Magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization

Abstract

The present invention belongs to the field of magnetic particle imaging technology and relates to a magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization. It aims to solve the problems of existing imaging technology free point scanning prone to information redundancy, low resolution, and insufficient response signal representation under low gradient conditions. The present invention includes: setting magnetic field generation-related parameters and measurement methods for the rotating Cartesian angle scanning trajectory of the magnetic field free point; constructing a harmonic graph of the system function at each rotation angle; constructing a system matrix at each rotation angle, analyzing the system matrix at each angle and the weights and contributions of each frequency component therein to determine the optimal system matrix; constructing an observation vector sequence; and reconstructing the magnetic particle image. The present invention reconstructs the image by rotating the Cartesian scanning trajectory of the magnetic field free point and weighting the system matrix under multi-angle conditions, enriching the system matrix and particle response representation under low gradient conditions and improving imaging resolution.

Description

Technical Field

[0001] The present invention belongs to the technical field of magnetic particle imaging, and in particular relates to a magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization. Background Art

[0002] In recent years, in vivo non-invasive molecular imaging technology has developed rapidly, enabling the effective observation of a variety of biomolecules in vivo. Among them, magnetic particle imaging, an emerging technology based on the nonlinear magnetization response of magnetic nanoparticles, has attracted considerable attention. Compared with traditional imaging methods, magnetic particle imaging technology has significant advantages. It has high sensitivity and high spatial resolution, and can accurately identify subtle differences when detecting small lesions. It has no radiation hazard, is safe for the human body, and is suitable for multiple examinations. It has no background signal interference, resulting in clear images and avoiding interference with diagnosis. It has no imaging depth limit and can obtain information deep into the body. It has great application potential, especially in deep-seated micro-tumor detection and cardiovascular and cerebrovascular function monitoring.

[0003] Magnetic particle imaging technology uses a combination of static and dynamic magnetic fields to detect the concentration distribution of magnetic nanoparticle tracers. The static magnetic field (gradient magnetic field) contains low-magnetic field regions, such as elliptical magnetic field free points or linear magnetic field free lines. The dynamic field is a uniformly alternating excitation magnetic field that is used to propel the low-magnetic field region within the imaging field of view and stimulate the magnetic nanoparticles to produce nonlinear characteristic signals, thereby achieving spatial encoding of the magnetic nanoparticle concentration. Although the magnetic field free point has a small low-magnetic field range, it occupies an important position in research and application due to its precise positioning, diverse scanning trajectories, and high imaging resolution.

[0004] The system matrix method is a key technology in the signal-to-image reconstruction process of magnetic particle imaging. Its main process involves measuring the signal spectrum of a unit sample at each pixel in the imaging field of view. After screening, a system matrix is ​​constructed in the frequency domain. The signal of the measured object is quantized into an observation vector, and a system of linear equations is established and solved to reconstruct the image. Existing magnetic particle imaging systems based on magnetic field free points require the free points to be driven to cover the entire imaging field of view for accurate reconstruction. Traditional methods use a combination of excitation and driving magnetic fields to drive the free points along a preset trajectory (such as Cartesian or Lissajous scanning trajectories) to cover the imaging field of view. However, these conventional scanning trajectories have numerous problems. In low-gradient conditions, the free points are large, the particle response signal is weak, and the reconstruction process lacks useful information, resulting in reduced resolution. Furthermore, conventional preset scanning trajectories only allow the free points to scan each grid point in the field of view at a single angle. Although the free points pass through the same grid point multiple times within a scanning cycle, the resulting time-domain signals have high information similarity and redundancy, lacking the representation of signals generated by magnetic particles under excitation at other angles, resulting in poor imaging quality.

