WO2023087465A1 - 一种匀场方法、装置、电子设备及存储介质 - Google Patents
一种匀场方法、装置、电子设备及存储介质 Download PDFInfo
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- WO2023087465A1 WO2023087465A1 PCT/CN2021/138523 CN2021138523W WO2023087465A1 WO 2023087465 A1 WO2023087465 A1 WO 2023087465A1 CN 2021138523 W CN2021138523 W CN 2021138523W WO 2023087465 A1 WO2023087465 A1 WO 2023087465A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R33/00—Arrangements or instruments for measuring magnetic variables
- G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
- G01R33/28—Details of apparatus provided for in groups G01R33/44 - G01R33/64
- G01R33/38—Systems for generation, homogenisation or stabilisation of the main or gradient magnetic field
- G01R33/385—Systems for generation, homogenisation or stabilisation of the main or gradient magnetic field using gradient magnetic field coils
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
Definitions
- the present application belongs to the field of electromagnetic technology, and in particular relates to a field shimming method, device, electronic equipment and storage medium.
- the inhomogeneity of the magnetic field can be reduced by adding additional shim coils in the magnetic resonance system, thereby improving the image quality.
- the embodiments of the present application provide a shimming method, device, electronic equipment, and storage medium, so as to solve the problem of inhomogeneous magnetic field distribution of imaging organisms in magnetic resonance systems in the prior art.
- the first aspect of the embodiments of the present application provides a shimming method, including:
- object static magnetic field distribution information corresponding to the target object, where the object static magnetic field distribution information is the static magnetic field distribution information of the target object under the action of the main magnet of the magnetic resonance system;
- the parameters of the shim coil include any one or more items of the channel number, size, spatial position, current magnitude, and number of turns of the shim coil.
- the method before the acquisition of object static magnetic field distribution information corresponding to the target object, the method further includes:
- the magnetic field distribution information of the shim coil magnetic field distribution model is determined.
- the acquiring object static magnetic field distribution information corresponding to the target object includes:
- n is a positive integer greater than 1;
- the determining the target static magnetic field according to the static magnetic field distribution information of the object and the preset shim coil magnetic field distribution model includes:
- the target static magnetic field is determined according to the object static magnetic field distribution information corresponding to the n target objects and the preset shim coil magnetic field distribution model.
- the shim coil magnetic field distribution model includes shim coil units with m channels, where m is a positive integer greater than 1; the static magnetic field distribution information of the objects corresponding to the n target objects and The preset shim coil magnetic field distribution model determines the target static magnetic field, including:
- F is the magnetic field distribution information of the target static magnetic field
- C j is the current magnitude of the shim coil unit of the jth channel in the shim coil magnetic field distribution model
- b j is the shim coil magnetic field distribution model
- B i is the object static magnetic field distribution information of the i-th target object.
- target shim coil parameters including:
- the particle swarm algorithm and the objective function adjust the shim coil parameters in the shim coil magnetic field distribution model until the standard deviation of the magnetic field distribution of the target static magnetic field is less than a preset threshold or until the number of iterations of the particle swarm algorithm When the preset number of times is reached, the parameters of the target shim coil are obtained.
- the particle swarm algorithm and the objective function adjust the shim coil parameters in the shim coil magnetic field distribution model until the standard deviation of the magnetic field distribution of the target static magnetic field is less than a preset threshold or until the The number of iterations of the particle swarm algorithm reaches the preset number, and the parameters of the target shim coil are obtained, including:
- the sub-target shim coil parameters corresponding to each of the shim coil magnetic field distribution models and the objective function determine the standard deviation of the magnetic field distribution of the target static magnetic field corresponding to each of the shim coil magnetic field distribution models;
- the shim coil magnetic field distribution model with the smallest standard deviation of the magnetic field distribution of the target static magnetic field is determined as the target shim coil magnetic field distribution model, and the channel number and sub-target shimming of the target shim coil magnetic field distribution model
- the coil parameters are used as the target shim coil parameters.
- the second aspect of the embodiments of the present application provides a shimming device, including:
- An object static magnetic field distribution information acquisition unit configured to obtain object static magnetic field distribution information corresponding to the target object, the object static magnetic field distribution information being the static magnetic field distribution information of the target object under the action of the main magnet of the magnetic resonance system;
- a target static magnetic field determining unit configured to determine the target static magnetic field according to the static magnetic field distribution information of the object and the preset shim coil magnetic field distribution model;
- the target shim coil parameter determination unit is configured to adjust the shim coil parameters in the shim coil magnetic field distribution model until the magnetic field uniformity of the target static magnetic field satisfies a preset condition to obtain the target shim coil parameters.
- the third aspect of the embodiments of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and operable on the processor.
- the processor executes the computer program , making the electronic device implement the steps of the shimming method described above.
- the fourth aspect of the embodiments of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the electronic device realizes the shimming method steps.
- a fifth aspect of the embodiments of the present application provides a computer program product, which, when the computer program product is run on an electronic device, causes the electronic device to execute the field shimming method described in any one of the foregoing first aspects.
- the embodiment of the present application has the following beneficial effects: in the embodiment of the present application, the static magnetic field distribution information of the target object under the action of the main magnet of the magnetic resonance system is obtained, that is, the static magnetic field distribution information of the object, and according to the object
- the static magnetic field distribution information and the preset shim coil magnetic field distribution model determine the target static magnetic field; then, adjust the shim coil parameters in the shim coil distribution model so that the magnetic field uniformity of the target static magnetic field meets the preset conditions, Obtain the parameters of the target shim coil.
- the target static magnetic field can indicate that the magnetic resonance system is working with superimposed shim coils and the presence of the target object state; by adjusting the shim coil parameters until the magnetic field uniformity of the target static magnetic field meets the preset conditions, the target shim coil parameters that meet the shimming effect can be obtained, so that the subsequent magnetic resonance system can work based on the The parameters of the target shim coil ensure the uniformity of the distribution of the static magnetic field, thereby improving the effect of magnetic resonance imaging.
- FIG. 1 is a schematic diagram of the implementation flow of a shimming method provided in an embodiment of the present application
- FIG. 2 is a schematic diagram of a shim coil provided in an embodiment of the present application.
- Fig. 3 is a schematic diagram of a comparison of shim coil performance simulation shimming results with different structures provided by the embodiment of the present application;
- Fig. 4 is a schematic diagram of a shimming device provided in an embodiment of the present application.
- FIG. 5 is a schematic diagram of an electronic device provided by an embodiment of the present application.
- the inhomogeneity of the static magnetic field can generally be reduced by adding shim coils, thereby improving the magnetic resonance imaging effect of the magnetic resonance system.
- the performance of the shim coils actually added in the magnetic resonance system is usually not optimal, resulting in the problem of uniform magnetic field distribution in the magnetic resonance system after the shim coils are added.
- the embodiment of the present application provides a shimming method, device, electronic equipment, and storage medium.
- the static magnetic field distribution information of the target object and the preset shim coil magnetic field distribution model it is determined that the magnetic field can be expressed
- the resonance system is in the static magnetic field (that is, the target static magnetic field) when the shim coil is superimposed and there is a working state of the object to be imaged
- the target shim coil parameters for the shimming effect enable the subsequent magnetic resonance system to ensure the uniformity of the static magnetic field distribution based on the target shim coil parameters during operation, thereby improving the magnetic resonance imaging effect.
- shim coils In the magnetic resonance system, shim coils generally include three types: spherical harmonic function shim coils, multiple shim coils and local shim coils. Among them, spherical harmonic function shimming coils generally need to increase the order to achieve a better shimming effect. However, increasing the order of spherical harmonic function shim coils may bring about some other practical problems, such as reduced effective use of space, deterioration of coil efficiency, additional consideration of the cooling system of shim coils, and the need to increase the number of power amplifiers, etc. That is, the spherical harmonic function shim coil has certain defects.
- multi-shimming coils Compared with spherical harmonic function shim coils, multi-shimming coils only need to use multiple simple coil loops to generate more complex high-order magnetic fields and obtain better shimming capabilities, but they usually lead to magnetic The signal-to-noise ratio of resonance imaging is reduced, and it will have a certain impact on the radio frequency receiving coil of the magnetic resonance system, so the multiple shim coils also have some defects.
- local shim coils can achieve magnetic field shimming simply and efficiently while reducing interference to radio frequency receiving coils, that is, local shim coils usually have better shimming performance good.
- the shim coils provided in the magnetic resonance system are specifically local shim coils, that is, the shim coil magnetic field distribution model in the embodiment of the present application is specifically the magnetic field distribution model corresponding to the local shim coils, and the shim coils
- the field coil parameters are specifically parameters corresponding to the local shim coils.
- FIG. 1 shows a schematic flow chart of a shimming method provided in an embodiment of the present application.
