Gradient coil optimization design method and device for neonatal magnetic resonance imaging system

Abstract

The application discloses a gradient coil optimization design method and device of a neonatal magnetic resonance imaging system, and relates to the technical field of nuclear magnetic resonance imaging. The method comprises the following steps: obtaining inductance matrix and resistance matrix of each coil in the gradient coil by using a target field method; constructing a linear optimization model based on the inductance matrix and the resistance matrix, and calculating a Tikhonov explicit initial solution of the linear optimization model; constructing a nonlinear optimization model based on the Tikhonov explicit initial solution, a first proportional factor and a second proportional factor representing different weight sensitivities in relative linearity and absolute linearity, and calculating current density expansion coefficients of each coil in the gradient coil according to the nonlinear optimization model; obtaining flow functions of each coil based on the current density expansion coefficients, and determining wiring tracks of each coil according to a contour map corresponding to the flow functions. The method can effectively consider the relative linearity and the absolute linearity, and improve the performance and applicability of the gradient coil.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nuclear magnetic resonance imaging, in particular to a gradient coil optimization design method and device for a neonatal magnetic resonance imaging system. BACKGROUND

[0002] In neonatal medical treatment, magnetic resonance imaging plays an irreplaceable role, which can identify early brain injury and developmental abnormalities through a non-invasive manner, and provides key imaging basis for the neural function evaluation of high-risk neonates. Compared with traditional high-field superconducting systems, low-field permanent magnetic resonance systems have advantages of light weight, low power consumption and compactness, and are more suitable for clinical scenarios of neonatal intensive care units, but their special structure also brings severe challenges to gradient coil design, such as that the small size of the pole plate significantly compresses the available diameter space of the gradient coil, and the narrow physical gap between the pole rings strictly limits the total thickness of the coil.

[0003] At present, the related art uses a single index of relative linearity or absolute linearity to design the gradient coil, and the two standards may lead to different current density distributions and coil topological structures in the optimization process, such as that pursuing high relative linearity will sacrifice the overall field uniformity, and giving priority to absolute linearity will ignore the error control of local key areas, which is difficult to achieve global optimization under multi-physical field constraints in compact design. SUMMARY

[0004] In view of the above defects or deficiencies in the related art, it is expected to provide a gradient coil optimization design method and device for a neonatal magnetic resonance imaging system, which can take into account the relative linearity and absolute linearity, and improve the performance and applicability of the gradient coil.

[0005] In a first aspect, the present application provides a gradient coil optimization design method for a neonatal magnetic resonance imaging system, the neonatal magnetic resonance imaging system comprising a first structure and a second structure symmetrically distributed above and below a permanent magnet, an imaging region being between the first structure and the second structure, each structure comprising a pole plate, a pole ring located at the edge of the pole plate, and an anti eddy current plate and a gradient coil arranged in the pole ring groove, the gradient coil optimization design method comprising:

[0006] obtaining an inductance matrix and a resistance matrix of each coil in the gradient coil by using a target field method;

[0007] constructing a linear optimization model based on the inductance matrix and the resistance matrix, and calculating a Tikhonov explicit initial solution of the linear optimization model;

[0008] A nonlinear optimization model is constructed based on the Tikhonov explicit initial solution, the first scaling factor and the second scaling factor representing different weight sensitivities in relative linearity and absolute linearity, and the current density expansion coefficient of each coil in the gradient coil is calculated according to the nonlinear optimization model.

[0009] The current density expansion coefficient is used to obtain the flow function of each coil, and the wiring trajectory of each coil is determined according to the contour plot corresponding to the flow function.

[0010] Optionally, in some embodiments of this application, obtaining the inductance matrix and resistance matrix corresponding to the gradient coil using the target field method includes:

[0011] On the design plane of the gradient coil, the current density distribution is discretized along the radial and angular directions respectively, and the magnetic induction intensity at each target point in the imaging region, as well as the magnetic energy storage energy and power loss of the system, are calculated based on the current density distribution.

[0012] The inductance matrix and resistance matrix are obtained based on the magnetic energy storage energy and power loss.

[0013] Optionally, in some embodiments of this application, the inductance matrix L is obtained by the following formula:

[0014]

[0015] The inductance transformation matrix can be expressed as:

[0016]

[0017] E represents the energy stored in the magnetic field, ρ0 represents the minimum radius of the gradient coil, and ρ m This represents the maximum radius of the gradient coil, where a and b represent... The subscript value, U q denoted by , where Q represents the order of the current density expansion, μ0 represents the free permeability, and U represents the current density expansion coefficient.

