read the sensitivity distribution parameters of the receiving channels used in the scan image, determine the sensitivity distribution map of the receiving channels used in the scan image based on the sensitivity distribution parameters, and merge the sensitivity distribution maps of each receiving channel used in the scan image to obtain a sensitivity calibration map of the receiving coil. The MRI device can then perform coil sensitivity non-uniformity correction on the scan image based on the determined sensitivity calibration map of the receiving coil to obtain a corrected image.

[0120] The above-described image correction method can obtain a sensitivity calibration map using predetermined sensitivity distribution parameters after acquiring the scanned image, and then use the sensitivity calibration map to correct the scanned image. Since the predetermined sensitivity distribution parameters are obtained by scanning a phantom with a high nuclide concentration, the correction results can be avoided from being affected by the nuclide concentration, thus improving the accuracy of image correction.

[0121] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0122] Based on the same inventive concept, this application also provides an image correction apparatus for implementing the image correction method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more image correction apparatus embodiments provided below can be found in the limitations of the image correction method described above, and will not be repeated here.

[0123] In one exemplary embodiment, such as Figure 8 As shown, an image correction device is provided, including: an acquisition module 402, a determination module 404, and a correction module 406, wherein:

[0124] The acquisition module 402 is used to acquire a scanned image of the sensitivity to be calibrated; the scanned image is acquired by a receiving coil, and the receiving coil is provided with a receiving channel;

[0125] The determining module 404 is used to determine the sensitivity calibration map of the receiving coil based on the sensitivity distribution parameters of the receiving channel; the sensitivity distribution parameters are obtained by scanning the phantom.

[0126] The calibration module 406 is used to calibrate the scanned image based on the sensitivity calibration map to obtain a calibrated image corresponding to the scanned image.

[0127] In an exemplary embodiment, the determining module 404 is further configured to determine a channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel; and merge the channel sensitivity distribution maps of each receiving channel to obtain the sensitivity calibration map of the receiving coil.

[0128] In an exemplary embodiment, the determining module 404 is further configured to perform fitting processing on the foreground region of the scanned image according to the sensitivity fitting parameters to obtain the channel sensitivity distribution map.

[0129] In an exemplary embodiment, the determining module 404 is further configured to determine the channel sensitivity distribution map of the receiving channel based on the sensitivity fitting result.

[0130] In one exemplary embodiment, the image correction device further includes:

[0131] The scanning simulation module is used to acquire a pre-scanned image obtained by scanning the phantom with multi-flip angle sequence pulses.

[0132] The image reconstruction module is used to obtain the sensitivity amplitude map of each receiving channel of the receiving coil under different flip angles based on the pre-scanned image.

[0133] The parameter calculation module is used to determine the sensitivity distribution parameters of each of the receiving channels based on the sensitivity amplitude diagram.

[0134] In an exemplary embodiment, the phantom comprises a multinucleoside ion solution with a nuclide concentration higher than a preset threshold, and the multi-flip angle sequence pulse includes a first pulse and a second pulse, wherein the flip angle of the first pulse is smaller than the flip angle of the second pulse.

[0135] In an exemplary embodiment, the parameter calculation module is further configured to determine the sensitivity distribution map of each of the receiving channels based on the sensitivity amplitude map; perform fitting processing on the sensitivity distribution map of each of the receiving channels based on the foreground region of the pre-scanned image to obtain a sensitivity fitting result and a sensitivity fitting parameter corresponding to the sensitivity fitting result; and store the sensitivity fitting result and the sensitivity fitting parameter.

[0136] Each module in the aforementioned 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, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0137] In an exemplary embodiment, a magnetic resonance imaging (MRI) device is provided, comprising a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor of the MRI device provides computational and control capabilities. The memory of the MRI device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the MRI device is used for exchanging information between the processor and external devices. The communication interface of the MRI device is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements an image correction method. The display unit of the MRI device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the magnetic resonance device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the outer shell of the magnetic resonance device, or an external keyboard, touchpad, or mouse, etc.

