A Passive Shimming Optimization Design Method and System for Superconducting Magnetic Resonance Magnets

Abstract

The present invention provides a passive shimming optimization design method and system for a superconducting magnetic resonance magnet, belonging to the technical field of superconducting magnet system optimization. The method includes: obtaining n groups of bare magnetic fields to be shimmed by Monte Carlo simulation of the magnetic field drift caused by the tolerances of geometric parameters and electromagnetic parameters; selecting the value ranges of four shimming factors according to the magnet size requirements to construct a DOE test group; using the binary improved OTMF algorithm for each test group, with the minimum total thickness of shimming sheets as the objective function, to shim the bare magnetic field with the largest non-uniformity; selecting several shimming design methods according to the shimming results; respectively shimming the n groups of bare magnetic fields to be shimmed under several shimming design methods; and selecting the shimming design method with the best shimming effect as the best passive shimming optimization design. The present invention completes the passive shimming optimization of the superconducting magnetic resonance magnet by designing four shimming factors.

Description

Technical Field

[0001] The present invention belongs to the technical field of superconducting magnet system optimization, and more specifically, relates to a passive shimming optimization design method and system for a superconducting magnetic resonance magnet. Background Art

[0002] Magnetic resonance imaging system (MRI) is an important medical imaging device in modern clinical diagnosis. The magnetic field strength and uniformity of the central spherical imaging region (Diameter of spherical volume, DSV) determine the imaging quality. However, due to factors such as manufacturing, engineering installation, and coil material tolerances, the magnetic field strength in the central spherical imaging region is prone to change, making it difficult to achieve high-quality imaging requirements for the uniformity in the DSV region. Therefore, shimming techniques are often used to correct the non-uniformity in the DSV region. The shimming methods of the MRI system mainly include two methods: active shimming method and passive shimming method. Compared with the active shimming method that requires energizing the shimming coil to generate a corrective magnetic field, passive shimming does not require additional power supply and coils, and only relies on shimming plates placed in the magnet cavity to generate a corrective magnetic field. Compared with the active shimming technique, passive shimming has the advantages of low cost and simple operation.

[0003] In the existing magnetic resonance passive shimming methods, the overall thickness of the iron sheet is used as the objective function, and the peak-to-peak magnetic field non-uniformity or the root mean square value of the magnetic field uniformity is used as the constraint, achieving a good shimming effect under fixed shimming design parameters, but no method for optimizing the design of passive shimming parameters for warm-hole type MRI is given. There are also some patents that propose a two-step shimming strategy for fine shimming, that is, a shimming operation method, but no method for optimizing the design of passive shimming parameters for warm-hole type MRI is mentioned. Chinese Patent Publication No. CN 114970861 A proposes a design method for passive shimming of an open MRI, and determines shimming design parameters such as coil thickness and coil width through a genetic algorithm, but its object is an open MRI, and no method for optimizing the design of passive shimming parameters for warm-hole type MRI is mentioned. Therefore, the passive shimming techniques proposed in the existing inventions are new technologies in terms of new structures, shimming operations, or shimming algorithms, and no method for optimizing the design of passive shimming parameters for warm-hole type MRI is mentioned.

[0004] Therefore, there is an urgent need to provide a passive shimming optimization design method for a superconducting magnetic resonance magnet that designs shimming parameters such as the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of the shimming plates, and the spacing between the shimming plates. Summary of the Invention

[0005] Aiming at the defects of the existing technology, the purpose of the present invention is to provide a method and system for optimizing the passive shimming of a superconducting magnetic resonance magnet, aiming to solve the problem of how to design the optimal parameters of the four shimming factors, namely the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of the shimming plates, and the spacing between the shimming plates, so as to optimize the passive shimming of the superconducting magnetic resonance magnet.