[0018]

[0019] β = qc(ρ - ρ0);

[0020]

[0021] ρ represents the polar radius. The polar angle is represented by q, which represents the subscript value of the current density expansion coefficient. d represents the distance from the center of the central magnetic field region to the design plane.

[0022] Optionally, the inductance transformation matrix in some embodiments of the present application can also be expressed as:

[0023]

[0024] wherein F represents the function to be integrated as a whole;

[0025] ε represents a minimum constant.

[0026] Optionally, the linear optimization model in some embodiments of the present application is:

[0027]

[0028] wherein D represents the electromagnetic transformation matrix, U represents the current density expansion coefficient, represents the target magnetic field vector, λ1 represents the first weight factor, λ2 represents the second weight factor, L represents the inductance matrix, R represents the resistance matrix, and T represents the transpose.

[0029] Optionally, the Tikhonov explicit initial solution in some embodiments of the present application is:

[0030]

[0031] Optionally, the nonlinear optimization model in some embodiments of the present application is:

[0032]

[0033] The constraint condition is:

[0034]

[0035] U≤max(2×U Opt );

[0036] -U≤max(2×U Opt );

[0037] wherein k1 represents the first proportional factor, k2 represents the second proportional factor, D1 is the transformation matrix for calculating the surface magnetic field of the central magnetic field region, D2 is the transformation matrix for calculating the surface magnetic field of the shielding region, and η represents a minimum constant, represents the magnetic field intensity on the central magnetic field region, represents the magnetic field intensity on the shielding region.

[0038] Optionally, the flow function in some embodiments of the present application is:

[0039]

[0040] wherein ρ represents the polar radius, represents the polar angle, p0 represents the minimum radius of the gradient coil, U q represents the current density expansion coefficient, q represents the index value of the current density expansion coefficient, Q represents the current density expansion order, ρ m represents the maximum radius of the gradient coil.

[0041] Optionally, the stream function value corresponding to each contour line in the contour map in some embodiments of the present application is:

[0042] ψ max = ψ min + (i-1 / 2)xA, i∈1,2,...,n;

[0043] wherein, ψ max represents the maximum value of the stream function, ψ min represents the minimum value of the stream function, n represents the number of turns of the coil

[0044] , i represents the sequence number corresponding to the number of turns of the coil, and A represents the coil current.

[0045] In a second aspect, the present application provides a gradient coil optimization design device for a neonatal magnetic resonance imaging system, the neonatal magnetic resonance imaging system comprising a first structure and a second structure symmetrically distributed above and below a permanent magnet, the imaging region being between the first structure and the second structure, each structure comprising a polar plate, a polar ring located at the edge of the polar plate, and an anti eddy current plate and a gradient coil arranged in the polar ring groove, the gradient coil optimization design device comprising:

[0046] An acquisition module is configured to obtain the inductance matrix and the resistance matrix of each coil in the gradient coil by using a target field method.

[0047] A first construction module is configured to construct a linear optimization model based on the inductance matrix and the resistance matrix, and calculate a Tikhonov explicit initial solution of the linear optimization model.

[0048] A second construction module is configured to construct a nonlinear optimization model based on the Tikhonov explicit initial solution, a first proportional factor and a second proportional factor representing different weight sensitivities in the relative linearity and the absolute linearity, and calculate the current density expansion coefficient of each coil in the gradient coil according to the nonlinear optimization model.

[0049] A determination module is configured to obtain the stream function of each coil based on the current density expansion coefficient, and determine the wiring track of each coil according to the contour map corresponding to the stream function.

[0050] From the above technical solutions, the embodiments of the present application have the following advantages:

[0051] The embodiment of the present application provides a gradient coil optimization design method and device of a neonatal magnetic resonance imaging system, inductance matrix and resistance matrix of each coil in the gradient coil are obtained through a target field method, a linear optimization model is constructed based on the inductance matrix and the resistance matrix, that is, the inductance matrix and the resistance matrix are introduced as penalty terms in the calculation process, a Tikhonov explicit initial solution is obtained initially, then the first proportional factor and the second proportional factor representing different weight sensitivities in relative linearity and absolute linearity are introduced to construct a nonlinear optimization model with the Tikhonov explicit initial solution as a starting point, and current density expansion coefficients of each coil in the gradient coil are obtained, the relative linearity and the absolute linearity are effectively considered, and then the flow function of each coil is obtained by using the current density expansion coefficients, and the wiring track of each coil is determined based on the contour map corresponding to the flow function, and the performance and applicability of the gradient coil are improved. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0053] Figure 1 A cross-sectional structure schematic diagram of a neonatal magnetic resonance imaging system is provided for the embodiments of the present application.