[0005] Therefore, in order to improve the resolution and imaging effect of magnetic particle imaging, it is urgent to propose a more effective magnetic field free point imaging method based on the system matrix. Summary of the Invention

[0006] In order to solve the above-mentioned problems in the prior art, namely, to solve the problems of redundant scanning information of magnetic particle imaging free points and insufficient representation of particle concentration-response signals under low resolution and low gradient conditions in the prior art, the present invention proposes a magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization, which is applied to a three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point. The image is reconstructed by rotating the Cartesian scanning trajectory of the magnetic field free point and weighting the system matrix under multi-angle. The method includes:

[0007] Step S100, setting scanning parameters, starting and running the three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point;

[0008] Step S200: using the low-frequency motion direction of the Cartesian scanning trajectory as the main motion direction of the magnetic field free point, and the angle between the main motion direction of the magnetic field free point and the perpendicular line of the x-direction receiving coil as the scanning trajectory angle, setting the rotation angle and rotation sequence of the Cartesian scanning trajectory; and rotating the magnetic field free point according to the rotation angle and rotation sequence;

[0009] Step S300: measuring the signal of a unit sample at each pixel within the imaging field of view, and then constructing a harmonic diagram of the system function at each rotation angle;

[0010] Step S400: calibrating the system function harmonic graph to obtain system matrices at different angles, performing frequency weighted selection at a single angle and multi-angle adaptive angle selection, determining a two-dimensional weight factor, and obtaining the optimal system matrix at each rotation angle based on the two-dimensional weight factor;

[0011] Step S500: measuring the response signal of the target object to be imaged at each rotation angle, and constructing an observation vector sequence at each rotation angle based on the two-dimensional weight factor;

[0012] Step S600: Merge the observation vector sequences and the optimal system matrix at each rotation angle by column, and after merging, construct a linear equation system; solve the linear equation system to obtain a reconstructed magnetic particle image corresponding to the target object to be imaged.

[0013] In some preferred embodiments, the rotation angle of the Cartesian scanning trajectory is set as follows:

[0014] Assuming that the basic trajectory of the Cartesian scanning trajectory is a grid motion along the x and y directions, the specific expression is as follows:

[0015] ;

[0016] ;

[0017] in, and Represent the driving magnetic field in the x and y directions respectively, A represents the magnetic field amplitude, and are the changing frequencies of the trajectory in the x and y directions respectively; when Obtain a basic Cartesian trajectory along the x-direction excitation;

[0018] Set the rotation parameters :

[0019] ;

[0020] The X-axis and Z-axis dual-axis excitation magnetic fields are The trigonometric function processing of the angle is performed, and the rotation transformation is performed based on the basic Cartesian trajectory to obtain the main direction of the magnetic field free point: The rotation Cartesian trajectory of :

[0021] ;

[0022] in, For the rotation angle, the multi-angle Cartesian trajectory is set by setting a set of rotation angles Take measurements.

[0023] In some preferred embodiments, the rotation order of the Cartesian scanning trajectory is set as follows:

[0024] With the initial direction of the basic Cartesian trajectory being 0°, the trajectory is rotated in steps of equal or unequal intervals to ensure that the range of motion of the magnetic field free point can cover the entire imaging field of view, and rotates a total of N angles; wherein N represents the set number.

[0025] In some preferred embodiments, the optimal system matrix at each rotation angle is obtained by:

[0026] Step S410: Obtain the system matrix at each rotation angle of the Cartesian scanning trajectory , is the rotation angle, ;

[0027] Step S420: performing a selection operation on the system matrix at each rotation angle according to the constructed evaluation function to obtain the weight of each angle;

[0028] The selection operation includes elimination, low weight or merging; the evaluation function includes contribution evaluation function and redundancy evaluation function;

[0029] Step S430: Analyze the weights and contributions of the various frequency components of the system matrix at a single angle to determine the frequency weighting matrix at the rotation angle;

[0030] Step S440: Multiply the weight of each angle by the corresponding frequency weighting matrix to obtain a two-dimensional weight factor , perform global weighting on each system matrix based on the two-dimensional weight factor to generate the optimal system matrix at each rotation angle .

[0031] In some preferred embodiments, the weight of each angle is obtained by:

[0032] Step S421: Evaluate the contribution of the system matrix at each rotation angle. The contribution of each angle is:

[0033] ;

[0034] in, The angle is The system matrix of , is the final reconstructed image;

[0035] Step S422: Redundancy evaluation is performed on the system matrix at each rotation angle. The redundancy at each angle is:

[0036] ;

[0037] in, For two different rotation angles, 、 The angle is 、 The system matrix;

[0038] Step S423: Screen the system matrix of each angle according to contribution and redundancy, and set the dynamic threshold 、 , filter out reviews Angles above a predetermined threshold are assigned weights;

[0039] ;

[0040] Then, the system matrix at each angle is for:

[0041] ;

[0042] in, , is the weighted matrix for multi-angle screening, i.e., the angle screening weight, and the vector in the matrix is the weight of each angle, , .