- the shimming method is applied to electronic equipment, and the details are as follows:
- object static magnetic field distribution information corresponding to a target object is acquired, where the object static magnetic field distribution information is static magnetic field distribution information of the target object under the action of a main magnet of a magnetic resonance system.
- the magnetic resonance system is a system that can realize magnetic resonance imaging by using the principle of nuclear magnetic resonance.
- nuclear magnetic resonance imaging is a process in which radio frequency electromagnetic waves are used to excite substances containing nuclei with non-zero spins in a magnetic field, nuclear magnetic resonance occurs, and then magnetic resonance signals are collected with induction coils, and processed by mathematical methods to establish digital images.
- the nuclear magnetic resonance system of the embodiment of the present application may include a main magnet for providing a static magnetic field, a gradient coil for providing a gradient magnetic field, and a radio frequency coil for exciting hydrogen atoms and receiving magnetic resonance signals generated by nuclear recovery.
- the target object is a corresponding tissue part of a human body or other animal body.
- a human body or other animal body For example, human brain, mouse brain and other tissue parts.
- the target object is placed in the magnetic resonance imaging area of the magnetic resonance system, and when the main magnet of the magnetic resonance system is in an energized working state, the current static magnetic field of the target object in the magnetic resonance imaging area under the action of the main magnet of the magnetic resonance system is obtained distribution information to obtain the object static magnetic field distribution information corresponding to the target object.
- the static magnetic field distribution information of the object may be a B0 magnetic field image collected through a two-dimensional multi-echo sequence, that is, a two-dimensional gradient echo (Gradiernt Recalled Echo, GRE) sequence, and each pixel of the B0 magnetic field image The value of the point represents the magnetic field strength at the corresponding location in the magnetic field.
- B0 is performed on the target object.
- Magnetic field image acquisition obtain the phase diagrams corresponding to each echo and unwrap them, and use the least squares method to fit the pixel points at the same position of each phase diagram on the echo time, and use the slope value of the fitted straight line
- the current B0 magnetic field image is determined by obtaining the B0 magnetic field value of each position in the magnetic resonance imaging region.
- the aforementioned number of echoes can be 5
- the repetition time of the pulse sequence can be a value between 25 and 300 milliseconds
- the 5 echo times can be set to 3.68 milliseconds, 6.12 milliseconds, 8.56 milliseconds, 11 milliseconds, 12.44 milliseconds
- the pulse flip angle can be set to 10 degrees.
- the magnetic field strength and the resonance frequency have a fixed corresponding relationship, therefore, the above-mentioned B0 magnetic field value can be represented by the resonant frequency value that is relatively easy to calculate in addition to the magnetic field strength .
- the formula for calculating the magnetic field strength caused by the difference in the magnetic susceptibility of organisms is (wherein, ⁇ B 0 represents the magnetic field strength caused by the difference in the magnetic susceptibility of the organism, ⁇ represents the phase difference between the two echoes, ⁇ represents the gyromagnetic ratio of the imaging nucleus, and ⁇ TE represents the time difference between the two echoes), the resonance frequency and
- the offset frequency value caused by the difference in the magnetic susceptibility of the living body can be calculated through the resonance frequency value calculation formula, so as to generate the B0 magnetic field image caused by the difference in the magnetic susceptibility of the living body according to the offset frequency value.
- a target static magnetic field is determined according to the static magnetic field distribution information of the object and a preset shim coil magnetic field distribution model.
- the preset shim coil magnetic field distribution model is a pre-set magnetic field distribution model corresponding to a shim coil with adjustable parameters.
- the target static magnetic field distribution information obtained in step S101 is superimposed on the shim coil magnetic field distribution model to obtain the target static magnetic field.
- the target static magnetic field may represent the static magnetic field when the magnetic resonance system is in a working state where shim coils are superimposed and there is an object to be imaged.
- the parameters of the shim coils in the above-mentioned shim coil magnetic field distribution model can be adjusted according to the preset parameter constraints, and the magnetic field uniformity of the target static magnetic field can be calculated after each adjustment.
- the shim coil parameters in the shim magnetic field distribution model at this time are used as the target shim coil parameters.
- the magnetic field uniformity of the target static magnetic field satisfies a preset condition, which may be: the standard deviation (also referred to as standard deviation) of the magnetic field distribution of the target static magnetic field is less than or equal to a preset threshold.
- the magnetic field strength of each position of the static magnetic field of the target can be integrated and then averaged to obtain the average magnetic field strength; then according to the magnetic field strength of each position and the average magnetic field The standard deviation of the magnetic field distribution of the target static magnetic field is obtained from the difference of the intensity.
- the target static magnetic field can indicate that the magnetic resonance system is in the state where the shim coils are superimposed And there is a static magnetic field in the working state of the target object; by adjusting the shim coil parameters until the magnetic field uniformity of the target static magnetic field meets the preset conditions, the target shim coil parameters that meet the shimming effect can be obtained, so that the subsequent magnetic resonance system During operation, the uniformity of static magnetic field distribution can be guaranteed based on the target shim coil parameters, thereby improving the effect of magnetic resonance imaging.
- the parameters of the shim coil include any one or more items of the channel number, size, spatial position, current magnitude, and number of turns of the shim coil.
- the shim coil magnetic field distribution model is specifically a magnetic field distribution model corresponding to a local shim coil with multiple channels.
- the number of channels, coil size, spatial position, current magnitude, number of turns, etc. in the local shim coil can all be used as adjustable shim coil parameters in the shim coil magnetic field distribution model, by adjusting any one of them or Multiple adjustments can flexibly and accurately adjust the uniformity of the magnetic field distribution of the target static magnetic field, and obtain target shim coil parameters that can maximize the target static magnetic field and achieve uniform magnetic field.
- the method before the acquisition of object static magnetic field distribution information corresponding to the target object, the method further includes:
- the magnetic field distribution information of the shim coil magnetic field distribution model is determined.
- a shim coil magnetic field distribution model in the magnetic resonance system may be constructed first.
- the shim coil magnetic field distribution model includes adjustable shim coil parameters such as channel number, coil size, spatial position, current magnitude, and number of turns.
- the magnetic field distribution information corresponding to the shim coil magnetic field distribution model can be obtained according to the Biot-Savart Law. Specifically, electromagnetic field calculation is performed according to Biot Savart's law, and a shim coil magnetic field distribution model capable of representing the magnetic field distribution information of the shim coil in the static magnetic field direction (usually the Z direction) of the main magnet is determined.
- the expression of the magnetic field distribution information of the shim coil magnetic field distribution model is as follows:
- b represents the magnetic field distribution information of the shim coil
- I is the current passing through the shim coil
- ⁇ 0 is the vacuum permeability
- I is the tiny wire element that sources the current
- ⁇ 0 is the vacuum permeability
- I, I is the tiny wire element that sources the current
- the shim coil magnetic field distribution model by adjusting the coil size parameters can change The size of ; can be changed by adjusting the spatial position in the parameters of the shim coil
- the value of I, I Therefore, in the shim coil distribution model, when adjusting the shim coil parameters, the magnetic field distribution information of the shim coil magnetic field distribution model can be automatically updated.
- the target static magnetic field can be quickly determined later, and the shimming performance of the magnetic resonance system can be realized efficiently and accurately based on the target static magnetic field.
- the acquiring object static magnetic field distribution information corresponding to the target object includes:
- n is a positive integer greater than 1;
- the determining the target static magnetic field according to the static magnetic field distribution information of the object and the preset shim coil magnetic field distribution model includes:
- the target static magnetic field is determined according to the object static magnetic field distribution information corresponding to the n target objects and the preset shim coil magnetic field distribution model.
- step S101 When the object static magnetic field distribution information corresponding to a target object is obtained in step S101, the finally determined target shim coil parameters can be tested on the target object or an object consistent with the type of the target object in the magnetic resonance system better uniformity of the magnetic field.
- the uniformity of the magnetic field cannot be well guaranteed when testing other objects of different types from the target object. Therefore, in the embodiment of the present application, in S101, specifically, object static magnetic field distribution information corresponding to n target objects may be acquired.
- step S103 specifically based on the object static magnetic field distribution information corresponding to n target objects, the target static magnetic field containing the static magnetic field distribution information of different target objects is determined, so that the subsequent adjustment of the magnetic field uniformity based on the target static magnetic field
- the target shimming coil parameters obtained from the field coil parameters can be generally applicable to magnetic resonance imaging of various types of objects, thereby improving the universality of the magnetic resonance system shimming.
- the target shim coil parameters determined by the shimming method can be applied to magnetic resonance imaging of more objects.
- n may be equal to 5.