[0006] To achieve the above object, the present invention provides a method for optimizing the passive shimming of a superconducting magnetic resonance magnet, including the following steps:

[0007] S1: Given the geometric parameters and electromagnetic parameters of the superconducting magnet to be shimmed;

[0008] S2: Through Monte Carlo simulation, obtain the magnetic field drift caused by the tolerances of the geometric parameters and electromagnetic parameters, and obtain n groups of bare magnetic fields to be shimmed;

[0009] S3: According to the requirements of the magnet size, select the value ranges of the four shimming factors, namely the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of the shimming plates, and the spacing between the shimming plates, and construct a DOE experimental group;

[0010] S4: For each experimental group, use the binary improved OTMF algorithm, with the minimum total thickness of the shimming plates as the objective function, to shim the bare magnetic field with the largest non-uniformity, and obtain the non-integer solutions of the DOE (Design of Experiment) experimental group;

[0011] S5: Select several shimming design methods according to the shimming results of the DOE experimental group;

[0012] S6: Under several shimming design methods respectively, shim the n groups of bare magnetic fields to be shimmed, and obtain the integer solutions of the n groups of bare magnetic fields;

[0013] S7: Select the shimming design method with the best integer shimming effect as the best passive shimming optimization design.

[0014] Further preferably, the geometric parameters include the cylindrical size where the shimming bars are placed, the thickness of a single shimming plate, and the maximum thickness of the shimming plates; the electromagnetic parameters include the number of superconducting coils of the bare solenoid, the positional relationship of the superconducting coils of the bare solenoid, and the material of the superconducting wire.

[0015] Further preferably, the OTMF model in the OTMF algorithm is:

[0016] Min:Lx′

[0017]

[0018] Wherein, x′ = [x1, x2, …, x M ,B t ​T , where \(t\) is the maximum thickness that the cavity can accommodate the shimming plate, \(\kappa\) is the coefficient for controlling the target magnetic field, and \(B\) avr is the average magnetic field intensity of the bare magnetic field corresponding to the group with the largest bare magnetic field non-uniformity; \(L = [1, \ldots, 1]\), which is an \((M + 1)\times1\) identity matrix; the sensitivity coefficient matrices \(A'\) and \(A''\) can be expressed as:

[0019]

[0020]

[0021] \(x = [x_1, x_2, \ldots, x\) M T , where \(x\) i represents the thickness of the shimming plate in the \(i\)-th cavity; \(B\) m is the bare magnetic field corresponding to the group with the largest bare magnetic field non-uniformity; \(B\) t is the target magnetic field; \(A\) i,j is the magnetic field in the \(z\)-axis direction generated by a unit thickness shimming plate in the \(j\)-th cavity at the \(i\)-th sampling point; \(\varepsilon\) is the maximum allowable non-uniformity.

[0022] Further preferably, the specific implementation method of the binary improved OTMF algorithm includes the following steps:

[0023] a. Initialize \(\varepsilon\) min \(= 0\), \(\varepsilon\) max \(= H_0\), where \(H_0\) is the non-uniformity of the DSV region before shimming; \(\varepsilon\) min is the minimum value of the maximum allowable non-uniformity; \(\varepsilon\) max is the maximum value of the maximum allowable non-uniformity;

[0024] b. Take and substitute it into the OTMF model for solution;

[0025] c. If there is no solution, it indicates that the minimum value \(H\) min of the non-uniformity of the DSV region is larger than \(\varepsilon\). Let \(\varepsilon\) min \(= \varepsilon\), and go to step b;

[0026] d. If there is a solution, it indicates that the maximum value \(H\) min of the non-uniformity of the DSV region is smaller than \(\varepsilon\). Let \(\varepsilon\) max \(= \varepsilon\); if \(\varepsilon\) max - \(\varepsilon\) min \(\leq 10\) -7 then it indicates that the non-uniformity of the DSV region reaches the set precision value, and the OTMF algorithm ends. Otherwise, go to step b;

[0027] Among them, the calculation formula for the non-uniformity of the DSV region is:

[0028] ​

[0029] Among them, A is a sensitivity coefficient matrix of size N×M; M is the total number of cavities; N is the number of sampling points; A i,j is the magnetic field in the z-axis direction generated by the shimming sheet with unit thickness in the j-th cavity at the i-th sampling point.