[0043] In some preferred embodiments, a system of linear equations is constructed:

[0044] ;

[0045] in, , is the response signal of the target object to be imaged at each rotation angle; C represents the discrete vector form of the target object to be imaged.

[0046] Beneficial effects of the present invention:

[0047] The present invention reconstructs images by using the Cartesian scanning trajectory of the rotating magnetic field free point and the weighted multi-angle system matrix, reducing redundant information and computational complexity while maintaining high sensitivity and image quality, optimizing reconstruction efficiency, and ultimately generating a comprehensive system matrix that is more comprehensive in directional information coverage. The reconstruction effect is superior to traditional methods under low-gradient fields, providing higher-quality image data for the application of magnetic particle imaging technology.

[0048] By adaptively screening and weighting the angle and frequency components that have a significant impact on imaging quality, the resolution of magnetic particle imaging is significantly improved, and the spatial resolution under low gradient fields is significantly improved;

[0049] The present invention introduces a multi-angle Cartesian trajectory detection method. By setting a rotating Cartesian angle scanning trajectory and related parameters based on a magnetic field free point, the Cartesian scanning trajectory of the rotating magnetic field free point effectively enriches the system matrix and particle response characterization under low gradients, solving the problem of insufficient particle concentration-response signal characterization in existing methods at low gradients. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Other features, objects and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0051] Figure 1 It is a flow chart of the magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization of the present invention;

[0052] Figure 2 This is a schematic diagram of the structure of the three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on the magnetic field free point of the present invention.

[0053] Figure 3This is a schematic diagram of the magnet structure of the three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point of the present invention;

[0054] Figure 4 This is a time domain diagram of the Cartesian scanning trajectory when the rotation angle is 0° in an embodiment of the present invention;

[0055] Figure 5 This is a time domain diagram of the Cartesian scanning trajectory when the rotation angle is 30° in an embodiment of the present invention;

[0056] Figure 6 This is a time domain diagram of the Cartesian scanning trajectory when the rotation angle is 60° in an embodiment of the present invention;

[0057] Figure 7 It is a time domain diagram of the Cartesian scanning trajectory when the rotation angle is 90° in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0059] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0060] The present invention provides a magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization. Existing magnetic particle imaging methods lack sufficient system matrix representation of particle concentration-response signals during measurement under low-gradient conditions, severely limiting the imaging resolution of magnetic particle imaging devices. To reduce redundant information and computational complexity and optimize reconstruction efficiency, the present invention reconstructs images using a Cartesian scanning trajectory of a rotating magnetic field free point and a weighted multi-angle system matrix. This enriches the system matrix and particle response representation under low-gradient conditions and improves the resolution of magnetic particle imaging.

[0061] The present invention provides a magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization, the method comprising the following steps:

[0062] Step S100, setting scanning parameters, starting and running the three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point;

[0063] Step S200: using the low-frequency motion direction of the Cartesian scanning trajectory as the main motion direction of the magnetic field free point, and the angle between the main motion direction of the magnetic field free point and the perpendicular line of the x-direction receiving coil as the scanning trajectory angle, setting the rotation angle and rotation sequence of the Cartesian scanning trajectory; and rotating the magnetic field free point according to the rotation angle and rotation sequence;

[0064] Step S300: measuring the signal of a unit sample at each pixel within the imaging field of view, and then constructing a harmonic diagram of the system function at each rotation angle;

[0065] Step S400: calibrating the system function harmonic graph to obtain system matrices at different angles, performing frequency weighted selection at a single angle and multi-angle adaptive angle selection, determining a two-dimensional weight factor, and obtaining the optimal system matrix at each rotation angle based on the two-dimensional weight factor;

[0066] Step S500: measuring the response signal of the target object to be imaged at each rotation angle, and constructing an observation vector sequence at each rotation angle based on the two-dimensional weight factor;

[0067] Step S600: Merge the observation vector sequences and the optimal system matrix at each rotation angle by column, and after merging, construct a linear equation system; solve the linear equation system to obtain a reconstructed magnetic particle image corresponding to the target object to be imaged.