- the shim coil magnetic field distribution model includes shim coil units with m channels, where m is a positive integer greater than 1; the static magnetic field distribution information of the objects corresponding to the n target objects and The preset shim coil magnetic field distribution model determines the target static magnetic field, including:
- F is the magnetic field distribution information of the target static magnetic field
- C j is the current magnitude of the shim coil unit of the jth channel in the shim coil magnetic field distribution model
- b j is the shim coil magnetic field distribution model
- B i is the object static magnetic field distribution information of the i-th target object.
- the shim coil includes shim coil units with m channels, where m is a positive integer greater than 1.
- m is a positive integer greater than 1.
- the shim coils in this embodiment of the present application may include 5-channel shim coil units labeled 1-5.
- the magnetic field distribution information of the target static magnetic field can be determined based on the magnetic field distribution information of the shim coil units of m channels in the shim coil magnetic field distribution model and the object static magnetic field distribution information of n target objects .
- the objective function may be used to determine the magnetic field distribution information of the target static magnetic field.
- the expression of the objective function is as follows:
- F represents the magnetic field distribution information of the static magnetic field of the target
- C j is the current magnitude of the shim coil unit of the jth channel in the shim coil magnetic field distribution model, and the value of C j is specifically related to the number of turns of the shim coil unit and information related to the tiny line elements of the source current
- b j is the magnetic field distribution information of the shim coil unit of the jth channel in the shim coil magnetic field distribution model, which can be determined by modeling the shim coil magnetic field distribution model The expression of the magnetic field distribution information determines the value of b j
- Bi is the static magnetic field distribution information of the i-th target object.
- the magnetic field distribution of the target static magnetic field can be accurately represented, so that the parameter adjustment of the shim coil can be accurately realized subsequently according to the objective function, and the target static magnetic field satisfying the preset conditions can be obtained.
- target shim coil parameters including:
- the particle swarm algorithm and the objective function adjust the shim coil parameters in the shim coil magnetic field distribution model until the standard deviation of the magnetic field distribution of the target static magnetic field is less than a preset threshold or until the number of iterations of the particle swarm algorithm When the preset number of times is reached, the parameters of the target shim coil are obtained.
- a certain number of shim coil parameter values may be determined to form a particle group according to the constraint range of the shim coil parameters in the shim coil magnetic field distribution model. Afterwards, the following steps are implemented through the particle swarm optimization algorithm:
- A1 Obtain an initial set of shim coil parameter values in the particle swarm, and determine the standard deviation of the magnetic field distribution of the target static magnetic field based on the shim coil parameter values and the objective function;
- A2 If the standard deviation is less than the preset threshold or the number of iterations of the particle swarm optimization algorithm reaches the preset number, then use the current set of shim coil parameter values as the target shim coil parameter value; otherwise, determine the local maximum value according to the standard deviation Optimal shim coil parameters and globally optimal shim coil parameters;
- A3 According to the local optimal shim coil parameters and the global optimal shim coil parameters, obtain the next set of shim coil parameter values from the particle swarm, and based on the shim coil parameter values and the objective function, determine the current target static The standard deviation of the magnetic field distribution of the magnetic field; after that, return to step A2.
- the standard deviation of the magnetic field distribution of the target static magnetic field is less than the preset threshold, it can directly indicate that the magnetic field distribution of the target static magnetic field is relatively uniform, and the number of iterations of the particle swarm optimization algorithm reaching the preset number can also indicate that the current parameter
- the optimal target shim coil parameters that can make the magnetic field distribution of the static magnetic field of the target more uniform are found within the range. Through the particle swarm optimization algorithm, the parameters of the target shim coil satisfying any one of the above two conditions can be quickly and accurately determined, and the shim efficiency can be improved.
- the particle swarm algorithm and the objective function adjust the shim coil parameters in the shim coil magnetic field distribution model until the standard deviation of the magnetic field distribution of the target static magnetic field is less than a preset threshold or until the The number of iterations of the particle swarm algorithm reaches the preset number, and the parameters of the target shim coil are obtained, including:
- the sub-target shim coil parameters corresponding to each of the shim coil magnetic field distribution models and the objective function determine the standard deviation of the magnetic field distribution of the target static magnetic field corresponding to each of the shim coil magnetic field distribution models;
- the shim coil magnetic field distribution model with the smallest standard deviation of the magnetic field distribution of the target static magnetic field is determined as the target shim coil magnetic field distribution model, and the channel number and sub-target shimming of the target shim coil magnetic field distribution model Coil parameter parameters are used as target shim coil parameters.
- the number of channels of the shim coil unit can be adjusted within a preset range, for example, the adjustment range of the number of channels can be 3-6.
- the magnetic field distribution model of each shim coil corresponding to each channel number can be determined by setting the number of channels. For example, four shim coil distribution models with channel numbers of 3, 4, 5, and 6 can be determined.
- each shim coil magnetic field distribution model corresponding to a fixed channel number adjust the shim coil parameters in the shim coil magnetic field distribution model except for the number of channels according to the particle swarm algorithm and the objective function, until the particle swarm algorithm When the number of iterations reaches the preset number, the optimal shim coil parameters of the shim coil magnetic field distribution model are obtained as the sub-target shim coil parameters.
- the sub-target shim coil parameters corresponding to each shim coil magnetic field distribution model corresponding to a fixed number of channels can be determined.
- the size d, spatial position, current size and number of turns of the shim coil in the model can be used as the shim coil magnetic field distribution model
- Adjustable shim coil parameters design the corresponding particle group.
- the particle swarm contains N groups of parameters, and the value range of N can be 20 to 50.
- implement the particle swarm algorithm implement the particle swarm algorithm through the following steps, and obtain the sub-target shim coil parameters corresponding to the shim coil magnetic field distribution model:
- B1 Initialize the particle swarm, assign a random initial position and velocity to each set of parameters in the particle swarm.
- the position update formula is:
- a 5-channel local shim coil parameter constraint condition for mouse brain imaging is given.
- 5 shim coil units are distributed in a diameter of 70mm (“mm” Indicates mm) on the cylinder, the number of turns of the coil unit is 1, the current limit condition of each coil unit is [-2 2]A ("A" indicates the current unit: ampere), and the 5 coil units are all the same square , the side length constraint condition is [20 50]mm, the angle constraint condition of the square distribution on the cylinder is [- ⁇ ⁇ ], centered on the center of the mouse brain, the constraint condition of the square center on the z-axis is [- 25 25] mm.
- B3 According to the objective function, calculate the standard deviation of the target static magnetic field obtained after substituting each set of parameters into the objective function, and determine whether to update the historical best position or the global best position according to the standard deviation. Specifically, in the local optimization process, for each set of parameters, compare the standard deviation value of its current position with the standard deviation value corresponding to its historical best position (pbest), if the standard deviation value of the current position is smaller, use the current Location update history best location. In the global optimization process, for each set of parameters, compare the standard deviation value of its current position with the standard deviation value corresponding to the global best position (gbest), if the standard deviation value of the current position is smaller, update it with the current position global best position.
- step B4 Determine whether the current number of iterations reaches the preset number, and if so, use the group of parameters corresponding to the current global best position as the sub-target shim coil parameters corresponding to the current shim coil magnetic field distribution model. If not, return to step B2.
- the particle swarm algorithm calculation is performed on the 5-channel local shim coils, and the obtained sub-target shim coil parameters include: the currents corresponding to the five shim coil units are respectively 2A, -1.6256A, 0.3702A, -2A, -1.4978A, the side length of the shim coil unit is 20 mm, and the angles distributed on the cylinder are 1.0471 radians, 1.9625 radians, -2.9783 radians, 1.5920 radians, -2.6117 radians In radians, the distances between the position of the center of the coil unit on the z-axis and the origin of the coordinate axes are: 15.5 mm, 25.0 mm, -16.9 mm, 5.7 mm, and -7.0 mm.
- the corresponding shim coil magnetic field distribution model with the smallest standard deviation is determined as the target shim coil magnetic field distribution model with the most uniform magnetic field distribution.
- the channel number of the target shim coil distribution model and its corresponding sub-target shim coil parameters are combined as target shim coil parameters, so as to maximize the shimming effect of the magnetic resonance system.
- the optimal sub-target shim coil parameters are respectively solved for the shim coil magnetic field distribution models with different channel numbers, and then the magnetic field distribution uniformity of the target static magnetic field determined by each sub-target shim coil is further , to determine the target shim coil magnetic field distribution model with the optimal number of channels, so as to optimize the number of channels of the shim coil and improve the shimming effect.
- the B0 magnetic field images of 8 objects can be obtained, and the B0 magnetic field images of 5 objects can be used as the static magnetic field distribution information of the target object, and the parameters of the target shim coil can be obtained through the above steps S101 to S103 .
- the B0 magnetic field images of the remaining three subjects were used as the test group, and the shimming effect of the static magnetic field in the magnetic resonance system was tested based on the target shim coil parameters.
