Brain image generation method based on microwave data adaptive time delay phase compensation

Abstract

The invention provides a brain image generation method based on microwave data adaptive time delay phase compensation, and the method comprises the steps: configuring antenna transmitting and receiving parameters which comprise the scanning point number, the frequency stepping and the starting frequency; acquiring microwave data at the frequency point based on the transceiving parameters to obtain a microwave data set in a matrix form; when the collection point number of the microwave data set in the matrix form is the same as the preset collection point number, collection is ended, and the matrix data set is stored; inputting the microwave data of the microwave data set in the matrix form into the constructed adaptive phase compensation neural network; carrying out adaptive time delay phase compensation processing on the microwave data to obtain an output signal; and drawing a regional thermodynamic diagram according to the output signal, and generating a microwave brain image. According to the method, the imaging accuracy and reliability are improved.

Description

Technical Field

[0001] The present invention relates to the field of microwave imaging technology, and in particular to a brain image generation method based on adaptive time delay phase compensation of microwave data. Background Art

[0002] Stroke is one of the most common cardiovascular diseases. Early detection of first or recurrent strokes and monitoring of stroke progression during treatment can enable patients to receive timely and effective treatment. Currently, computed tomography (CT) and magnetic resonance imaging (MRI) are the most commonly used tools for stroke diagnosis. While these existing methods can provide accurate diagnoses, they are too bulky for on-site testing and bedside monitoring. Furthermore, CT is not suitable for frequent examinations due to its ionizing radiation exposure. MRI is very expensive, time-consuming, and not available in all hospitals, especially in rural areas. Therefore, microwave imaging has been introduced as a complementary approach to traditional stroke diagnosis, offering advantages such as low cost, fast scanning speed, portability, and the absence of ionizing radiation. This technology is based on detecting dramatic changes in the dielectric properties of the stroke-affected area relative to surrounding healthy tissue. Its portability and low cost allow the device to be deployed in all hospitals, even at the point of care, making it more accessible to patients in need.

[0003] Current microwave brain imaging techniques primarily utilize contrast source inversion, time delay inversion, and time delay summation. These techniques rely on measuring the propagation coefficient of the signal along the path between the transmitter, the target brain region, and the receiver to determine the time delay and inversion amount. Because the human brain is composed of multiple different tissues, from the outer skull to the inner brain tissue, the thickness and electromagnetic properties of these tissue layers significantly affect the signal propagation speed, which depends on the microwave frequency and the electromagnetic parameters of different tissues at that frequency. Furthermore, since the signal propagation path is not always perpendicular to the tissue layers, this introduces errors in the calculation of the average signal path. This error, especially when multiple signals are superimposed, can affect the final imaging results. This effect is minimal when there are few tissue layers and the electromagnetic parameters between them are not significantly different. However, if there is air between the detection device and the patient's scalp, the significant difference in electromagnetic parameters between air and brain tissue can cause significant signal reflection and scattering on the head surface, resulting in image distortion. Therefore, in practical applications, microwave imaging results are prone to offset and blurring due to the complex distribution of brain tissue, the distance between the antenna and the skull surface varies from person to person, the angle between the transmitted microwave signal and the target to be measured and the skull section is difficult to determine, and the antenna spacing must be fixed a priori. Summary of the Invention

[0004] In view of this, the present invention provides a brain image generation method based on adaptive time delay and phase compensation of microwave data to solve the above problems.

[0005] The present invention provides a brain image generation method based on adaptive time delay and phase compensation of microwave data, comprising: configuring antenna transceiver parameters, wherein the transceiver parameters include the number of scanning points, frequency step, and starting frequency; collecting microwave data at frequency points based on the transceiver parameters to obtain a microwave data set in matrix form; when the number of collection points in the microwave data set in matrix form is the same as a preset number of collection points, terminating the collection and saving the microwave data set in matrix form; inputting the microwave data of the microwave data set in matrix form into a constructed adaptive phase compensation neural network; performing adaptive time delay and phase compensation processing on the microwave data to obtain an output signal; and drawing a regional heat map based on the output signal to generate a microwave brain image.

[0006] In another implementation of the present invention, after inputting the microwave data of the microwave data set in matrix form into the constructed adaptive phase compensation neural network, it also includes: transmitting the microwave data from the input layer of the adaptive phase compensation neural network to the hidden layer, and performing nonlinear mapping on it through radial basis function.