[0054] Figure 2 A local structure schematic diagram of a neonatal magnetic resonance imaging system is provided for the embodiments of the present application.

[0055] Figure 3 A flowchart of a gradient coil optimization design method of a neonatal magnetic resonance imaging system is provided for the embodiments of the present application.

[0056] Figure 4 A design plane schematic diagram of a gradient coil is provided for the embodiments of the present application.

[0057] Figure 5 A relationship diagram of resistance weight and X gradient coil linearity is provided for the embodiments of the present application.

[0058] Figure 6 A relationship diagram of inductance weight and X gradient coil linearity is provided for the embodiments of the present application.

[0059] Figure 7 A relationship diagram of resistance weight and Y gradient coil linearity is provided for the embodiments of the present application.

[0060] Figure 8A relationship diagram of inductance weight and Y gradient coil linearity provided for an embodiment of the present application;

[0061] Figure 9 A relationship diagram of resistance weight and Z gradient coil linearity provided for an embodiment of the present application;

[0062] Figure 10 A relationship diagram of inductance weight and Z gradient coil linearity provided for an embodiment of the present application;

[0063] Figure 11 A schematic diagram of an X gradient coil structure provided for an embodiment of the present application;

[0064] Figure 12 A schematic diagram of a Y gradient coil structure provided for an embodiment of the present application;

[0065] Figure 13 A schematic diagram of a main coil structure of a Z gradient coil provided for an embodiment of the present application;

[0066] Figure 14 A schematic diagram of a shielding coil structure of a Z gradient coil provided for an embodiment of the present application;

[0067] Figure 15 A structural block diagram of a gradient coil optimization design device for a neonatal magnetic resonance imaging system provided for an embodiment of the present application;

[0068] Figure 16 A structural block diagram of a terminal device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0069] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0070] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0071] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict, and the following embodiments are described in detail. Figures 1 to 16 The gradient coil optimization design method and device for a neonatal magnetic resonance imaging system provided by the embodiments of the present application are described in detail.

[0072] Please refer to Figure 1This is a cross-sectional structural diagram of a neonatal magnetic resonance imaging system provided in an embodiment of this application. The 0.23T neonatal magnetic resonance imaging system 10 includes a first structure 102 and a second structure 103 symmetrically distributed along the permanent magnet 101. The area between the first structure 102 and the second structure 103 is the imaging region 104. Each structure includes an electrode plate, an electrode ring located at the edge of the electrode plate, and an anti-eddy current plate and a gradient coil disposed in the groove of the electrode ring. That is, the electrode plate can be a first electrode plate 1021 or a second electrode plate 1031, the electrode ring can be a first electrode ring 1022 or a second electrode ring 1032, the anti-eddy current plate can be a first anti-eddy current plate 1023 or a second anti-eddy current plate 1033, and the gradient coil can be a first gradient coil 1024 or a second gradient coil 1034.

[0073] Furthermore, such as Figure 2 The diagram shows a partial structural schematic of a neonatal magnetic resonance imaging system provided in an embodiment of this application. Specifically, the first gradient coil 1024 includes an X-gradient coil, a Y-gradient coil, a Z-gradient coil, and a Z-shielded coil. The height of the X-gradient coil is 122.65 mm, the height of the Y-gradient coil is 113.35 mm, the height of the Z-gradient coil is 110.25 mm, and the height of the Z-shielded coil is 125.75 mm. All have a design radius of 386 mm. The final thickness of the partition at the dashed box in the diagram is 7.6 mm. The Z-gradient coil employs a self-shielding design, effectively suppressing magnetic field leakage to adjacent components such as the polar ring and anti-eddy current plate. The X-gradient coil and Y-gradient coil employ an unshielded design, suppressing eddy current artifacts through the self-cancellation effect of reverse currents in the same plane, thus meeting imaging performance requirements without the need for an additional shielding layer.