- Figure 3 shows the comparison of the performance simulation shimming results of shim coils with different structures provided by the embodiment of the present application; among them, MC8 represents a multi-coil with 8 channels, and LC3 represents a multi-coil with 3 channels Local shim coils, and so on for others, Basic set means the basic setting, d means the side length of the coil unit, and L is the total length of the shim coil. It can be seen from the figure that the local shim coil can achieve a good shim effect with a small number of channels. Through testing, the influence of the local shimming coil on the signal-to-noise ratio of the radio frequency coil is controlled within 5%. While achieving a good shimming effect, it will not cause great interference to the radio frequency coil.
- Fig. 4 shows a schematic structural diagram of a shimming device provided by the embodiment of the present application. For the convenience of description, only the parts related to the embodiment of the present application are shown:
- the shim device includes: an acquisition unit 41 , a target static magnetic field determination unit 42 , and a target shim coil parameter determination unit 43 . in:
- the obtaining unit 41 is configured to obtain object static magnetic field distribution information corresponding to the target object, and the object static magnetic field distribution information is the static magnetic field distribution information of the target object under the action of the main magnet of the magnetic resonance system.
- the target static magnetic field determination unit 42 is configured to determine the target static magnetic field according to the static magnetic field distribution information of the object and the preset shim coil magnetic field distribution model.
- the target shim coil parameter determination unit 43 is configured to adjust the shim coil parameters in the shim coil magnetic field distribution model until the magnetic field uniformity of the target static magnetic field satisfies a preset condition to obtain the target shim coil parameters.
- the parameters of the shim coil include any one or more items of the channel number, size, spatial position, current magnitude, and number of turns of the shim coil.
- the shimming device also includes:
- the model determination unit is configured to determine the magnetic field distribution information of the shim coil magnetic field distribution model according to Biot Savart's law. .
- the acquiring unit 41 is specifically configured to acquire object static magnetic field distribution information respectively corresponding to n target objects, where n is a positive integer greater than 1;
- the target static magnetic field determining unit 42 is configured to determine the target static magnetic field according to the object static magnetic field distribution information corresponding to the n target objects and a preset shim coil magnetic field distribution model.
- the shim coil magnetic field distribution model includes m channel shim coil units, where m is a positive integer greater than 1; the target static magnetic field determination unit 42 is specifically configured to use the objective function Determine the target static magnetic field;
- F is the magnetic field distribution information of the target static magnetic field
- C j is the current size of the shim coil unit of the j channel in the shim coil magnetic field distribution model
- b j is the shim coil unit
- Bi is the static magnetic field distribution information of the ith target object.
- the target shim coil parameter determination unit 43 is specifically configured to adjust the shim coil parameters in the shim coil magnetic field distribution model according to the particle swarm algorithm and the objective function until the magnetic field of the target static magnetic field The standard deviation of the distribution is less than a preset threshold or until the number of iterations of the particle swarm optimization algorithm reaches a preset number of times to obtain the target shim coil parameters.
- the target shim coil parameter determination unit 43 adjust the shim coil parameters in the shim coil magnetic field distribution model until the target static magnetic field
- the standard deviation of the magnetic field distribution is less than the preset threshold or until the number of iterations of the particle swarm optimization algorithm reaches the preset number of times to obtain the parameters of the target shim coil, including:
- the sub-target shim coil parameters corresponding to each of the shim coil magnetic field distribution models and the objective function determine the standard deviation of the magnetic field distribution of the target static magnetic field corresponding to each of the shim coil magnetic field distribution models;
- the shim coil magnetic field distribution model with the smallest standard deviation of the magnetic field distribution of the target static magnetic field is determined as the target shim coil magnetic field distribution model, and the channel number and sub-target shimming of the target shim coil magnetic field distribution model
- the coil parameters are used as the target shim coil parameters.
- Fig. 5 is a schematic diagram of an electronic device provided by an embodiment of the present application.
- the electronic device 5 of this embodiment includes: a processor 50 , a memory 51 , and a computer program 52 stored in the memory 51 and operable on the processor 50 , such as a shimming program.
- the processor 50 executes the computer program 52, the steps in the embodiments of the above-mentioned field shimming methods are implemented, for example, steps S101 to S103 shown in FIG. 1 .
- the processor 50 executes the computer program 52, it realizes the functions of each module/unit in the above-mentioned device embodiments, such as the functions of the acquisition unit 41 to the target shim coil parameter determination unit 43 shown in FIG. 4 .
- the computer program 52 can be divided into one or more modules/units, and the one or more modules/units are stored in the memory 51 and executed by the processor 50 to complete this application.
- the one or more modules/units may be a series of computer program instruction segments capable of accomplishing specific functions, and the instruction segments are used to describe the execution process of the computer program 52 in the electronic device 5 .
- the electronic device 5 may be computing devices such as desktop computers, notebooks, palmtop computers, and cloud servers.
- the electronic device may include, but not limited to, a processor 50 and a memory 51 .
- FIG. 5 is only an example of the electronic device 5, and does not constitute a limitation to the electronic device 5. It may include more or less components than those shown in the figure, or combine certain components, or different components. , for example, the electronic device may also include an input and output device, a network access device, a bus, and the like.
- the so-called processor 50 can be a central processing unit (Central Processing Unit, CPU), and can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
- a general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.
- the storage 51 may be an internal storage unit of the electronic device 5 , such as a hard disk or memory of the electronic device 5 .
- the memory 51 can also be an external storage device of the electronic device 5, such as a plug-in hard disk equipped on the electronic device 5, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, flash card (Flash Card), etc.
- the memory 51 may also include both an internal storage unit of the electronic device 5 and an external storage device.
- the memory 51 is used to store the computer program and other programs and data required by the electronic device.
- the memory 51 can also be used to temporarily store data that has been output or will be output.
- the disclosed device/electronic equipment and method can be implemented in other ways.
- the device/electronic device embodiments described above are only illustrative.
- the division of the modules or units is only a logical function division.
- the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
- the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
- each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
- the above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.
- the integrated module/unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments in the present application can also be completed by instructing related hardware through computer programs.
- the computer programs can be stored in a computer-readable storage medium, and the computer When the program is executed by the processor, the steps in the above-mentioned various method embodiments can be realized.
- the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form.
- the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a removable hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM, Read-Only Memory) , Random Access Memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.
- ROM Read-Only Memory
- RAM Random Access Memory
- electrical carrier signal telecommunication signal and software distribution medium, etc.