[0068] In order to more clearly illustrate the magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization of the present invention, the following is combined with Figure 1 Each step in the embodiment of the present invention is described in detail.

[0069] The first embodiment of the present invention provides a magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization, comprising the following steps S100 to S600, and is applied to a three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point.

[0070] The three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point is as follows: Figure 2As shown, it consists of four parts: gradient end, driving and excitation end, receiving end, and compensation end. The gradient end consists of a pair of Maxwell coils and two iron cores. The two coils operate in an independently powered low-frequency AC superimposed DC bias mode, responsible for generating a magnetic field free point (FFP) and driving the FFP to move along the y direction. The driving and excitation end can apply high-frequency and low-frequency AC simultaneously, and the two pairs of Helmholtz coils are responsible for moving the FFP and exciting the magnetic particles to generate nonlinear response signals. The receiving end is set in the x and z axis directions. The x-axis receiving coil is cylindrical, and the z-axis is a saddle-shaped coil that is evenly symmetrical up and down. Both use 0.4mm diameter Litz wire and are responsible for receiving the response signals of the particles in these two directions respectively. The compensation coil is divided into an external excitation compensation in the x direction and a built-in compensation coil in the z direction, so as to eliminate the direct feedthrough signal generated by the excitation end at the receiving end.

[0071] like Figure 3 As shown in the figure, the pair of coils at the gradient end responsible for generating the magnetic field free point (FFP) and driving the FFP in the y-direction are named Cy1 and Cy2, respectively. The two pairs of coils at the drive and excitation end responsible for two-dimensional movement of the FFP are named Cx and Cz, respectively. The magnetic field generated by these three pairs of coils can achieve three-dimensional movement of the FFP. The magnetic field generated by the Cx and Cz coils not only drives the FFP in two dimensions but also provides high-frequency excitation to generate MPI excitation signals. The receiving coils are named Rx and Rz, and their directions are the same as Cx and Cz. They are responsible for sensing the MPI signals of the magnetic nanoparticles. The external excitation compensation coil in the x-direction is named Sx, and the internal compensation coil in the z-direction is named Sc. They are responsible for eliminating the direct feedthrough of the Cx and Cz excitation signals on Rx and Rz.

[0072] Step S100 , setting scanning parameters, starting and running the three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point.

[0073] Preferably, in this embodiment, a fixed dual-channel excitation field is used to set the excitation field magnetic field to realize multi-angle rotation Cartesian measurement of the magnetic field free point; the above-mentioned method of setting the rotation angle of the Cartesian scanning trajectory is:

[0074] First define the basic Cartesian trajectory:

[0075] Assuming that the basic trajectory of the Cartesian scanning trajectory is a grid motion along the x and y directions, the specific expression is as follows:

[0076] ;

[0077] ;

[0078] in, and Represent the driving magnetic field in the x and y directions respectively, A represents the magnetic field amplitude, and are the changing frequencies of the trajectory in the x and y directions respectively; when Obtain a basic Cartesian trajectory along the x-direction excitation;

[0079] Set the rotation parameters And introduce:

[0080] ;

[0081] The X-axis and Z-axis dual-axis excitation magnetic fields are The trigonometric function processing of the angle is performed, and the rotation transformation is performed based on the basic Cartesian trajectory to obtain the main direction of the magnetic field free point: The rotation Cartesian trajectory of :

[0082] ;

[0083] in, For the rotation angle, the multi-angle Cartesian trajectory is set by setting a set of rotation angles Take measurements.

[0084] Step S200: Using the low-frequency motion direction of the Cartesian scanning trajectory as the main motion direction of the magnetic field free point, and the angle between the main motion direction of the magnetic field free point and the perpendicular line of the x-direction receiving coil as the scanning trajectory angle, set the rotation angle and rotation order of the Cartesian scanning trajectory; and rotate the magnetic field free point according to the rotation angle and the rotation order.