[0030] On the other hand, the present invention provides a passive shimming optimization design system for a superconducting magnetic resonance magnet, including:

[0031] A parameter setting module for setting the geometric parameters and electromagnetic parameters of the superconducting magnet to be shimmed;

[0032] A bare magnetic field group determination module for obtaining n groups of bare magnetic fields to be shimmed by Monte Carlo simulation of the magnetic field drift caused by the tolerances of geometric parameters and electromagnetic parameters;

[0033] A DOE test group construction module for constructing a DOE test group by selecting the value ranges of four shimming factors, namely the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of the shimming sheet, and the spacing between shimming sheets, according to the magnet size requirements;

[0034] A non-integer solution shimming module for shimming the non-uniformity-maximum bare magnetic field with the minimum total thickness of the shimming sheet as the objective function for each test group in the DOE by using the binary improved OTMF algorithm to obtain the non-integer solutions of the DOE test group;

[0035] An initial shimming design scheme screening module for selecting several shimming design methods according to the shimming results of the DOE test group;

[0036] An integer solution shimming module for shimming the n groups of bare magnetic fields to be shimmed under several shimming design methods respectively to obtain the integer solutions of the n groups of bare magnetic fields;

[0037] A best passive shimming optimization design screening module for selecting the shimming design method with the best integer shimming effect as the best passive shimming optimization design.

[0038] Further preferably, the geometric parameters include the cylindrical size where the shimming bars are placed, the thickness of a single shimming sheet, and the maximum thickness of the shimming sheet; the electromagnetic parameters include the number of superconducting coils of the bare solenoid, the positional relationship of the superconducting coils of the bare solenoid, and the material of the superconducting wire.

[0039] Further preferably, the OTMF model in the OTMF algorithm is:

[0040] Min: Lx′

[0041]

[0042] where x′ = [x1, x2, …, xM , B t T , where t is the maximum thickness that the cavity can accommodate the shimming sheet, κ is the coefficient for controlling the target magnetic field, B avr is the average magnetic field intensity of the bare magnetic field corresponding to the group with the largest bare magnetic field non-uniformity; L = [1, …, 1], i.e., the (M + 1) × 1 identity matrix; x = [x1, x2, …, x M T , x i represents the thickness of the shimming sheet in the i-th cavity; B m is the bare magnetic field corresponding to the group with the largest bare magnetic field non-uniformity; B t is the target magnetic field; A i,j is the magnetic field in the z-axis direction generated by the shimming sheet with unit thickness in the j-th cavity at the i-th sampling point; ε is the maximum allowable non-uniformity; the sensitivity coefficient matrices A′ and A″ can be expressed as:

[0043]

[0044]

[0045] Further preferably, the specific implementation method of the binary improved OTMF algorithm includes the following steps:

[0046] a. Initialize ε min = 0, ε max = H0; where H0 is the non-uniformity of the DSV region before shimming; ε min is the minimum value of the maximum allowable non-uniformity; ε max is the maximum value of the maximum allowable non-uniformity;

[0047] b. Take and substitute it into the OTMF model for solution;

[0048] c. If there is no solution, it indicates that the minimum value H min of the non-uniformity of the DSV region is greater than ε, let ε min = ε, and go to step b;

[0049] d. If there is a solution, it indicates that the maximum small value H min of the non-uniformity of the DSV region is less than ε, let ε max = ε; if ε max - ε min ≤ 10 -7 it indicates that the non-uniformity of the DSV region reaches the set precision value, and the OTMF algorithm ends, otherwise go to step b;

[0050] Among them, the calculation formula for the non-uniformity of the DSV region is:

[0051] ​​

[0052] Among them, A is a sensitivity coefficient matrix of size N×M; M is the total number of cavities; N is the number of sampling points; A i,j is the magnetic field in the z-axis direction generated by a uniform field sheet with a unit thickness in the j-th cavity at the i-th sampling point.

[0053] Generally speaking, compared with the prior art, the above technical solution conceived by the present invention has the following

[0054] beneficial effects:

[0055] The present invention provides a method for optimizing the passive shimming design of a superconducting magnetic resonance magnet. Among them, according to the magnet size requirements, the value ranges of four shimming factors, namely, the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of the shimming sheet, and the spacing between shimming sheets, are selected to construct a DOE experimental group; based on this, the optimal passive shimming design is obtained in two steps. In the first step, for each experimental group of the DOE, the binary improved OTMF algorithm is used to shim the bare magnetic field with the largest non-uniformity with the minimum total thickness of the shimming sheet as the objective function to obtain a non-integer solution; in the second step, under several shimming design methods, n groups of bare magnetic field groups to be shimmed are shimmed, and the shimming design method with the best integer shimming effect is selected as the optimal passive shimming design. The present invention completes the passive shimming optimization of the superconducting magnetic resonance magnet by designing the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of the shimming sheet, and the spacing between shimming sheets. With an optimal passive shimming design of a 1.5T superconducting magnet, excellent magnetic field uniformity is obtained, and a uniformity of nearly 0.5 ppm can be generated.