[0074] Please refer to Figure 3 This is a flowchart illustrating a gradient coil optimization design method for a neonatal magnetic resonance imaging system provided in this application embodiment. The gradient coil optimization design method specifically includes the following steps:

[0075] S101, using the target field method to obtain the inductance matrix and resistance matrix of each coil in the gradient coil.

[0076] In some embodiments of this application, the gradient coil can be designed in the plane (e.g., Figure 4 The z = ±d shown, where d is Figure 2 The distance from the center of the central magnetic field region (Diameter of Sphere Volume, DSV) to the design plane (the design planes for the X-gradient coil, Y-gradient coil, and Z-gradient coil are different) is used to discretize the current density distribution along the radial and angular directions, respectively. For example, the radial component J of the current density can be expressed by a combination of trigonometric basis functions in polar coordinates. ρ and angular components The pole is the center of the magnetic field region, and the center is obtained as:

[0077]

[0078] In formula (1), p represents the polar radius, represents the polar angle, p0 represents the minimum radius of the gradient coil, and the value is 0; U q represents the current density expansion coefficient, q represents the subscript value of the current density expansion coefficient; Q represents the current density expansion order, Q = 4 for the X gradient coil and the Y gradient coil, and Q = 6 for the Z gradient coil; w is used to determine the type of the designed gradient coil, w = 0 corresponds to the Z gradient coil, and w = 1 corresponds to the X gradient coil and the Y gradient coil; c depends on the wiring range, and the current density needs to satisfy the geometric constraint condition of the double-plane gradient coil, that is:

[0079]

[0080] In formula (2), p m represents the maximum radius of the gradient coil, and the value is 386 mm; represents the current density.

[0081] Further, based on the Biot-Savart law, the magnetic induction intensity at each target point in the imaging region and the magnetic energy storage energy and power loss of the system are calculated according to the current density distribution, that is Figure 4 The magnetic field B(r) generated at the target point shown in formula (3) is:

[0082]

[0083] In formula (3), μ0 represents the vacuum permeability, r represents the spatial coordinates of the target point, r ′ represents the spatial coordinates of the current element, S represents the area of the current element plane, and J represents the current density at the current element. For the design of the double-plane gradient coil in polar coordinates, the inductance matrix and the resistance matrix can be represented by the magnetic energy storage energy and the power loss of the system, and the magnetic energy storage energy E and the power loss P are respectively:

[0084]

[0085] In formula (4), r' + represents the spatial coordinates on the positive plane (z = d), r' - represents the spatial coordinates on the negative plane (z = -d), δ represents the resistivity of the coil, and t represents the thickness of the coil.

[0086] Further, the inductance matrix and the resistance matrix are obtained based on the magnetic energy storage energy and the power loss, for example U represents the current density expansion coefficient, T represents the transpose, and L represents the inductance matrix. For example... R represents the resistance matrix. To accelerate calculations, this application simplifies the calculation method for the inductance matrix L. For example, the magnetic energy storage is first converted into polar coordinates, i.e.:

[0087]

[0088] In equation (5), q a and q b This is to differentiate them; both are values ​​from 1 to Q, but they change asynchronously. The inductance transformation matrix can be represented as:

[0089]

[0090] In equation (6), and In expression (7) Is the index value a or b, for example? Integrals are... To perform integration, we first integrate with respect to b, and then integrate with respect to a. In this case, a and b are also formulas of the same form. We categorize these formulas in different cases to distinguish them from q. a and q b The usage is the same as that of . and Similarly;

[0091]

[0092] β=qc(ρ-ρ0) (8)

[0093]

[0094] In MATLAB, the above quadruple integral can be calculated by defining a function handle. However, due to the singularity of equation (6), i.e., when ρ a =ρ b ,and When R1 = 0, the integral becomes unsolvable.

[0095] Therefore, in some embodiments of this application, the integration region can be divided into four sub-regions, and the singular points can be placed on the integration boundaries. The inductance transformation matrix can then be expressed as:

[0096]

[0097] In equation (10), F represents the function being integrated over the whole system. For example, F can be... The integral values of the four terms are equivalent by replacing the iteration integral with the upper limit of the variable. For the first term L1 and the second term L2, the integral domain can be expressed as the union of two sub-regions, and the two sub-regions are symmetrical with respect to the straight line Symmetry, that is,

[0098]

[0099] By replacing the two variables in D2, using the symmetry of the function and the characteristic of Jacobian being 1, L1 = L2 can be obtained, and the third term and the fourth term are also equal. In addition, since the function is symmetrical about the straight line ρ a = ρ b also has symmetry, that is,

[0100]

[0101] According to the symmetry, the values of the four parts in the formula are equal. In order to further improve the efficiency of numerical integration and avoid the denominator being zero, in the embodiments of the present application

[0102] ε represents a minimum constant, and the value is 1E-12.