[0085] Preferably, the initial direction of the basic Cartesian trajectory is 0°, and the step rotation is performed in an equal or unequal interval manner to ensure that the motion range of the magnetic field free point can cover the entire imaging field of view, and rotate N angles in total; wherein N represents a set number. Figure 4-7 In this embodiment, it is preferred to rotate to 90°, N is 3, and each rotation is 30°.

[0086] Step S300: Measure the signal of a unit sample at each pixel within the imaging field of view, and then construct a harmonic diagram of the system function at each rotation angle. The method is as follows:

[0087] The time domain signal of a unit sample at each pixel is measured, and a frequency spectrum is obtained through fast Fourier transform; based on the signal-to-noise ratio of the magnetic particle imaging device based on the magnetic field free point, harmonic signals with a signal-to-noise ratio greater than a set signal-to-noise ratio threshold are screened, and the screened harmonic signals are used as first harmonic signals; based on the frequency spectrum, first harmonic signals of the same order at each pixel are synthesized to obtain system function harmonic graphs of different orders.

[0088] Step S400: calibrating the system function harmonic graph to obtain system matrices at different angles, performing frequency weighted selection at a single angle and multi-angle adaptive angle selection, determining a two-dimensional weight factor, and obtaining the optimal system matrix at each rotation angle based on the two-dimensional weight factor;

[0089] Preferably, the optimal system matrix at each rotation angle is obtained by:

[0090] Step S410: Obtain the system matrix at each rotation angle of the Cartesian scanning trajectory , is the rotation angle, ;

[0091] Step S420: performing a selection operation on the system matrix at each rotation angle according to the constructed evaluation function to obtain the weight of each angle;

[0092] The selection operation includes elimination, low weight or merging; the evaluation function includes a contribution evaluation function and a redundancy evaluation function.

[0093] Preferably, the weight of each angle is obtained by:

[0094] Step S421: Evaluate the contribution of the system matrix at each rotation angle. for:

[0095] ;

[0096] in, The angle is The system matrix of , is the final reconstructed image;

[0097] Step S422: Redundancy evaluation of the system matrix at each rotation angle is performed. for:

[0098] ;

[0099] in, For two different rotation angles, 、 The angle is 、 The system matrix;

[0100] Step S423: Screen the system matrix of each angle according to contribution and redundancy, and set the dynamic threshold 、 , filter out reviews Angles above a predetermined threshold are assigned weights;

[0101] ;

[0102] Then, the system matrix at each angle is:

[0103] ;

[0104] in, , is the weighted matrix for multi-angle screening, i.e., the angle screening weight, and the vector in the matrix is the weight of each angle, , .

[0105] Preferably, in this embodiment, the selection operation includes elimination, low weight or merging.

[0106] Step S430: Analyze the weights and contributions of the frequency components of the system matrix at a single angle to determine the frequency weighting matrix at the rotation angle. The method is:

[0107] Step S431: Perform fast Fourier transform on the received signal to extract the frequency components and their amplitude information, analyze the amplitude of the signal at different frequencies, and determine the main frequency components of the signal; use the threshold value to filter the effective frequency and determine the filtering function. :

[0108] ;

[0109] in, is a dynamic threshold, adjusted based on the noise level, h is the signal amplitude; f 0. f 1 represents the driving field frequency, k, k 1 represents the modulation coefficient of the modulation signal;

[0110] Step S432: Extract the corresponding column from the system matrix according to the selected frequency index and calculate the weight matrix :

[0111] ;

[0112] in, The angle is The signal amplitude of the signal received at the time is adjusted based on the signal amplitude or contribution, z Represents frequency components above the dynamic threshold;

[0113] Step S433: Get a certain angle The following is the filtered system matrix:

[0114] ;

[0115] in, For a single angle The frequency weighted matrix of , the vectors in the matrix are the weights of each frequency at that angle; The angle is The system matrix of ;

[0116] Then the frequency screening weight of the system matrix for:

[0117] .

[0118] Step S440: Multiply the weight of each angle by the corresponding frequency weighting matrix to obtain a two-dimensional weight factor. Perform global weighting on each system matrix based on the two-dimensional weight factor to generate the optimal system matrix at each rotation angle. The method is as follows:

[0119] Determine the two-dimensional weight factor based on the angle screening weight and the frequency screening weight , specifically:

[0120] ;

[0121] Based on the two-dimensional weighting factor Perform global weighting on the system matrix to generate the optimal system matrix at each rotation angle :

[0122] ;

[0123] in, .