[0056] The method for optimizing the passive shimming design of the superconducting magnetic resonance magnet provided by the present invention, wherein for each experimental group of the DOE, the binary improved OTMF algorithm is used to shim the bare magnetic field with the largest non-uniformity with the minimum total thickness of the shimming sheet as the objective function, realizing simple installation and the lowest cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 is a flowchart of the passive shimming optimization design of the superconducting magnetic resonance magnet provided by the embodiment of the present invention;

[0058] Figure 2 is a schematic diagram of Monte Carlo simulation tolerances provided by the embodiment of the present invention;

[0059] Figure 3 is a statistical chart of the magnetic field drift of 1000 groups of Monte Carlo simulations provided by the embodiment of the present invention;

[0060] Figure 4 is a schematic diagram of the magnetic field coordinate system provided by the embodiment of the present invention;

[0061] Figure 5 Group G with the largest non-uniformity of the bare magnetic field provided by the embodiments of the present invention max Magnetic field distribution diagram;

[0062] Figure 6 Flow chart of the binary improved OTMF algorithm provided by the embodiments of the present invention;

[0063] Figure 7 DOE test result diagram provided by the embodiments of the present invention;

[0064] Figure 8 Statistical chart of the shimming effects of 1000 groups of three sets of solutions provided by the embodiments of the present invention. Detailed implementation manners

[0065] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0066] Now, one or more aspects of the present invention are summarized for facilitating the basic understanding of the present invention, where this summary is not an extensive overview of the present invention, and is not intended to identify certain elements of the present invention, nor to delimit its scope. On the contrary, the main purpose of this summary is to present some concepts of the present invention in a simplified form before presenting a more detailed description below.

[0067] Embodiment 1

[0068] As Figure 1 shown, the embodiments of the present invention provide a method for optimizing the passive shimming design of a superconducting magnetic resonance magnet, including the following steps:

[0069] S1: Obtain the geometric parameters of a 1.5T functional magnetic resonance imaging superconducting magnet system, as shown in Table 1; among them, the shimming bars need to be placed on the inner surface of a cylinder with a radius of 24.99 cm and a length of 120 cm; the thickness of a single shimming sheet is 0.05 mm, and the maximum thickness of the shimming sheet is set to 6 mm;

[0070] And obtain the electromagnetic design parameters of a 1.5T functional magnetic resonance imaging superconducting magnet system, as shown in Table 2; among them, the 1.5T functional magnetic resonance imaging superconducting magnet system is composed of 10 bare solenoid superconducting coils; B+ / B-, L+ / L-, M+ / M-, S+ / S- and C+ / C- are symmetric about the z-axis (where the xyz coordinate system is the Cartesian coordinate system), forming coil pairs, and the superconducting wire is NbTi wire;

[0071] Table 1

[0072] Magnetic field strength 1.5T DSV diameter 20 cm Radius of the cylindrical surface where the shimming bars are placed 24.99 cm Length of the cylindrical surface where the shimming bars are placed 120 cm Thickness of a single shimming sheet 0.05 mm Maximum thickness of the shimming sheet 6 mm

[0073] Table 2

[0074]

[0075] S2: Obtain n groups of raw magnetic field groups G to be shimmed by Monte Carlo simulation of the magnetic field drift caused by parameter tolerances, and denote the group with the largest non-uniformity as G n , and denote the group with the largest non-uniformity as G max ;

[0076] Figure 2 is a schematic diagram of tolerance generation. Among them, since the tolerance in the production of NbTi wire is the wire tolerance, its tolerance distribution is a uniform distribution U(-0.015, 0.015) with a mean equal to 0.015 mm; while the tolerance caused by the wire installation position is the position tolerance, and its tolerance distribution is a normal distribution N[0, (0.254 / 3) 2 ; 1000 groups of magnetic field drift test groups G caused by tolerances were simulated by Monte Carlo, as n shown; the peak-to-peak non-uniformity of the magnetic field caused by tolerances is concentrated between 50 ppm and 750 ppm, and the average peak non-uniformity is 310.3094 ppm; among them, the uniformity of the group G Figure 3 with the largest non-uniformity of the raw magnetic field is 1199.2373 ppm, and the magnetic field distribution is as max shown in Figure 5 ;