[0103] S102, constructing a linear optimization model based on the inductance matrix and the resistance matrix, and calculating a Tikhonov explicit initial solution of the linear optimization model.

[0104] In some embodiments of the present application, the linear optimization model can be:

[0105]

[0106] In formula (13), D represents an electromagnetic conversion matrix, represents a target magnetic field vector, λ1 represents a first weight factor, and λ2 represents a second weight factor. This optimization problem belongs to a least square problem with a quadratic regular term, and has a Tikhonov explicit initial solution, that is,

[0107]

[0108] S103, constructing a nonlinear optimization model based on the Tikhonov explicit initial solution, the first proportion factor and the second proportion factor representing different weight sensitivities in the relative linearity and the absolute linearity, and calculating the current density expansion coefficient of each coil in the gradient coil according to the nonlinear optimization model.

[0109] In some embodiments of the present application, the Tikhonov explicit initial solution is used as a starting point to improve the linearity, and the nonlinear optimization model can be:

[0110]

[0111] The constraints are:

[0112]

[0113] U≤max(2×U Opt )

[0114] -U≤max(2×U Opt (15)

[0115] In equation (15), k1 represents the first scaling factor, which can be set to 50; k2 represents the second scaling factor, which can be set to 1, and its value is determined according to the experiment; D1 is the transformation matrix used to calculate the surface magnetic field of the central magnetic field region; D2 is the transformation matrix used to calculate the surface magnetic field of the shielded region; η represents a minimum constant. This indicates the magnetic field strength in the central magnetic field region. This indicates the magnetic field strength in the shielded area.

[0116] by Figure 2 For example, the corresponding design parameters, such as Figure 5 The figure shows the effect of resistance weights on the relative and absolute linearity of the X-gradient coil, with λ1 ranging from 1E-10 to 1E-9. Figure 5 It can be seen that the relative linearity is mostly within 5%, and the absolute linearity is all within 5%. Figure 6 The figure shows the effect of inductance weight on the relative and absolute linearity of the X-gradient coil, with λ2 ranging from 1.6E⁻² to 2.5E⁻². Figure 6 It can be seen that both the relative linearity and the absolute linearity are within 5%, and as the weight increases, the relative linearity remains almost unchanged, while the absolute linearity error decreases.

[0117] For example Figure 7 The figure shows the effect of resistance weights on the relative and absolute linearity of the Y-gradient coil, with λ1 ranging from 1E-10 to 1E-9. Figure 7 It can be seen that the relative linearity is mostly within 5%, and the absolute linearity is all within 5%. Figure 8 The figure shows the effect of inductance weight on the relative and absolute linearity of the Y-gradient coil, with λ2 ranging from 1.6E⁻² to 2.5E⁻². Figure 8 It can be seen that the relative linearity is mostly within 5%, and the absolute linearity is all within 5%. Furthermore, as the weight increases, the error of both types of linearity increases.

[0118] For example Figure 9 The figure shows the effect of resistance weights on the relative and absolute linearity of the Z-gradient coil, with λ1 ranging from 11E-5 to 20E-5. Figure 9It can be seen that the relative linearity is mostly within 5%, and the absolute linearity is all within 5%. Figure 10 The figure shows the effect of inductance weight on the relative and absolute linearity of the Z-gradient coil, with λ2 ranging from 0.1 to 1. Figure 10 It can be seen that the relative linearity and absolute linearity are mostly within 5%, and the errors of both linearity decrease as the weight increases.

[0119] S104: The flow function of each coil is obtained based on the current density expansion coefficient, and the wiring trajectory of each coil is determined according to the contour map corresponding to the flow function.