Abstract
一种匀场方法、装置、电子设备及存储介质，适用于电磁技术领域，所述方法包括：获取目标对象对应的对象静磁场分布信息，所述对象静磁场分布信息为所述目标对象在磁共振系统的主磁体作用下的静磁场分布信息（S101）；根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场（S102）；调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数（S103）。所述方法能够准确地确定实现磁共振系统的匀场效果的目标匀场线圈参数，保证磁场分布的均匀性，提高磁共振成像效果。
Description
本申请属于电磁技术领域，尤其涉及一种匀场方法、装置、电子设备及存储介质。
当生物体通过磁共振系统进行图像采集时，由于生物体不同组织之间存在磁化率差异，导致组织的交界处产生局部非均匀磁场，从而导致采集到的图像存在图像伪影的缺陷。通常，可以通过在磁共振系统中增加额外的匀场线圈来降低磁场的非均匀性，从而提高图像的质量。
然而，目前的匀场线圈的性能不够优化，导致在磁共振系统中成像的生物体仍存在磁场分布不均匀的问题。
发明内容
有鉴于此，本申请实施例提供了一种匀场方法、装置、电子设备及存储介质，以解决现有技术磁共振系统中成像的生物体磁场分布不均匀的问题。
本申请实施例的第一方面提供了一种匀场方法，包括：
获取目标对象对应的对象静磁场分布信息，所述对象静磁场分布信息为所述目标对象在磁共振系统的主磁体作用下的静磁场分布信息；
根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场；
调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数。
可选地，所述匀场线圈参数包括匀场线圈的通道数、尺寸大小、空间位置、 电流大小、匝数中的任意一项或者多项。
可选地，在所述获取目标对象对应的对象静磁场分布信息之前，还包括：
根据毕奥萨伐尔定律，确定所述匀场线圈磁场分布模型的磁场分布信息。
可选地，所述获取目标对象对应的对象静磁场分布信息，包括：
获取n个目标对象分别对应的对象静磁场分布信息，其中，n为大于1的正整数；
对应地，所述根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场，包括：
根据所述n个目标对象分别对应的所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场。
可选地，所述匀场线圈磁场分布模型包括m个通道的匀场线圈单元，m为大于1的正整数；所述根据所述n个目标对象分别对应的所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场，包括：
利用目标函数
确定目标静磁场；
其中，F为所述目标静磁场的磁场分布信息，C
j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的电流大小，b
j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的磁场分布信息，B
i为第i个所述目标对象的对象静磁场分布信息。
可选地，所述调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数，包括：
根据粒子群算法和所述目标函数，调整匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场分布的标准差小于预设阈值或者直至所述粒子群算法的迭代次数到达预设次数，得到目标匀场线圈参数。
可选地，所述根据粒子群算法和所述目标函数，调整匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场分布的标准差小于预设阈值或者直至所述粒子群算法的迭代次数到达预设次数，得到目标匀场线圈参数， 包括：
针对设置了不同通道数的各个匀场线圈磁场分布模型，分别根据粒子群算法和所述目标函数，调整所述匀场线圈磁场分布模型的子匀场线圈参数，直至所述粒子群算法的迭代次数到达预设次数，得到各个所述匀场线圈磁场分布模型分别对应的子目标匀场线圈参数；
根据各个所述匀场线圈磁场分布模型分别对应的子目标匀场线圈参数和所述目标函数，确定各个所述匀场线圈磁场分布模型分别对应的所述目标静磁场的磁场分布的标准差；
将所述目标静磁场的磁场分布的标准差最小的所述匀场线圈磁场分布模型确定为目标匀场线圈磁场分布模型，并以所述目标匀场线圈磁场分布模型的通道数和子目标匀场线圈参数作为目标匀场线圈参数。
本申请实施例的第二方面提供了一种匀场装置，包括：
对象静磁场分布信息获取单元，用于获取目标对象对应的对象静磁场分布信息，所述对象静磁场分布信息为所述目标对象在磁共振系统的主磁体作用下的静磁场分布信息；
目标静磁场确定单元，用于根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场；
目标匀场线圈参数确定单元，用于调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数。
本申请实施例的第三方面提供了一种电子设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，当所述处理器执行所述计算机程序时，使得电子设备实现如所述匀场方法的步骤。
本申请实施例的第四方面提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，当所述计算机程序被处理器执行时，使得电子设备实现如所述匀场方法的步骤。
本申请实施例的第五方面提供了一种计算机程序产品，当计算机程序产品在电子设备上运行时，使得电子设备执行上述第一方面中任一项所述的匀场方法。
本申请实施例与现有技术相比存在的有益效果是：本申请实施例中，获取目标对象在磁共振系统的主磁体作用下的静磁场分布信息，即对象静磁场分布信息，根据该对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场；之后，调整该匀场线圈分布模型中的匀场线圈参数，使得该目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数。由于目标静磁场是基于目标对象的对象静磁场分布信息和预设的匀场线圈磁场分布模型而确定的，因此该目标静磁场可以表示磁共振系统处于叠加了匀场线圈且存在目标对象的工作状态时的静磁场；通过调整匀场线圈参数直至目标静磁场的磁场均匀度满足预设条件，能够得到满足匀场效果的目标匀场线圈参数，使得后续该磁共振系统在工作时能够基于该目标匀场线圈参数保证静磁场分布的均匀性，从而提高磁共振成像效果。
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍。
图1是本申请实施例提供的一种匀场方法的实现流程示意图；
图2是本申请实施例提供的一种匀场线圈的示意图；
图3是本申请实施例提供的一种不同结构的匀场线圈性能仿真匀场结果对比的示意图；
图4是本申请实施例提供的一种匀场装置的示意图；
图5是本申请实施例提供一种电子设备的示意图。
以下描述中，为了说明而不是为了限定，提出了诸如特定系统结构、技术之类的具体细节，以便透彻理解本申请实施例。然而，本领域的技术人员应当清楚，在没有这些具体细节的其它实施例中也可以实现本申请。在其它情况中，省略对众所周知的系统、装置、电路以及方法的详细说明，以免不必要的细节妨碍本申请的描述。
应当理解，当在本说明书和所附权利要求书中使用时，术语“包括”指示所描述特征、整体、步骤、操作、元素和/或组件的存在，但并不排除一个或多个其它特征、整体、步骤、操作、元素、组件和/或其集合的存在或添加。
为了说明本申请所述的技术方案，下面通过具体实施例来进行说明。
在磁共振系统中，通常可以通过增加匀场线圈来降低静磁场的非均匀性，从而提高磁共振系统的磁共振成像效果。然而，在磁共振系统中实际添加的匀场线圈的性能通常不是最优的，导致增加了匀场线圈后的磁共振系统仍存在磁场分布均匀的问题。
为了解决该技术问题，本申请实施例提供了一种匀场方法、装置、电子设备及存储介质，通过目标对象的对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定可以表示磁共振系统处于叠加了匀场线圈且存在待成像对象的工作状态时的静磁场(即目标静磁场)后，通过调整匀场线圈参数直至目标静磁场的磁场均匀度满足预设条件，能够得到满足匀场效果的目标匀场线圈参数，使得后续该磁共振系统在工作时能够基于该目标匀场线圈参数保证静磁场分布的均匀性，从而提高磁共振成像效果。
在磁共振系统中，匀场线圈通常包括三类：球谐函数匀场线圈、多匀场线圈和局部匀场线圈。其中，球谐函数匀场线圈通常需要增加阶数才能够实现较好的匀场效果。然而，增加球谐函数匀场线圈的阶数可能会带来一些其它的实际问题，例如有效利用空间缩小、线圈效率变差、需要额外考虑匀场线圈的冷却系统、需要增加功率放大器数目等，即球谐函数匀场线圈存在一定的缺陷。而多匀场线圈虽然相对于球谐函数匀场线圈来说，只需要通过多个简单的线圈 回路即可产生较为复杂的高阶磁场，获得较好的匀场能力，然而其通常会导致磁共振成像的信噪比降低，并且会对磁共振系统的射频接收线圈带来一定的影响，因此多匀场线圈也存在一些缺陷。而局部匀场线圈相对于球谐函数匀场线圈和多匀场线圈来说，能够在简单高效地实现磁场匀场的同时降低对射频接收线圈的干扰，即局部匀场线圈通常匀场性能较好。因此，在一个实施例中，磁共振系统中设置的匀场线圈具体为局部匀场线圈，即本申请实施例中的匀场线圈磁场分布模型具体为局部匀场线圈对应的磁场分布模型，匀场线圈参数具体为局部匀场线圈对应的参数。
实施例一：
图1示出了本申请实施例提供的一种匀场方法的流程示意图，该匀场方法应用于电子设备，详述如下：
在S101中，获取目标对象对应的对象静磁场分布信息，所述对象静磁场分布信息为所述目标对象在磁共振系统的主磁体作用下的静磁场分布信息。