[0138] Those skilled in the art will understand that the above structure is only a part of the structure related to the present application and does not constitute a limitation on the magnetic resonance device to which the present application is applied. The specific magnetic resonance device may include more or fewer components than the above, or combine certain components, or have different component arrangements.

[0139] In one exemplary embodiment, a magnetic resonance device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0140] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above-described method embodiments.

[0141] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0142] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0143] 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 above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0144] 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 application.

[0145] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. 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 application should be determined by the appended claims.

Claims

1. An image correction method, characterized in that, The method includes: A scanned image of the sensitivity to be calibrated is acquired; the scanned image is acquired by a receiving coil, which is equipped with a receiving channel; Based on the sensitivity distribution parameters of the receiving channel, a sensitivity calibration map of the receiving coil is determined; the sensitivity distribution parameters are obtained by scanning a phantom. The scanned image is corrected based on the sensitivity calibration map to obtain the corrected image corresponding to the scanned image.

2. The method according to claim 1, characterized in that, The receiving coil is provided with multiple receiving channels; Determining the sensitivity calibration map of the receiving coil based on the sensitivity distribution parameters of the receiving channel includes: Based on the sensitivity distribution parameters of each receiving channel, determine the channel sensitivity distribution map of each receiving channel; By merging the channel sensitivity distribution maps of each of the receiving channels, the sensitivity calibration map of the receiving coil is obtained.

3. The method according to claim 2, characterized in that, The sensitivity distribution parameters include sensitivity fitting parameters; Determining the channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel includes: Based on the sensitivity fitting parameters, the foreground region of the scanned image is fitted to obtain the channel sensitivity distribution map.

4. The method according to claim 2, characterized in that, The sensitivity distribution parameters include the sensitivity fitting results; Determining the channel sensitivity distribution map of each receiving channel based on the sensitivity distribution parameters of each receiving channel includes: Based on the sensitivity fitting results, the channel sensitivity distribution map of the receiving channel is determined.

5. The method according to claim 1, characterized in that, Before acquiring the scanned image of the sensitivity to be calibrated, the method further includes: The pre-scanned image is obtained by scanning the phantom with a multi-flip angle sequence pulse. Based on the pre-scanned image, the sensitivity amplitude diagrams of each receiving channel of the receiving coil under different flip angles are obtained; Based on the sensitivity amplitude diagram, the sensitivity distribution parameters of each receiving channel are determined.

6. The method according to claim 5, characterized in that, The phantom contains a multinucleoside ion solution with a nuclide concentration higher than a preset threshold. The multi-flip angle sequence pulse includes a first pulse and a second pulse, wherein the flip angle of the first pulse is smaller than that of the second pulse.

7. The method according to claim 5, characterized in that, Determining the sensitivity distribution parameters of each receiving channel based on the sensitivity amplitude diagram includes: Based on the sensitivity amplitude diagram, determine the sensitivity distribution diagram of each of the receiving channels; Based on the foreground region of the pre-scanned image, the sensitivity distribution map of each receiving channel is fitted to obtain the sensitivity fitting result and the sensitivity fitting parameter corresponding to the sensitivity fitting result; Store the sensitivity fitting results and the sensitivity fitting parameters.

8. An image correction device, characterized in that, The device includes: An acquisition module is used to acquire a scanned image of the sensitivity to be calibrated; the scanned image is acquired by a receiving coil, which is provided with a receiving channel; The determination module is used to determine the sensitivity calibration map of the receiving coil based on the sensitivity distribution parameters of the receiving channel; the sensitivity distribution parameters are obtained by scanning the phantom. The calibration module is used to calibrate the scanned image based on the sensitivity calibration map to obtain a calibrated image corresponding to the scanned image.

9. A magnetic resonance imaging (MRI) 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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