[0007] In another implementation of the present invention, the adaptive time delay and phase compensation processing of the microwave data to obtain an output signal includes: obtaining a feedforward controller based on the microwave data after Laplace transformation through an a priori given amplitude constant and phase constant when there is a time delay when microwaves pass through different tissues resulting in a phase error; using the feedforward controller as a compensation controller, combining the feedforward controller with a feedback controller to obtain the output signal.

[0008] In another implementation of the present invention, the microwave data after Laplace transformation is expressed as:

[0009] Where α is the amplitude constant; θ is the phase constant; x(s) is the microwave signal after Laplace transform; and x(t+θ) is the original microwave signal under the θ phase condition.

[0010] x(t) is the input microwave data, expressed as:

[0011] in, is the microwave signal after phase compensation; N is the number of received microwave signals.

[0012] In another implementation of the present invention, the feedforward controller is expressed as:

[0013] Wherein, x(s+θ) is a microwave signal with a phase error θ.

[0014] In another implementation of the present invention, the feedback controller is expressed as:

[0015] Wherein, τ is the time delay; β is the phase constant, which can be adjusted according to the actual situation. When β>1, it belongs to leading compensation, and when β<1, it belongs to lagging compensation.

[0016] In another implementation of the present invention, the output signal is represented by:

[0017] in, T is the transpose symbol of the matrix; is the Laplace transform of the microwave data received by each antenna; w i is the weight vector represented by each antenna; s i are the transformation vectors of the Laplace transform of the data; W is the weight, p is the control coefficient, and q is the weight update coefficient.

[0018] Another aspect of the present invention provides a brain image generation system based on adaptive time delay and phase compensation of microwave data, comprising: a data acquisition module: configuring antenna transceiver parameters, the transceiver parameters including the number of scanning points, frequency step, and starting frequency; collecting frequency point data based on the transceiver parameters to obtain a matrix data set; when the number of collection points of the microwave data set in matrix form is the same as the preset number of collection points, ending the collection and saving the matrix data set; a data processing module: inputting the microwave data of the microwave data set in matrix form into a constructed adaptive phase compensation neural network; performing adaptive time delay and phase compensation processing on the microwave data to obtain an output signal; and an imaging module: drawing a regional heat map based on the output signal to generate a microwave brain image.

[0019] Another aspect of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of a method for generating a brain image based on adaptive time delay phase compensation of microwave data as described above are implemented. Another aspect of the present invention provides a computer storage medium, characterized in that a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the steps of the brain image generation method based on microwave data adaptive time delay phase compensation as described in any one of the above items are implemented.

[0020] The brain image generation method based on adaptive delay and phase compensation of microwave data of the present invention realizes multi-frequency and multi-antenna sweep reception by controlling the signal transmission and reception format, uses the obtained microwave data as input, constructs an adaptive phase compensation neural network, transmits the data from the input layer to the hidden layer, performs nonlinear mapping on it through radial basis functions, compensates its antecedent according to the delay, and transmits the posterior term to the output layer for output, thereby realizing fast, accurate and effective microwave brain imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. By reading the detailed description of the embodiments below, the advantages and benefits of the solutions will become clear to those skilled in the art. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention.

[0022] Figure 1 1 is a flow chart of a method for generating a brain image based on adaptive time delay and phase compensation of microwave data according to an embodiment of the present invention.

[0023] Figure 2 Schematic diagram of a microwave signal transceiver switch module according to an embodiment of the present invention.

[0024] Figure 3 The figure is a schematic diagram of the overall process of microwave signal acquisition according to an embodiment of the present invention.

[0025] Figure 4 The figure is a schematic diagram of the signal acquisition process of a single frequency point and a single antenna according to an embodiment of the present invention.

[0026] Figure 5 The figure is a schematic diagram of the adaptive delay phase compensation process according to an embodiment of the present invention.

[0027] Figure 6 Schematic diagram of a radial basis function neural network based on time delay phase compensation according to an embodiment of the present invention.

[0028] Figure 7 FIG. 1 is a schematic diagram of imaging result optimization according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and detailedly described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in the embodiments of the present invention should fall within the scope of protection of the embodiments of the present invention.

[0030] Figure 1 A flowchart of a method for generating a brain image based on adaptive time delay and phase compensation of microwave data is provided in an embodiment of the present invention, as shown in FIG. Figure 1 shown.

[0031] S101: Configure antenna transceiver parameters, including scanning points, frequency step, and starting frequency.