磁共振系统为能够利用核磁共振原理实现磁共振成像的系统。其中，核磁共振成像，是利用射频电磁波对磁场中含有自旋不为零的原子核的物质进行激发，发生核磁共振，然后用感应线圈采集磁共振信号，经过数学方法进行处理建立数字图像的过程。本申请实施例的核磁共振系统可以包括用于提供静磁场的主磁体，用于提供梯度磁场的梯度线圈、用于激励氢原子并接收原子核恢复产生的磁共振信号的射频线圈。
本申请实施例中，目标对象为人体或者其它动物体对应的组织部位。例如人体大脑、老鼠大脑等组织部位。将该目标对象置于磁共振系统的磁共振成像区域中，在磁共振系统的主磁体处于通电工作状态时，获取当前该目标对象在磁共振系统的主磁体作用下磁共振成像区域的静磁场分布信息，得到目标对象对应的对象静磁场分布信息。
在一个实施例中，对象静磁场分布信息可以为通过二维多回波序列，即二维梯度回波(Gradiernt Recalled Echo，GRE)序列采集得到的B0磁场图像，该 B0磁场图像的每个像素点的值表示磁场中对应位置的磁场强度。在一个实施例中，在目标对象放置于磁共振系统的磁共振成像区域，并设置磁共振系统中脉冲序列对应的回波数目、重复时间、脉冲翻转角度等参数后，对该目标对象进行B0磁场图像采集，获取各个回波分别对应的相位图后进行解缠绕，并用最小二乘法对各个相位图同一位置的像素点在回波时间上进行直线拟合，以拟合到的直线的斜率值作为该位置的B0磁场值；通过求得的磁共振成像区域中各个位置的B0磁场值，确定当前的B0磁场图像。示例性地，前述的回波数目可以为5，脉冲序列的重复时间可以为25～300毫秒之间的数值，5个回波时间可分别设置为3.68毫秒、6.12毫秒、8.56毫秒、11毫秒、12.44毫秒，脉冲翻转角度可以设置为10度。在一个实施例中，由于磁共振系统中，磁场强度与共振频率具有固定的对应关系，因此，上述的B0磁场值除了通过磁场强度表示外，还可以通过较为容易计算到的共振频率值来表示。示例性地，生物体磁化率差异导致的磁场强度的计算公式为
(其中，ΔB
0表示生物体磁化率差异导致的磁场强度，Δφ表示两个回波的相位差，γ表示成像原子核的旋磁比，ΔTE表示两个回波之间的时间差)，共振频率与该磁场强度的对应关系可以通过公式Δω
0＝γ·ΔB
0表示(其中，Δω
0表示核磁共振角频率)，通过这两个公式，可以确定共振频率值计算公式为
(其中，Δf表示生物体磁化率差异导致的偏移频率值)。通过该共振频率值计算公式可以计算得到生物体磁化率差异导致的偏移频率值，从而根据该偏移频率值生成生物体磁化率差异导致的B0磁场图像。
在S102中，根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场。
本申请实施例中，预设的匀场线圈磁场分布模型为提前设定的参数可调的匀场线圈对应的磁场分布模型。将步骤S101获取到的对象静磁场分布信息与该匀场线圈磁场分布模型进行叠加，得到目标静磁场。该目标静磁场可以表示磁 共振系统处于叠加了匀场线圈且存在待成像对象的工作状态时的静磁场。
在S103中，调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数。
在确定目标静磁场后，可以按照预设的参数约束条件，对上述匀场线圈磁场分布模型中的匀场线圈参数进行调整，并在每次调整后计算目标静磁场的磁场均匀度。当调整至目标静磁场的磁场均匀度满足预设条件时，以此时匀场磁场分布模型中的匀场线圈参数作为目标匀场线圈参数。其中，目标静磁场的磁场均匀度满足预设条件，可以为：目标静磁场的磁场分布的标准差(也可以称为标准偏差)小于或者等于预设阈值。在一个实施例中，可以根据目标静磁场的磁场分布信息，对目标静磁场各个位置的磁场强度进行积分后去平均值，得到平均磁场强度；之后根据该每个位置的磁场强度与该平均磁场强度的差值，求得该目标静磁场的磁场分布的标准差。
本申请实施例中，由于目标静磁场是基于目标对象的对象静磁场分布信息和预设的匀场线圈磁场分布模型而确定的，因此该目标静磁场可以表示磁共振系统处于叠加了匀场线圈且存在目标对象的工作状态时的静磁场；通过调整匀场线圈参数直至目标静磁场的磁场均匀度满足预设条件，能够得到满足匀场效果的目标匀场线圈参数，使得后续该磁共振系统在工作时能够基于该目标匀场线圈参数保证静磁场分布的均匀性，从而提高磁共振成像效果。
可选地，所述匀场线圈参数包括匀场线圈的通道数、尺寸大小、空间位置、电流大小、匝数中的任意一项或者多项。
本申请实施例中，匀场线圈磁场分布模型具体为具有多个通道的局部匀场线圈对应的磁场分布模型。该局部匀场线圈中的通道数、线圈尺寸大小、空间位置、电流大小、匝数等，均可以作为匀场线圈磁场分布模型中可调的匀场线圈参数，通过对其中的任意一项或者多项进行调整，能够灵活准确地调整目标静磁场的磁场分布均匀度，得到能够使得目标静磁场最大化地实现磁场均匀的目标匀场线圈参数。
可选地，在所述获取目标对象对应的对象静磁场分布信息之前，还包括：
根据毕奥萨伐尔定律，确定所述匀场线圈磁场分布模型的磁场分布信息。
本申请实施例中，可以在获取目标对象对应的对象静磁场分布信息之前，先构建磁共振系统中的匀场线圈磁场分布模型。该匀场线圈磁场分布模型中，包括可以调节的通道数、线圈尺寸大小、空间位置、电流大小、匝数等匀场线圈参数。该匀场线圈磁场分布模型对应的磁场分布信息，可以根据毕奥萨瓦尔(Biot-Savart Law)定律得到。具体地，根据毕奥萨伐尔定律进行电磁场计算，确定能够表示匀场线圈在主磁体的静磁场方向上(通常为Z方向)的磁场分布信息的匀场线圈磁场分布模型。示例性地，该匀场线圈磁场分布模型的磁场分布信息表达式如下：
其中，b表示匀场线圈的磁场分布信息，I为匀场线圈通过的电流，μ
0为真空磁导率，
为源电流的微小线元素，
分别为场点和源点。在该匀场线圈磁场分布模型中，通过调整线圈尺寸大小参数能够改变
的大小；通过调整匀场线圈参数中的空间位置能够改变
的值，通过调整匀场线圈参数中的源电流和匝数可以改变I、
的大小，因此在该匀场线圈分布模型中，在调整匀场线圈参数时，能够自动更新该匀场线圈磁场分布模型的磁场分布信息。
本申请实施例中，通过提前准确地确定匀场线圈分布模型，使得后续能够快捷地确定目标静磁场，高效准确地基于该目标静磁场实现磁共振系统的匀场性能。
可选地，所述获取目标对象对应的对象静磁场分布信息，包括：
获取n个目标对象分别对应的对象静磁场分布信息，其中，n为大于1的正整数；
对应地，所述根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场，包括：
根据所述n个目标对象分别对应的所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场。
当步骤S101中获取的为一个目标对象对应的对象静磁场分布信息时，则最终确定出的目标匀场线圈参数能够在磁共振系统对该目标对象或者与该目标对象的类型一致的对象进行测试时实现较好的磁场均匀度。而对于其它与该目标对象不同类型的对象在进行测试时的磁场均匀度无法较好地保证。因此，本申请实施例在S101中，具体可以获取n个目标对象分别对应的对象静磁场分布信息。之后，在步骤S103中，具体基于n个目标对象分别对应的对象静磁场分布信息，确定了包含不同目标对象的静磁场分布信息的目标静磁场，使得后续基于目标静磁场的磁场均匀度调整匀场线圈参数得到的目标匀场线圈参数，能够普遍适用于多种不同类型的对象的磁共振成像，提高磁共振系统匀场的普适性。其中，n的数值越大，则通过该匀场方法确定的目标匀场线圈参数能够适用于更多对象的磁共振成像。示例性地，n可以等于5。
可选地，所述匀场线圈磁场分布模型包括m个通道的匀场线圈单元，m为大于1的正整数；所述根据所述n个目标对象分别对应的所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场，包括：
利用目标函数
确定目标静磁场；
其中，F为所述目标静磁场的磁场分布信息，C
j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的电流大小，b
j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的磁场分布信息，B
i为第i个所述目标对象的对象静磁场分布信息。
本申请实施例的匀场线圈磁场分布模型中，匀场线圈包括m个通道的匀场线圈单元，其中m为大于1的正整数。示例性地，如图2所示，本申请实施例的匀场线圈可以包括标号为1-5的5个通道的匀场线圈单元。
对应地，本申请实施例中，可以基于匀场线圈磁场分布模型中m个通道的匀场线圈单元的磁场分布信息以及n个目标对象的对象静磁场分布信息，确定 目标静磁场的磁场分布信息。具体地，可以利用目标函数确定目标静磁场的磁场分布信息。该目标函数的表达式如下：
其中，F表示目标静磁场的磁场分布信息；C
j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的电流大小，C
j数值大小具体与匀场线圈单元的匝数以及源电流的微小线元素等信息相关；b
j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的磁场分布信息，可以通过在匀场线圈磁场分布模型建模时确定的磁场分布信息表达式确定b
j的值；B
i为第i个所述目标对象的对象静磁场分布信息。
通过该目标函数，能够准确地表示目标静磁场的磁场分布情况，使得后续根据该目标函数能够准确地实现匀场线圈参数调节，得到满足预设条件的目标静磁场。
可选地，所述调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数，包括：
根据粒子群算法和所述目标函数，调整匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场分布的标准差小于预设阈值或者直至所述粒子群算法的迭代次数到达预设次数，得到目标匀场线圈参数。
本申请实施例中，具体可以根据匀场线圈磁场分布模型中的匀场线圈参数的约束范围，确定一定数目的匀场线圈参数值组成粒子群。之后，通过粒子群算法实现以下步骤：
A1：在该粒子群中获取初始的一组匀场线圈参数值，基于该匀场线圈参数值和目标函数，确定目标静磁场的磁场分布的标准差；
A2：若该标准差小于预设阈值或者粒子群算法的迭代次数到达预设次数，则以当前该组匀场线圈参数值作为目标匀场线圈参数的值；否则，根据该标准差确定局部最优匀场线圈参数和全局最优匀场线圈参数；