[0077] S3: According to the geometric constraints of the magnet, the value ranges of the four main shimming factors, namely the number of toroidal shimming bars selected, the number of cavities in each shimming bar, the size of the shimming plates, and the spacing between the shimming plates, are shown in Table 3; among them, three specifications of large, medium, and small (z-direction length × phi-direction length × single-piece thickness) are selected for the size of the shimming plates; at the same time, since the spacing between the shimming plates is a discrete quantity, three levels of 3.5 cm, 7 cm, and 10 cm are also selected for the spacing; the number of cavities in each shimming bar is incremented from 2 to explore, and the total cavity length of each shimming bar needs to be less than 120 cm; the number of toroidal shimming bars is selected at four levels of 10, 16, 24, and 32, and the corresponding DOE test level combinations can be obtained from this;

[0078] Table 3

[0079]

[0080] S4: Collect the raw magnetic field B max of the group G m with the largest non-uniformity of the raw magnetic field through a Hall probe. Let the number of DSV acquisition points be N, then B m can be expressed as [B1, B2, B3, …, B N; At any point in space, the magnetic field contribution of a unit - volume shimming sheet to the sampling points in the DSV region can be measured or calculated; Taking the center of the DSV region as the origin, a coordinate system is established as shown in Figure 4 , where point Q represents the center point of any shimming sheet, and point P represents any sampling point in the DSV region; Then The magnetic field dB in the z - axis direction at point P(r,θ,φ) contributed by a unit - volume shimming sheet at a certain point z can be calculated by formula (1):

[0081]

[0082] where μ0 is the vacuum permeability, M z is the magnetization intensity of the shimming sheet, ε m is the Neuman factor, represents the associated Legendre function; dV is the unit - volume element; n is the order of the Legendre function; m is the Legendre - function series; r is the radius of the DSV region;

[0083]

[0084] The sensitivity - coefficient matrix A of size N×M can be calculated from formulas (1) and (2); where M is the total number of cavities; N is the number of sampling points; A i,j is the magnetic field in the z - axis direction generated by a unit - thickness shimming sheet in the j - th cavity at the i - th sampling point; Introducing the total - thickness decision vector x of length M of the shimming sheet and the target magnetic field B t , the linear optimization model of passive shimming can be obtained; where x = [x1,x2,…,x M T , x i represents the thickness of the shimming sheet in the i - th cavity, then the non - uniformity H can be expressed as:

[0085]

[0086] where ε is the maximum allowable non - uniformity;

[0087] Introducing B t into the decision variable x, the OTMF model is obtained, which can be expressed as:

[0088] Min: Lx′

[0089]

[0090] where x′ = [x1,x2,…,x M ,B t T ​​, where t is the maximum thickness of the cavity that can accommodate the shimming sheet, κ is the coefficient for controlling the target magnetic field, and B avr is the average magnetic field strength of the bare magnetic field corresponding to the group with the largest bare magnetic field non-uniformity; L = [1,…,1], i.e., the (M + 1)×1 identity matrix; the sensitivity coefficient matrices A′ and A″ can be expressed as:

[0091]

[0092] Then the binary improved OTMF algorithm process is as Figure 6 shown as follows:

[0093] a. Initialize ε min = 0, ε max = H0, where H0 is the non-uniformity of the DSV region before shimming;

[0094] b. Take and substitute it into the OTMF model for solution;

[0095] c. If there is no solution, it indicates that the minimum value H min of the non-uniformity of the DSV region is larger than ε, that is, H min is between ε and ε max , so let ε min = ε, and go to step b;

[0096] d. If there is a solution, it indicates that the minimum value H min of the non-uniformity of the DSV region is smaller than ε, that is, H min is between 0 and ε, so let ε max = ε; if at this time ε max - ε min ≤ 10 -7 , that is, the set precision value is reached, the algorithm ends; if the set precision value is not reached, go to step b;

[0097] S5: According to the shimming results of the DOE test group, initially select 3 shimming design methods; more specifically as follows:

[0098] The shimming results of the DOE test group are as Figure 7 shown, where: (1) Considering the convergence rate and the total volume of shimming sheets consumed when just reaching the convergence length, it is better to select the number of circumferential shimming bars as 24; (2) The number of cavities should be selected according to the shimming sheet size and spacing; if the number is too large, the total volume of shimming sheets consumed increases, so it is better when just reaching the convergence length; based on the above shimming results of the DOE test group, three sets of shimming design methods are initially selected, as shown in Table 4;