[0124] By analyzing the multi-angle system matrix and the signal-to-noise ratio of each frequency component and its contribution to the final reconstruction quality, the authors screen out frequency components with the greatest impact on imaging quality and assign greater weights to the system matrix at high-contribution angles. This reduces redundant information and computational complexity, optimizing reconstruction quality and efficiency. This method significantly improves spatial resolution in low-gradient fields while maintaining high sensitivity and image quality. Furthermore, the optimal system matrix provides more comprehensive directional information coverage, resulting in superior reconstruction results compared to traditional methods in low-gradient fields.

[0125] Preferably, the angle screening weight and the frequency screening weight are optimized, and the optimal system matrix is ​​optimized as follows:

[0126] ;

[0127] in, is the optimal system matrix after multi-angle and frequency screening weighting, y is the observed response signal, and x is the concentration distribution to be solved; is a regularization term used to suppress noise or introduce priors; is the regularization term of the angle screening weight, which is used to constrain the sparsity or smoothness of the screening angle; is the regularization term of the frequency screening weight, which is used to constrain the sparsity of the screening frequency; is the angle screening weight, is the frequency screening weight; 、 、 is the regularization weight.

[0128] Further preferably, the angle screening weight and the frequency screening weight are optimized by:

[0129] A. Establishing evaluation indicators as reconstruction quality evaluation criteria, wherein the evaluation indicators include PSNR, SSIM, temporal resolution, and robustness;

[0130] B. Initial angle weight and frequency weights With the initial image ;

[0131] C. Fixed weight and , the image is optimized by solving the following equation:

[0132] ;

[0133] D. Fixed image x , and optimize by updating the weights through the following equation:

[0134] ;

[0135] ;

[0136] E. Alternating Iterative Optimization x 、 、 , until the error converges.

[0137] Step S500: measuring the response signal of the target object to be imaged at each rotation angle, and constructing an observation vector sequence at each rotation angle based on the two-dimensional weight factor;

[0138] Get the response signal at each rotation angle of the Cartesian scanning trajectory:

[0139] ;

[0140] The observation vector sequence at each rotation angle is constructed based on the two-dimensional weight factor:

[0141] ;

[0142] in, The response signal received after scanning at each rotation angle is: is the rotation angle, .

[0143] Step S600: Merge the observation vector sequence and the optimal system matrix at each rotation angle by column, and then construct a linear equation system. Construct the linear equation system:

[0144] ;

[0145] in, , is the response signal of the target object to be imaged at each rotation angle; C represents the discrete vector form of the target object to be imaged;

[0146] The linear equations are solved to obtain a reconstructed magnetic particle image corresponding to the target object to be imaged.

[0147] Although the various steps in the above embodiment are described in the above-mentioned order, those skilled in the art will understand that in order to achieve the effect of this embodiment, different steps do not have to be executed in such an order. They can be executed simultaneously (in parallel) or in a reverse order. These simple changes are within the scope of protection of the present invention.

[0148] A second embodiment of the present invention provides an adaptive optimization magnetic particle imaging and reconstruction system based on multi-angle Cartesian scanning, the system comprising a signal acquisition device and a central processing device;

[0149] The signal acquisition device includes a three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point; the signal acquisition device is configured to set scanning parameters and a rotation angle and rotation sequence of a Cartesian scanning trajectory, and rotate the magnetic field free point according to the rotation angle and rotation sequence; and is further configured to collect a signal of a unit sample at each pixel within the imaging field of view, and collect a response signal of the target object to be imaged at each rotation angle;

[0150] The central processing unit includes a CPU and a GPU; the central processing unit includes:

[0151] A data processing module is configured to construct a harmonic graph of the system function at each rotation angle based on the signal of the unit sample at each pixel, thereby obtaining the system matrix at different angles; and is further configured to construct an observation vector sequence based on the above response signal;

[0152] The matrix weighting module is configured to perform frequency weighted selection at a single angle and multi-angle adaptive angle selection on the system matrix at different angles to obtain the optimal system matrix at each rotation angle;

[0153] The imaging module is configured to merge the observation vector sequence by column and merge the optimal system matrix under each rotation angle by column, and after merging, construct a linear equation system; solve the linear equation system to obtain a reconstructed magnetic particle image corresponding to the target object to be imaged.