A3：根据该局部最优匀场线圈参数和全局最优匀场线圈参数，从粒子群中 获取下一组匀场线圈参数值，并基于该匀场线圈参数值和目标函数，确定当前目标静磁场的磁场分布的标准差；之后，返回执行步骤A2。
本申请实施例中，目标静磁场的磁场分布的标准差小于预设阈值能够直接表示该目标静磁场的磁场分布较为均匀，而粒子群算法的迭代次数到达预设次数也能够表示当前已经在参数范围内查找到较优的能够使得目标静磁场的磁场分布较为均匀的目标匀场线圈参数。通过粒子群算法，能够快速准确地确定满足上述两个条件中的任意一项的目标匀场线圈参数，提高匀场效率。
可选地，所述根据粒子群算法和所述目标函数，调整匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场分布的标准差小于预设阈值或者直至所述粒子群算法的迭代次数到达预设次数，得到目标匀场线圈参数，包括：
针对设置了不同通道数的各个匀场线圈磁场分布模型，分别根据粒子群算法和所述目标函数，调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述粒子群算法的迭代次数到达预设次数，得到各个所述匀场线圈磁场分布模型分别对应的子目标匀场线圈参数；
根据各个所述匀场线圈磁场分布模型分别对应的子目标匀场线圈参数和所述目标函数，确定各个所述匀场线圈磁场分布模型分别对应的所述目标静磁场的磁场分布的标准差；
将所述目标静磁场的磁场分布的标准差最小的所述匀场线圈磁场分布模型确定为目标匀场线圈磁场分布模型，并以所述目标匀场线圈磁场分布模型的通道数和子目标匀场线圈参数参数作为目标匀场线圈参数。
匀场线圈磁场分布模型中，匀场线圈单元的通道数可以在预设范围内调整，例如，该通道数的调整范围可以为3～6。本申请实施例中，可以通过通道数的设置，确定每个通道数情况下分别对应的各个匀场线圈磁场分布模型。例如，可以确定通道数分别为3、4、5、6的4个匀场线圈分布模型。之后，在每个对应了固定通道数的匀场线圈磁场分布模型中，分别根据粒子群算法和目标函数 调整匀场线圈磁场分布模型中的除通道数以外的匀场线圈参数，直至粒子群算法的迭代次数到达预设次数时，得到该匀场线圈磁场分布模型的最优匀场线圈参数作为子目标匀场线圈参数。通过该方法，可以确定各个对应固定通道数的匀场线圈磁场分布模型分别对应的子目标匀场线圈参数。
示例性地，对于一个固定通道数为m1的的匀场线圈磁场分布模型，可以该模型中的匀场线圈的尺寸大小d、空间位置，电流大小和匝数作为该匀场线圈磁场分布模型中可调节的匀场线圈参数，设计对应的粒子群。具体地，该粒子群中包含N组参数，N的取值范围可以为20～50，每组参数中，可以包含D＝4*m1个根据匀场线圈参数约束范围确定的匀场线圈参数值(具体包括m1个尺寸大小参数值、m1个空间位置参数值、m1个电流大小参数值、m1个匝数参数值)。针对该粒子群，通过以下的步骤实现粒子群算法，得到该匀场线圈磁场分布模型对应的子目标匀场线圈参数：
B1：初始化粒子群，对粒子群中每组参数赋予随机的初始位置和速度。
B2：根据速度更新公式和位置更新公式，更新当前的粒子群；其中速度更新公式为：
位置更新公式为：
在以上公式中，
表示第k次迭代参数i的速度，
表示第k次迭代参数i的位置；pbest
i表示参数i的历史最佳位置，gbest
i表示参数i的全局最佳位置；c
1，c
2表示加速度常数，一般设置为1.4962，r
1，r
2表示两个随机参数，取值范围0～1，以增加搜索的随机性，w表示惯性权重，一般设置为0.7298，用来调节对求解空间的搜索范围。参数的限制条件可根据实际应用来设置。例如，在一个实施例中，给出了一种用于老鼠大脑成像的5通道局部匀场线圈参数限制条件，在优化设计过程中，5个匀场线圈单元分布在直径为70mm(“mm”表示毫米)的圆柱体上，线圈单元匝数为1，每个线圈单元的电流限制条件为[-2 2]A(“A”表示电流单位：安培)，5个线圈单元都为一样的正方形，边长限制条件为[20 50]mm，正方形的在圆柱体上分布的角度限制条件为[-π π]，以 老鼠大脑的中心为中心，正方形中心在z轴上的限制条件为[-25 25]mm。
B3：根据目标函数，计算每组参数代入目标函数之后，求得的目标静磁场的标准差，并根据该标准差确定是否更新历史最佳位置或者全局最佳位置。具体地，局部优化过程中，对每一组参数，将其当前位置的标准差值与其历史最佳位置(pbest)对应的标准差值比较，如果当前位置的标准差值更小，则用当前位置更新历史最佳位置。在全局优化过程中，对每一组参数，将其当前位置的标准差值与其全局最佳位置(gbest)对应的标准差值比较，如果当前位置的标准差值更小，则用当前位置更新全局最佳位置。
B4：判断当前的迭代次数是否到达预设次数，若是，则以当前的全局最佳位置对应的该组参数作为当前的匀场线圈磁场分布模型对应的子目标匀场线圈参数。若否，则返回执行步骤B2。
在一个实施例中，通过上述的步骤B1至步骤B4，对5通道的局部匀场线圈进行粒子群算法计算，得到的子目标匀场线圈参数包括：5个匀场线圈单元分别对应的电流为2A、-1.6256A、0.3702A、-2A、-1.4978A，匀场线圈单元边长为20毫米，在圆柱体上分布的角度分别为1.0471弧度、1.9625弧度、-2.9783弧度、1.5920弧度、-2.6117弧度，线圈单元中心在z轴上的位置与坐标轴原点的距离分别为：15.5毫米、25.0毫米、-16.9毫米、5.7毫米、-7.0毫米。
通过上述的方法，确定不同通道数的各个匀场线圈磁场分布模型后的子目标匀场线圈参数后，对于每个匀场线圈磁场分布模型，将其对应的子目标匀场线圈参数代入目标函数进行计算，确定该匀场线圈分布模型对应的目标静磁场的磁场分布的标准差。
之后，将对应的标准差最小的匀场线圈磁场分布模型确定为磁场分布最均匀的目标匀场线圈磁场分布模型。此时，将该目标匀场线圈分布模型的通道数及其对应的子目标匀场线圈参数组合作为目标匀场线圈参数，从而最大化地实现磁共振系统的匀场效果。
本申请实施例中，通过对不同通道数的匀场线圈磁场分布模型分别求解最 优的子目标匀场线圈参数，之后再进一步根据各个子目标匀场线圈确定的目标静磁场的磁场分布均匀度，确定通道数最优的目标匀场线圈磁场分布模型，从而能够实现匀场线圈的通道数优化，提升匀场效果。
在一个实施例中，可以获取8个对象的B0磁场图像，并以其中5个对象的B0磁场图像作为目标对象的对象静磁场分布信息，通过上述的步骤S101至步骤S103得到目标匀场线圈参数。之后，以剩余的3个对象的B0磁场图像作为测试组，基于该目标匀场线圈参数测试磁共振系统中的静磁场匀场效果。在一次实验中，通过本申请实施例的方法确定目标匀场线圈参数后，基于该目标匀场线圈参数，以三个老鼠大脑的B0磁场图像作为测试组，测试得到磁共振系统中磁场的非均匀性可以减少25％-37％。
作为示例而非限定，图3示出了本申请实施例提供的不同结构的匀场线圈性能仿真匀场结果对比；其中，中MC8表示通道数为8的多线圈，LC3表示通道数为3的局部匀场线圈，其他的以此类推，Basic set表示基本设置，d表示线圈单元的边长，L为匀场线圈的总长度。由图可以看出，局部匀场线圈能够以较少的通道数实现良好的匀场效果。通过测试，局部匀场线圈对射频线圈的信噪比影响控制在5％之内，在实现较好的匀场效果的同时，不会对射频线圈造成较大的干扰。
应理解，上述实施例中各步骤的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
实施例二：
图4示出了本申请实施例提供的一种匀场装置的结构示意图，为了便于说明，仅示出了与本申请实施例相关的部分：
该匀场装置包括：获取单元41、目标静磁场确定单元42、目标匀场线圈参数确定单元43。其中：
获取单元41，用于获取目标对象对应的对象静磁场分布信息，所述对象静 磁场分布信息为所述目标对象在磁共振系统的主磁体作用下的静磁场分布信息。
目标静磁场确定单元42，用于根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场。
目标匀场线圈参数确定单元43，用于调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数。
可选地，所述匀场线圈参数包括匀场线圈的通道数、尺寸大小、空间位置、电流大小、匝数中的任意一项或者多项。
可选地，所述匀场装置还包括：
模型确定单元，用于根据毕奥萨伐尔定律，确定所述匀场线圈磁场分布模型的磁场分布信息。。
可选地，所述获取单元41，具体用于获取n个目标对象分别对应的对象静磁场分布信息，其中，n为大于1的正整数；
对应地，所述目标静磁场确定单元42，用于根据所述n个目标对象分别对应的所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场。
可选地，所述匀场线圈磁场分布模型包括m个通道的匀场线圈单元，m为大于1的正整数；所述目标静磁场确定单元42，具体用于利用目标函数
确定目标静磁场；其中，F为所述目标静磁场的磁场分布信息，C
j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的电流大小，b
j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的磁场分布信息，B
i为第i个所述目标对象的对象静磁场分布信息。
可选地，所述目标匀场线圈参数确定单元43，具体用于根据粒子群算法和所述目标函数，调整匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场分布的标准差小于预设阈值或者直至所述粒子群算法的迭代次数到达预设次数，得到目标匀场线圈参数。
可选地，在所述目标匀场线圈参数确定单元43中，所述根据粒子群算法和所述目标函数，调整匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场分布的标准差小于预设阈值或者直至所述粒子群算法的迭代次数到达预设次数，得到目标匀场线圈参数，包括：
针对设置了不同通道数的各个匀场线圈磁场分布模型，分别根据粒子群算法和所述目标函数，调整所述匀场线圈磁场分布模型的子匀场线圈参数，直至所述粒子群算法的迭代次数到达预设次数，得到各个所述匀场线圈磁场分布模型分别对应的子目标匀场线圈参数；