[0099] Table 4

[0100]

[0101] S6: For the three sets of shimming design methods initially selected, use the binary improved OTMF algorithm to perform shimming on these 1000 groups of magnetic field drift test groups G n respectively; and perform integerization processing on the results to obtain the shimming effects of the three methods under integer solutions as Figure 8 shown; under the 1st shimming design method, the average peak-to-peak non-uniformity after shimming for 1000 test groups is 0.4346 ppm, and the peak-to-peak non-uniformity after shimming for 99% of the test groups is less than 0.5 ppm, with the best shimming effect;

[0102] S7: Select the 1st shimming design method as the best passive shimming optimization design, and the parameters are shown in Table 5;

[0103] Table 5

[0104]

[0105] Example 2

[0106] The embodiment of the present invention provides a passive shimming optimization design system for a superconducting magnetic resonance magnet, including:

[0107] A parameter setting module for setting the geometric parameters and electromagnetic parameters of the superconducting magnet to be shimmed;

[0108] A bare magnetic field group determination module for obtaining n groups of bare magnetic fields to be shimmed by Monte Carlo simulation of the magnetic field drift caused by the tolerances of geometric parameters and electromagnetic parameters;

[0109] A DOE test group construction module for selecting the value ranges of four shimming factors, namely the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of shimming sheets, and the spacing between shimming sheets, according to the magnet size requirements, and constructing DOE test groups;

[0110] A non-integer solution shimming module for using the binary improved OTMF algorithm for each DOE test group, with the minimum total thickness of shimming sheets as the objective function, to perform shimming on the bare magnetic field with the largest non-uniformity, and obtaining non-integer solutions of the DOE test groups;

[0111] An initial shimming design scheme screening module for selecting several shimming design methods according to the shimming results of DOE test groups;

[0112] An integer solution shimming module for performing shimming on n groups of bare magnetic fields to be shimmed respectively under several shimming design methods to obtain integer solutions of n groups of bare magnetic fields;

[0113] A best passive shimming optimization design screening module for selecting the shimming design method with the best integer shimming effect as the best passive shimming optimization design.

[0114] Further preferably, the geometric parameters include the cylindrical size where the shimming bars are placed, the thickness of a single shimming sheet, and the maximum thickness of the shimming sheets; the electromagnetic parameters include the number of superconducting coils of the bare solenoid, the positional relationship of the superconducting coils of the bare solenoid, and the material of the superconducting wire.

[0115] Further preferably, the OTMF model in the OTMF algorithm is:

[0116] Min: Lx′

[0117]

[0118] where x′ = [x1, x2, …, x M , B t T , t is the maximum thickness that the cavity can accommodate the shimming sheets, κ is the coefficient for controlling the target magnetic field, B avr is the average magnetic field strength of the bare magnetic field corresponding to the group with the largest bare magnetic field inhomogeneity; L = [1, …, 1], that is, the (M + 1) × 1 identity matrix; x = [x1, x2, …, x M T , x i represents the thickness of the shimming sheet in the i-th cavity; B m is the bare magnetic field corresponding to the group with the largest bare magnetic field inhomogeneity; B t is the target magnetic field; A i,j is the magnetic field in the z-axis direction generated by the shimming sheet with unit thickness in the j-th cavity at the i-th sampling point; ε is the maximum allowable inhomogeneity; the sensitivity coefficient matrices A′ and A″ can be expressed as:

[0119]

[0120]

[0121] Further preferably, the specific implementation method of the binary improved OTMF algorithm includes the following steps:

[0122] a. Initialize ε min = 0, ε max = H0; where H0 is the inhomogeneity of the DSV region before shimming; ε min is the minimum value of the maximum allowable inhomogeneity; ε max is the maximum value of the maximum allowable inhomogeneity;

[0123] b. Substitute into the OTMF model for solution;

[0124] c. If there is no solution, it indicates that the minimum value H min of the inhomogeneity of the DSV region is larger than ε, let ε min ​​= ε, go to step b;

[0125] d. If there is a solution, it indicates that the maximum and minimum H of the non-uniformity of the DSV region min is smaller than ε, let ε max = ε; if ε max - ε min ≤ 10 -7 it indicates that the non-uniformity of the DSV region reaches the set precision value, and the OTMF algorithm ends. Otherwise, go to step b;

[0126] Among them, the calculation formula for the non-uniformity of the DSV region is:

[0127]

[0128] Among them, A is the sensitivity coefficient matrix of size N×M; M is the total number of cavities; N is the number of sampling points; A i,j is the magnetic field in the z-axis direction generated by the uniform field sheet with unit thickness in the j-th cavity for the i-th sampling point.