[0120] In some embodiments of this application, the current density on the design plane of the gradient coil must satisfy the two-dimensional current continuity equation, that is:

[0121]

[0122] Furthermore, a scalar function ψ is constructed in the coil plane, namely:

[0123]

[0124] Then any coordinate point on the coil plane The stream function at point can be expressed as:

[0125]

[0126] Furthermore, by selecting an appropriate number of coil turns n, the coil routing trajectory can be obtained from the contour plot corresponding to the stream function, and the stream function value corresponding to each contour line in the contour plot is:

[0127] ψ max =ψ min +(i-1 / 2)×A,i∈1,2,...,n (19)

[0128] In equation (19), ψ max ψ represents the maximum value of the stream function. min The stream function is represented by the minimum value of n.

[0129] The number of turns in the coil is indicated by 'i', where 'i' represents the coil number and 'A' represents the coil current. For example, the X-gradient coil can have 18 turns, and its structure is as follows: Figure 11 As shown, the horizontal axis represents the x-axis, and the vertical axis represents the y-axis, both in meters. For example, the number of turns in a Y-gradient coil can be 18, and the coil structure is as follows... Figure 12 As shown, the horizontal axis represents the y-axis, and the vertical axis represents the x-axis, both in meters. For example, the main coil of a Z-gradient coil can have 19 turns, and the corresponding shielding coil can have 14 turns. The main coil structure is as follows... Figure 13 As shown, and the shielded coil structure is as follows:Figure 14 As shown in the figure, the abscissa represents the x-axis and the ordinate represents the y-axis, both in meters, and the linearity and engineering manufacturing requirements are met. In addition, when selecting the number of turns of the coil, the coil current needs to be ensured to be less than the maximum current that can be supplied by the system, and the currents required by the main coil and the shielding coil of the Z gradient coil are equal, so that one power supply can be used for power supply.

[0130] The embodiment of the application provides a gradient coil optimization design method of a neonatal magnetic resonance imaging system. The inductance matrix and the resistance matrix of each coil in the gradient coil are obtained by using a target field method, and a linear optimization model is constructed based on the inductance matrix and the resistance matrix. That is, the inductance matrix and the resistance matrix are introduced as penalty terms in the calculation process to obtain a Tikhonov explicit initial solution. Then, a first proportional factor and a second proportional factor representing different weight sensitivities in the relative linearity and the absolute linearity are introduced to construct a nonlinear optimization model based on the Tikhonov explicit initial solution, and the current density expansion coefficients of each coil in the gradient coil are obtained. The relative linearity and the absolute linearity are effectively considered, and then the stream function of each coil is obtained by using the current density expansion coefficients, and the wiring track of each coil is determined based on the contour map corresponding to the stream function, thereby improving the performance and applicability of the gradient coil.

[0131] Based on the foregoing embodiment, the embodiment of the application provides a gradient coil optimization design device for a neonatal magnetic resonance imaging system. The neonatal magnetic resonance imaging system includes a first structure 102 and a second structure 103 symmetrically distributed above and below a permanent magnet 101, and an imaging area 104 between the first structure 102 and the second structure 103. Each structure includes a polar plate, a polar ring at the edge of the polar plate, and an anti eddy current plate and a gradient coil arranged in the groove of the polar ring. The gradient coil optimization design device 20 can be applied to Figures 1 to 14 In the gradient coil optimization design method of the corresponding embodiment, please refer to Figure 15 The gradient coil optimization design device 20 includes:

[0132] The acquisition module 201 is configured to obtain the inductance matrix and the resistance matrix of each coil in the gradient coil by using a target field method.

[0133] The first construction module 202 is configured to construct a linear optimization model based on the inductance matrix and the resistance matrix, and calculate a Tikhonov explicit initial solution of the linear optimization model.

[0134] The second construction module 203 is configured to construct a nonlinear optimization model based on the Tikhonov explicit initial solution, a first proportional factor and a second proportional factor representing different weight sensitivities in the relative linearity and the absolute linearity, and calculate the current density expansion coefficients of each coil in the gradient coil according to the nonlinear optimization model.

[0135] The determining module 204 is configured to obtain the flow function of each coil based on the current density expansion coefficient, and determine the wiring track of each coil according to the contour map corresponding to the flow function.

[0136] Optionally, the acquiring module 201 is specifically configured to discretize the current density distribution along the radial direction and the angular direction on the design plane of the gradient coil respectively, and calculate the magnetic induction intensity at each target point in the imaging area and the magnetic energy storage and power loss of the system according to the current density distribution.

[0137] The inductance matrix and the resistance matrix are obtained based on the magnetic energy storage and the power loss.

[0138] It should be noted that the same steps and the same content in the embodiments and other embodiments are described with reference to the descriptions in other embodiments, and will not be described here.