根据各个所述匀场线圈磁场分布模型分别对应的子目标匀场线圈参数和所述目标函数，确定各个所述匀场线圈磁场分布模型分别对应的所述目标静磁场的磁场分布的标准差；
将所述目标静磁场的磁场分布的标准差最小的所述匀场线圈磁场分布模型确定为目标匀场线圈磁场分布模型，并以所述目标匀场线圈磁场分布模型的通道数和子目标匀场线圈参数作为目标匀场线圈参数。
需要说明的是，上述装置/单元之间的信息交互、执行过程等内容，由于与本申请方法实施例基于同一构思，其具体功能及带来的技术效果，具体可参见方法实施例部分，此处不再赘述。
实施例三：
图5是本申请一实施例提供的电子设备的示意图。如图5所示，该实施例的电子设备5包括：处理器50、存储器51以及存储在所述存储器51中并可在所述处理器50上运行的计算机程序52，例如匀场程序。所述处理器50执行所述计算机程序52时实现上述各个匀场方法实施例中的步骤，例如图1所示的步骤S101至S103。或者，所述处理器50执行所述计算机程序52时实现上述各装置实施例中各模块/单元的功能，例如图4所示获取单元41至目标匀场线圈参数确定单元43的功能。
示例性的，所述计算机程序52可以被分割成一个或多个模块/单元，所述 一个或者多个模块/单元被存储在所述存储器51中，并由所述处理器50执行，以完成本申请。所述一个或多个模块/单元可以是能够完成特定功能的一系列计算机程序指令段，该指令段用于描述所述计算机程序52在所述电子设备5中的执行过程。
所述电子设备5可以是桌上型计算机、笔记本、掌上电脑及云端服务器等计算设备。所述电子设备可包括，但不仅限于，处理器50、存储器51。本领域技术人员可以理解，图5仅仅是电子设备5的示例，并不构成对电子设备5的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件，例如所述电子设备还可以包括输入输出设备、网络接入设备、总线等。
所称处理器50可以是中央处理单元(Central Processing Unit，CPU)，还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
所述存储器51可以是所述电子设备5的内部存储单元，例如电子设备5的硬盘或内存。所述存储器51也可以是所述电子设备5的外部存储设备，例如所述电子设备5上配备的插接式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等。进一步地，所述存储器51还可以既包括所述电子设备5的内部存储单元也包括外部存储设备。所述存储器51用于存储所述计算机程序以及所述电子设备所需的其他程序和数据。所述存储器51还可以用于暂时地存储已经输出或者将要输出的数据。
所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，仅以上述各功能单元、模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能单元、模块完成，即将所述装置的内部结构划分成不同的功能单元或模块，以完成以上描述的全部或者部分功能。实施例中的各功 能单元、模块可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中，上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。另外，各功能单元、模块的具体名称也只是为了便于相互区分，并不用于限制本申请的保护范围。上述系统中单元、模块的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述或记载的部分，可以参见其它实施例的相关描述。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的实施例中，应该理解到，所揭露的装置/电子设备和方法，可以通过其它的方式实现。例如，以上所描述的装置/电子设备实施例仅仅是示意性的，例如，所述模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通讯连接可以是通过一些接口，装置或单元的间接耦合或通讯连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元 中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的模块/单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实现上述实施例方法中的全部或部分流程，也可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一计算机可读存储介质中，该计算机程序在被处理器执行时，可实现上述各个方法实施例的步骤。其中，所述计算机程序包括计算机程序代码，所述计算机程序代码可以为源代码形式、对象代码形式、可执行文件或某些中间形式等。所述计算机可读介质可以包括：能够携带所述计算机程序代码的任何实体或装置、记录介质、U盘、移动硬盘、磁碟、光盘、计算机存储器、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、电载波信号、电信信号以及软件分发介质等。需要说明的是，所述计算机可读介质包含的内容可以根据司法管辖区内立法和专利实践的要求进行适当的增减，例如在某些司法管辖区，根据立法和专利实践，计算机可读介质不包括电载波信号和电信信号。
以上所述实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围，均应包含在本申请的保护范围之内。
Claims (10)
- 一种匀场方法，其特征在于，包括：获取目标对象对应的对象静磁场分布信息，所述对象静磁场分布信息为所述目标对象在磁共振系统的主磁体作用下的静磁场分布信息；根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场；调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数。
- 如权利要求1所述的匀场方法，其特征在于，所述匀场线圈参数包括匀场线圈的通道数、尺寸大小、空间位置、电流大小、匝数中的任意一项或者多项。
- 如权利要求1所述的匀场方法，其特征在于，在所述获取目标对象对应的对象静磁场分布信息之前，还包括：根据毕奥萨伐尔定律，确定所述匀场线圈磁场分布模型的磁场分布信息。
- 如权利要求1所述的匀场方法，其特征在于，所述获取目标对象对应的对象静磁场分布信息，包括：获取n个目标对象分别对应的对象静磁场分布信息，其中，n为大于1的正整数；对应地，所述根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场，包括：根据所述n个目标对象分别对应的所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场。
- 如权利要求4所述的匀场方法，其特征在于，所述匀场线圈磁场分布模型包括m个通道的匀场线圈单元，m为大于1的正整数；所述根据所述n个目标对象分别对应的所述对象静磁场分布信息和预设的匀场线圈磁场分布模型， 确定目标静磁场，包括：利用目标函数确定目标静磁场；
其中，F为所述目标静磁场的磁场分布信息，C j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的电流大小，b j为所述匀场线圈磁场分布模型中第j个通道的匀场线圈单元的磁场分布信息，B i为第i个所述目标对象的对象静磁场分布信息。 - 如权利要求5所述的匀场方法，其特征在于，所述调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数，包括：根据粒子群算法和所述目标函数，调整匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场分布的标准差小于预设阈值或者直至所述粒子群算法的迭代次数到达预设次数，得到目标匀场线圈参数。
- 如权利要求6所述的匀场方法，其特征在于，所述根据粒子群算法和所述目标函数，调整匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场分布的标准差小于预设阈值或者直至所述粒子群算法的迭代次数到达预设次数，得到目标匀场线圈参数，包括：针对设置了不同通道数的各个匀场线圈磁场分布模型，分别根据粒子群算法和所述目标函数，调整所述匀场线圈磁场分布模型的子匀场线圈参数，直至所述粒子群算法的迭代次数到达预设次数，得到各个所述匀场线圈磁场分布模型分别对应的子目标匀场线圈参数；根据各个所述匀场线圈磁场分布模型分别对应的子目标匀场线圈参数和所述目标函数，确定各个所述匀场线圈磁场分布模型分别对应的所述目标静磁场的磁场分布的标准差；将所述目标静磁场的磁场分布的标准差最小的所述匀场线圈磁场分布模型确定为目标匀场线圈磁场分布模型，并以所述目标匀场线圈磁场分布模型的通道数和子目标匀场线圈参数作为目标匀场线圈参数。
- 一种匀场装置，其特征在于，包括：获取单元，用于获取目标对象对应的对象静磁场分布信息，所述对象静磁场分布信息为所述目标对象在磁共振系统的主磁体作用下的静磁场分布信息；目标静磁场确定单元，用于根据所述对象静磁场分布信息和预设的匀场线圈磁场分布模型，确定目标静磁场；目标匀场线圈参数确定单元，用于调整所述匀场线圈磁场分布模型中的匀场线圈参数，直至所述目标静磁场的磁场均匀度满足预设条件，得到目标匀场线圈参数。
- 一种电子设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，当所述处理器执行所述计算机程序时，使得电子设备实现如权利要求1至7任一项所述方法的步骤。
- 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，当所述计算机程序被处理器执行时，使得电子设备实现如权利要求1至7任一项所述方法的步骤。
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