[0129] In summary, compared with the prior art, the present invention has the following advantages:

[0130] The present invention provides a method for optimizing the passive shimming design of a superconducting magnetic resonance magnet. Among them, according to the magnet size requirements, the value ranges of four shimming factors, namely the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of the shimming sheet, and the spacing between shimming sheets, are selected to construct a DOE experimental group; based on this, the best passive shimming optimization design is obtained in two steps. In the first step, for each experimental group of DOE, the binary improved OTMF algorithm is used to shim the bare magnetic field with the largest non-uniformity with the objective of minimizing the total thickness of the shimming sheets, and a non-integer solution is obtained; in the second step, under several shimming design methods, the n groups of bare magnetic field groups to be shimmed are shimmed, and the shimming design method with the best integer shimming effect is selected as the best passive shimming optimization design. The present invention completes the passive shimming optimization of the superconducting magnetic resonance magnet by designing the number of circumferential shimming bars, the number of cavities in each shimming bar, the size of the shimming sheet, and the spacing between shimming sheets. With an optimal passive shimming design of a 1.5T superconducting magnet, excellent magnetic field uniformity is obtained, and a uniformity of nearly 0.5 ppm can be generated.

[0131] The method for optimizing the passive shimming design of the superconducting magnetic resonance magnet provided by the present invention uses the binary improved OTMF algorithm for each experimental group of DOE to shim the bare magnetic field with the largest non-uniformity with the objective of minimizing the total thickness of the shimming sheets, realizing simple installation and the lowest cost.

[0132] Those skilled in the art can easily understand that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included within the protection scope of the present invention.

Claims

1. A passive shimming optimization design method for a superconducting magnetic resonance magnet, characterized in that, It includes the following steps: S1: Given the geometric parameters and electromagnetic parameters of the superconducting magnet to be shimmed; S2: Obtain the bare magnetic field group to be shimmed by Monte Carlo simulation of the magnetic field drift caused by the tolerances of geometric parameters and electromagnetic parameters, and obtain n a group of bare magnetic fields to be shimmed; S3: According to the magnet size requirements, select the value ranges of four shimming factors, namely the number of toroidal shimming bars, the number of cavities in each shimming bar, the size of the shimming plates, and the spacing between the shimming plates, to construct a DOE test group; S4: For each DOE test group, use the binary improved OTMF algorithm, with the minimum total thickness of the shimming plates as the objective function, to shim the non-uniformity of the maximum unshimmed magnetic field, and obtain the non-integer solutions of the DOE test group; S5: Select several shimming design methods according to the shimming results of the DOE test group; S6: Under several shimming design methods respectively, shim the n group of bare magnetic fields to be shimmed, and obtain n groups of integer solutions of the bare magnetic fields; S7: Select the shimming design method with the best integer shimming effect as the best passive shimming optimization design; The specific implementation method of the binary improved OTMF algorithm includes the following steps: a. Initialization , ; wherein, is the inhomogeneity of the DSV region before shimming; is the minimum value of the allowable maximum inhomogeneity; is the maximum value of the allowable maximum inhomogeneity; b. Take , substitute it into the OTMF model for solution; c. If there is no solution, it indicates that the minimum value of the non-uniformity of the DSV region is larger than . Let , and go to step b; d. If there is a solution, it indicates the minimum value of the non-uniformity of the DSV region is smaller than . Let ; If it indicates that the non-uniformity of the DSV region reaches the set precision value, and the OTMF algorithm ends. Otherwise, go to step b.

2. The passive shimming optimization design method of the superconducting magnetic resonance magnet according to claim 1, wherein The geometric parameters include the cylindrical size where the shimming bars are placed, the thickness of a single shimming plate, and the maximum thickness of the shimming plates; the electromagnetic parameters include the number of superconducting coils in the bare solenoid, the positional relationship of the superconducting coils in the bare solenoid, and the material of the superconducting wire.