[0154] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working process and related instructions of the system described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0155] It should be noted that the adaptive optimization magnetic particle imaging and reconstruction system based on multi-angle Cartesian scanning provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be further decomposed or combined. For example, the modules in the above embodiment can be combined into one module or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are merely for the purpose of distinguishing the modules or steps and are not to be considered as improper limitations of the present invention.

[0156] An electronic device according to a third embodiment of the present invention includes:

[0157] at least one processor; and

[0158] a memory communicatively connected to at least one of the processors; wherein,

[0159] The memory stores instructions that can be executed by the processor, and the instructions are used to be executed by the processor to implement the above-mentioned magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization.

[0160] A fourth embodiment of the present invention provides a computer-readable storage medium storing computer instructions, wherein the computer instructions are used to be executed by a computer to implement the above-mentioned magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization.

[0161] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes and related instructions of the electronic device and computer-readable storage medium described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0162] Those skilled in the art should be able to appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two, and the programs corresponding to the software modules and method steps can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the art. In order to clearly illustrate the interchangeability of electronic hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0163] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0164] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0165] The terms "first", "second", etc. are used to distinguish similar objects, rather than to describe or indicate a particular order or sequence.

[0166] The term "comprise" or any other similar term is intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0167] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization, applied to a three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point, characterized in that: The method comprises the following steps: Step S100, setting scanning parameters, starting and running the three-dimensional dual-excitation channel symmetrical magnetic particle imaging device based on a magnetic field free point; Step S200: using the low-frequency motion direction of the Cartesian scanning trajectory as the main motion direction of the magnetic field free point, and the angle between the main motion direction of the magnetic field free point and the perpendicular line of the x-direction receiving coil as the scanning trajectory angle, setting the rotation angle and rotation sequence of the Cartesian scanning trajectory; and rotating the magnetic field free point according to the rotation angle and rotation sequence; Step S300: measuring the signal of a unit sample at each pixel within the imaging field of view, and then constructing a harmonic diagram of the system function at each rotation angle; Step S400: calibrating the system function harmonic graph to obtain system matrices at different angles, performing frequency weighted selection at a single angle and multi-angle adaptive angle selection, determining a two-dimensional weight factor, and obtaining the optimal system matrix at each rotation angle based on the two-dimensional weight factor; Step S500: measuring the response signal of the target object to be imaged at each rotation angle, and constructing an observation vector sequence at each rotation angle based on the two-dimensional weight factor; Step S600: Merge the observation vector sequences and the optimal system matrix at each rotation angle by column, and after merging, construct a linear equation system; solve the linear equation system to obtain a reconstructed magnetic particle image corresponding to the target object to be imaged.

2. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 1, characterized in that: Set the rotation angle of the Cartesian scanning trajectory using: Let the basic trajectory of the Cartesian scanning trajectory be the grid motion along the x and y directions, and the specific expression is as follows: ； ； in, and Represent the driving magnetic field in the x and y directions respectively, A represents the magnetic field amplitude, and are the changing frequencies of the trajectory in the x and y directions respectively; when Obtain a basic Cartesian trajectory along the x-direction excitation; Set the rotation parameters : ； The X-axis and Z-axis dual-axis excitation magnetic fields are The trigonometric function processing of the angle is performed, and the rotation transformation is performed based on the basic Cartesian trajectory to obtain the main direction of the magnetic field free point: The rotation Cartesian trajectory of : ； in, For the rotation angle, the multi-angle Cartesian trajectory is set by setting a set of rotation angles Take measurements.

3. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 2, characterized in that: Set the rotation order of the Cartesian scan trajectory using: With the initial direction of the basic Cartesian trajectory being 0°, the trajectory is rotated in steps of equal or unequal intervals to ensure that the range of motion of the magnetic field free point can cover the entire imaging field of view, and rotates a total of N angles; wherein N represents the set number.

4. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 1, characterized in that: The optimal system matrix at each rotation angle is obtained as follows: Step S410: Obtain the system matrix at each rotation angle of the Cartesian scanning trajectory , is the rotation angle, ; Step S420: performing a selection operation on the system matrix at each rotation angle according to the constructed evaluation function to obtain the weight of each angle; The selection operation includes elimination, low weight or merging; the evaluation function includes contribution evaluation function and redundancy evaluation function; Step S430: Analyze the weights and contributions of the various frequency components of the system matrix at a single angle to determine the frequency weighting matrix at the rotation angle; Step S440: Multiply the weight of each angle by the corresponding frequency weighting matrix to obtain a two-dimensional weight factor, and perform global weighting on each system matrix based on the two-dimensional weight factor to generate the optimal system matrix at each rotation angle.

5. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 4, characterized in that: The method to obtain the weight of each angle is: Step S421: Evaluate the contribution of the system matrix at each rotation angle. for: ； in, The angle is The system matrix of , is the final reconstructed image; Step S422: Redundancy evaluation of the system matrix at each rotation angle is performed. for: ； in, For two different rotation angles, 、 The angle is 、 The system matrix; Step S423: Screen the system matrix of each angle according to contribution and redundancy, and set the dynamic threshold 、 , filter out reviews Angles above a predetermined threshold are assigned weights; ； Then, the system matrix at each angle is for: ； in, , is the weighted matrix for multi-angle screening, i.e., the angle screening weight, and the vector in the matrix is the weight of each angle, , .

6. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 4, characterized in that: The frequency weighting matrix under the rotation angle is determined as follows: Step S431: Perform fast Fourier transform on the received signal to extract the frequency components and their amplitude information, analyze the amplitude of the signal at different frequencies, and determine the main frequency-multiple components of the signal; Use the threshold value to filter the effective frequency and determine the filtering function : ； in, is a dynamic threshold, adjusted based on the noise level, h is the signal amplitude; f 0. f 1 represents the driving field frequency, k、 k 1 represents the modulation coefficient of the modulation signal; Step S432: Extract the corresponding column from the system matrix according to the selected frequency index and calculate the weight matrix : ； in, The angle is The signal amplitude of the signal received at the time is adjusted based on the signal amplitude or contribution, z Represents frequency components above the dynamic threshold; Step S433: Get a certain angle The following is the filtered system matrix: ； in, For a single angle The frequency weighted matrix of , the vectors in the matrix are the weights of each frequency at that angle; The angle is The system matrix of ; Then the frequency screening weight of the system matrix for: 。 7. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 5 or 6, characterized in that: The two-dimensional weight factor is obtained as follows: Determine the two-dimensional weight factor based on the angle screening weight and the frequency screening weight , specifically: ； Based on the two-dimensional weighting factor Perform global weighting on the system matrix to generate the optimal system matrix at each rotation angle : ； in, .

8. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 7, characterized in that: The angle screening weight and frequency screening weight are optimized, and the optimal system matrix is ​​optimized as follows: ； in, is the optimal system matrix after multi-angle and frequency screening weighting, y is the observed response signal, and x is the concentration distribution to be solved; is a regularization term used to suppress noise or introduce priors; is the regularization term of the angle screening weight, which is used to constrain the sparsity or smoothness of the screening angle; is the regularization term of the frequency screening weight, which is used to constrain the sparsity of the screening frequency; is the angle screening weight, is the frequency screening weight; 、 、 is the regularization weight.

9. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 8, characterized in that: The angle screening weight and frequency screening weight are optimized as follows: A. Establishing evaluation indicators as reconstruction quality evaluation criteria, wherein the evaluation indicators include PSNR, SSIM, temporal resolution, and robustness; B. Initial angle weight and frequency weights With the initial image ; C. Fixed weight and , the image is optimized by solving the following equation: ； D. Fix the image x and optimize by updating the weights using the following equation: ； ； E. Alternate iterative optimization x, 、 , until the error converges.

10. The magnetic particle imaging reconstruction method based on multi-angle Cartesian scanning adaptive optimization according to claim 7, characterized in that: Construct a system of linear equations: ； in, , is the response signal of the target object to be imaged at each rotation angle; C represents the discrete vector form of the target object to be imaged.

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