[0139] The gradient coil optimization design device of the neonatal magnetic resonance imaging system provided in the embodiments of the present application obtains the inductance matrix and the resistance matrix of each coil in the gradient coil through the target field method, and constructs a linear optimization model based on the inductance matrix and the resistance matrix, that is, the inductance matrix and the resistance matrix are introduced as penalty terms in the calculation process to preliminarily obtain a Tikhonov explicit initial solution, and then the first proportional factor and the second proportional factor representing different weight sensitivities in the relative linearity and the absolute linearity are introduced to construct a nonlinear optimization model with the Tikhonov explicit initial solution as the starting point, and the current density expansion coefficient of each coil in the gradient coil is obtained, which effectively takes into account the relative linearity and the absolute linearity, and then the flow function of each coil is obtained by using the current density expansion coefficient, and the wiring track of each coil is determined based on the contour map corresponding to the flow function, thereby improving the performance and applicability of the gradient coil.

[0140] Based on the foregoing embodiments, the embodiments of the present application provide a terminal device. Please refer to Figure 16 The terminal device 30 can include a processor 301 and a memory 302. The memory 302 stores at least one instruction, at least one program, a code set or an instruction set, which is loaded and executed by the processor 301 to implement Figures 1 to 14 The steps of the gradient coil optimization design method of the corresponding embodiments.

[0141] As another aspect, the embodiments of the present application provide a computer readable storage medium for storing program code, which is used to execute any one of the implementation manners of the gradient coil optimization design method of the corresponding embodiments. Figures 1 to 14

[0142] ​Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and module can refer to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0143] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, for example, the division of the modules is only a logical function division, and actual implementation can have another division manner, for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed mutual ones can be indirect coupling or communication connection through some interfaces, devices or modules, and can be electrical, mechanical or other forms. The modules described as separate components can be or can not be physically separated, and the components shown as modules can be or can not be physical units, that is, can be located in one place, or can be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0144] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each module can be physically present alone, or two or more units can be integrated in one module. The integrated unit can be realized in the form of hardware or in the form of a software functional unit. If the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.

[0145] Based on such understanding, the technical scheme of the present application or the essential part or the whole or part of the technical scheme that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the gradient coil optimization design method of each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various storage program codes.

[0146] Any technical features in the above embodiments can be combined, and for the sake of brevity, not all possible combinations are described above, however, it should be understood that the application encompasses all possible combinations of the technical features described above.

[0147] The principles and implementation manners of the present application are described herein by using specific examples, and the above embodiments are only used to help understand the method of the present application and its core idea; meanwhile, according to the idea of the present application, the specific implementation manners and application scopes will be changed by those skilled in the art. In conclusion, the content of the present specification should not be understood as a limitation of the present application.

Claims

1. A method for gradient coil optimized design for a neonatal magnetic resonance imaging system, characterized in that, The neonatal magnetic resonance imaging system comprises a first structure and a second structure symmetrically distributed above and below a permanent magnet, and an imaging area is arranged between the first structure and the second structure, each structure comprises a pole plate, a pole ring arranged at the edge of the pole plate, and an anti eddy current plate and a gradient coil arranged in the groove of the pole ring, and the gradient coil optimization design method comprises: An inductance matrix and a resistance matrix of each coil in the gradient coil are obtained by using a target field method; A linear optimization model is constructed based on the inductance matrix and the resistance matrix, and a Tikhonov explicit initial solution of the linear optimization model is calculated; A nonlinear optimization model is constructed based on the Tikhonov explicit initial solution, a first proportional factor and a second proportional factor representing different weight sensitivities in relative linearity and absolute linearity, and current density expansion coefficients of each coil in the gradient coil are calculated according to the nonlinear optimization model; Flow functions of the coils are obtained based on the current density expansion coefficients, and wiring tracks of the coils are determined according to contour lines corresponding to the flow functions; The linear optimization model is: In the above formula, D represents an electromagnetic conversion matrix, U represents a current density expansion coefficient, represents a target magnetic field vector, λ1 represents a first weight factor, λ2 represents a second weight factor, L represents an inductance matrix, R represents a resistance matrix, and T represents a transpose. The Tikhonov explicit initial solution is: The nonlinear optimization model is: The constraint condition is: U < max(2 x U Opt ); - U < max(2 x U Opt ); In the above formula, k1 represents a first proportional factor, k2 represents a second proportional factor, D1 is a transformation matrix for calculating the surface magnetic field of the central magnetic field region, D2 is a transformation matrix for calculating the surface magnetic field of the shield region, η represents a minimum constant, represents the magnetic field strength on the central magnetic field region, represents the magnetic field strength on the shield region.