3. The passive shimming optimization design method of the superconducting magnetic resonance magnet according to claim 1 or 2, characterized in that, The OTMF model in the OTMF algorithm is: Among them, , t is the maximum thickness of the cavity that can accommodate the shimming sheet, is the coefficient for controlling the target magnetic field, is the average magnetic field strength of the bare magnetic field corresponding to the group with the largest bare magnetic field inhomogeneity; , and is the identity matrix; , represents the i thickness of the shimming sheet in the th cavity; is the target magnetic field; is the j th cavity, and the magnetic field generated by the shimming sheet with unit thickness in the i th cavity at the z axis direction; is the allowable maximum inhomogeneity; the sensitivity coefficient matrix and can be expressed as: 。 4. The passive shimming optimization design method of the superconducting magnetic resonance magnet according to claim 3, characterized in that The calculation formula for the non-uniformity of the DSV region is: Among them, A is the sensitivity coefficient matrix.

5. A passive shimming optimization design system for a superconducting magnetic resonance magnet, characterized in that, It includes: A parameter setting module for given the geometric parameters and electromagnetic parameters of the superconducting magnet to be shimmed; A bare magnetic field group determination module, which is used to obtain, through Monte Carlo simulation, the magnetic field drift caused by the tolerances of geometric parameters and electromagnetic parameters, and obtain n a group of bare magnetic fields to be shimmed; A DOE test group construction module for selecting the value ranges of four shimming factors, namely the number of toroidal shimming bars, the number of cavities in each shimming bar, the size of the shimming plates, and the spacing between the shimming plates, according to the magnet size requirements, to construct a DOE test group; A non-integer solution shimming module for using the binary improved OTMF algorithm for each DOE test group, with the minimum total thickness of the shimming plates as the objective function, to shim the non-uniformity of the maximum unshimmed magnetic field, and obtain the non-integer solutions of the DOE test group; An initial shimming design scheme screening module for selecting several shimming design methods according to the shimming results of the DOE test group; The integer solution shimming module is used to perform shimming on n groups of raw magnetic fields to be shimmed under several shimming design methods respectively, and obtain n groups of integer solutions of the raw magnetic fields; A best passive shimming optimization design screening module for selecting the shimming design method with the best integer shimming effect as the best passive shimming optimization design; The specific implementation method of the binary improved OTMF algorithm includes the following steps: a. Initialization , ; where is the inhomogeneity of the DSV region before shimming; is the minimum value of the maximum allowable inhomogeneity; is the maximum value of the maximum allowable inhomogeneity; b. Take , substitute it into the OTMF model for solution; c. If there is no solution, it indicates that the minimum value of the non-uniformity of the DSV region is greater than . Let , and go to step b; d. If there is a solution, it indicates the maximum and minimum of the non-uniformity of the DSV region ratio is small. Let ; If then it indicates that the non-uniformity of the DSV region reaches the set precision value, and the OTMF algorithm ends. Otherwise, go to step b.

6. The passive shimming optimization design system of the superconducting magnetic resonance magnet according to claim 5, characterized in that The geometric parameters include the cylindrical size where the shimming bars are placed, the thickness of a single shimming plate, and the maximum thickness of the shimming plates; the electromagnetic parameters include the number of superconducting coils in the bare solenoid, the positional relationship of the superconducting coils in the bare solenoid, and the material of the superconducting wire.

7. The passive shimming optimization design system for superconducting magnetic resonance magnets according to claim 5 or 6, characterized in that The OTMF model in the OTMF algorithm is: Among them, , t is the maximum thickness of the shimming plate that the cavity can accommodate, is the coefficient for controlling the target magnetic field, is the average magnetic field intensity of the bare magnetic field corresponding to the group with the largest bare magnetic field inhomogeneity; , is the identity matrix; , represents the i thickness of the shimming plate in the th cavity; is the bare magnetic field corresponding to the group with the largest bare magnetic field inhomogeneity; is the target magnetic field; is the magnetic field generated by the shimming plate with unit thickness in the j th cavity in the i th sampling point in the z axis direction; is the allowable maximum inhomogeneity; The sensitivity coefficient matrix and can be expressed as: 。 8. The passive shimming optimization design system for a superconducting magnetic resonance magnet according to claim 7, wherein The calculation formula for the non-uniformity of the DSV region is: Among them, A is the sensitivity coefficient matrix.

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