2. The gradient coil optimization design method of claim 1, wherein, The inductance matrix and the resistance matrix of each coil in the gradient coil are obtained by using the target field method, comprising: The current density distribution is discretized along the radial direction and the angular direction on the design plane of the gradient coil, and the magnetic induction intensity at each target point in the imaging area and the magnetic energy storage energy and power loss of the system are calculated according to the current density distribution; The inductance matrix and the resistance matrix are obtained based on the magnetic energy storage energy and the power loss.

3. The gradient coil optimization design method of claim 2, wherein, The inductance matrix L is obtained by the following formula: Wherein, the inductance transformation matrix can be represented as: E represents the magnetic energy storage energy, p0 represents the minimum radius of the gradient coil, p m represents the maximum radius of the gradient coil, a, b represent the subscript values of the gradient coil, U q represents the current density expansion coefficient, Q represents the current density expansion order, μ0 represents the vacuum permeability, U represents the current density expansion coefficient; Beta = qc (p-p0) ; p denotes the polar radius, q denotes the index value of the current density expansion coefficient, d denotes the distance of the center of the central magnetic field region to the design plane.

4. The gradient coil optimization design method of claim 3, wherein, The inductance transformation matrix can also be represented as: Wherein, F represents the function to be integrated as a whole; e represents a very small constant.

5. The gradient coil optimization design method of claim 1, wherein, The flow function is: wherein p denotes a polar radius, denotes a polar angle, p0denotes a minimum radius of the gradient coil, q denotes a current density expansion coefficient, q denotes an index value of the current density expansion coefficient, Q denotes a current density expansion order, p m denotes a maximum radius of the gradient coil.

6. The gradient coil optimization design method of claim 5, wherein, The flow function value corresponding to each contour line in the contour line map is: ψ max = ψ min + (i - 1 / 2) x A, i e 1, 2,..., n; wherein ψ max represents the maximum value of the stream function, ψ min represents the minimum value of the stream function, n represents the number of turns of the coil, i represents the number of turns of the coil corresponding to the serial number, and A represents the coil current.

7. A gradient coil optimization design apparatus for a neonatal magnetic resonance imaging system, characterized by, The neonatal magnetic resonance imaging system comprises a first structure and a second structure symmetrically distributed above and below a permanent magnet, and an imaging area is arranged between the first structure and the second structure, each structure comprises a pole plate, a pole ring arranged at the edge of the pole plate, and an anti eddy current plate and a gradient coil arranged in the groove of the pole ring, and the gradient coil optimization design device comprises: An acquisition module is configured to obtain an inductance matrix and a resistance matrix of each coil in the gradient coil by using a target field method; A first construction module is configured to construct a linear optimization model based on the inductance matrix and the resistance matrix, and calculate a Tikhonov explicit initial solution of the linear optimization model; A second construction module is configured to construct a nonlinear optimization model based on the Tikhonov explicit initial solution, a first proportional factor and a second proportional factor representing different weight sensitivities in relative linearity and absolute linearity, and calculate current density expansion coefficients of each coil in the gradient coil according to the nonlinear optimization model; A determining module is configured to obtain a flow function of each coil based on the current density expansion coefficient, and determine a wiring track of each coil according to a corresponding contour map of the flow function; The linear optimization model is: In the above formula, D represents an electromagnetic conversion matrix, U represents a current density expansion coefficient, represents a target magnetic field vector, λ1 represents a first weight factor, λ2 represents a second weight factor, L represents an inductance matrix, R represents a resistance matrix, and T represents a transpose. The Tikhonov explicit initial solution is: The nonlinear optimization model is: The constraint condition is: U < max(2 x U Opt ); - U < max(2 x U Opt ); In the above formula, k1 represents a first proportional factor, k2 represents a second proportional factor, D1 is a transformation matrix for calculating the surface magnetic field of the central magnetic field region, D2 is a transformation matrix for calculating the surface magnetic field of the shield region, η represents a minimum constant, represents the magnetic field strength on the central magnetic field region, represents the magnetic field strength on the shield region.

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