[0032] For example, it is necessary to obtain microwave scanning data of multiple frequencies and multiple antennas, so multiple switches are required to be connected in series and parallel to realize single-frequency microwave scanning with single transmission and multiple receptions. The MAX2871 RF chip is controlled by a typical embodiment such as the STM32 microcontroller to transmit high-frequency signals of different frequencies in sequence.

[0033] like Figure 2 As shown in the figure, taking the microwave signal transmission and reception of 16 antennas as an example, to ensure that antennas 1 to 16 can transmit sequentially during each scan and that all antennas except the transmitting antenna can receive signals during the transmission process, the BGSX44MU18 RF switch chip is preferably used to build a switch module. Among them, the 16 antennas are connected to the A1-A4 terminals of the four switch chips respectively. The B1 terminals of the switch chips are all connected to the A1-A4 terminals of the TX switch chip, and they can transmit sequentially through B1. The B4 terminals of the switch chips are all connected to the A1-A4 terminals of the RX switch chip, and they can receive sequentially through B1.

[0034] S102: Collect microwave data at the frequency points based on the transmitting and receiving parameters to obtain a microwave data set in a matrix form.

[0035] For example, Figure 3 As shown in the figure, after ensuring that single-transmit, multi-receive microwave signal transmission and reception can be achieved, configure the antenna transmission and reception parameters, including the number of scan points, frequency step, and start frequency, to complete the collection of single frequency point data. For example, with 16 antennas, complete 16 transmissions of 15 receptions of microwave signals, and obtain a 16*15 matrix data set.

[0036] Specifically, if Figure 4 As shown, the transmission frequency and power are first configured according to the transmission and reception requirements. The reference signal is acquired after the phase-locked loop (PLL) is locked. The input matching (S11) and isolation (S12) parameters during signal transmission are then collected, the Dcache is refreshed, and the RMS amplitude and phase are calculated, with the results for this frequency point saved in the buffer. Typically, calculations are required for the real and imaginary parts of the microwave signal amplitude, the phase intensity and angle, and the linear phase characteristics. The signal received by the computer is in the form of an 8*16*15*5 matrix.

[0037] S103: When the number of acquisition points of the microwave data set in the matrix form is the same as the preset number of acquisition points, the acquisition is ended and the matrix data set is saved.

[0038] Exemplarily, whether the scanning is completed is determined based on the preset number of acquisition points. For example, if 8 frequency points are to be acquired, then after obtaining an 8*16*15 matrix data set, it is determined that the number of acquisition points is sufficient, and the acquisition is ended and saved.

[0039] S104 , inputting the microwave data of the microwave data set in matrix form into the constructed adaptive phase compensation neural network.

[0040] Exemplarily, after the microwave data of all antennas at all frequencies are obtained, they are input into the adaptive phase compensation neural network.

[0041] S105 , performing adaptive time delay phase compensation processing on the microwave data to generate a microwave brain image.

[0042] S106 , drawing a regional thermal map according to the output signal to obtain a microwave brain imaging result.

[0043] The brain image generation method based on adaptive delay and phase compensation of microwave data of the present invention realizes multi-frequency and multi-antenna sweep reception by controlling the signal transmission and reception format, uses the obtained microwave data as input, constructs an adaptive phase compensation neural network, transmits the data from the input layer to the hidden layer, performs nonlinear mapping on it through radial basis functions, compensates its antecedent according to the delay, and transmits the posterior term to the output layer for output, thereby realizing fast, accurate and effective microwave brain imaging.

[0044] In another implementation of the present invention, after inputting the microwave data of the microwave data set in matrix form into the constructed adaptive phase compensation neural network, it also includes: transmitting the microwave data from the input layer of the adaptive phase compensation neural network to the hidden layer, and performing nonlinear mapping on it through radial basis function.

[0045] In another implementation of the present invention, the adaptive time delay and phase compensation processing of the microwave data to obtain an output signal includes: obtaining a feedforward controller based on the microwave data after Laplace transformation through an a priori given amplitude constant and phase constant when there is a time delay when microwaves pass through different tissues resulting in a phase error; using the feedforward controller as a compensation controller, combining the feedforward controller with a feedback controller to obtain the output signal.

[0046] For example, Figure 6As shown, taking a 16-antenna microwave detection device and 10 standard brain data as an example, each target to be tested will generate the aforementioned 8*16*15*5 data, which, when compared with the 10 standard brain data, will generate 10*8*16*15*5 data containing amplitude difference and phase difference, which can be divided into 8*10 inputs, i.e. x(1)~x(80), and each input neuron contains 16*15*5 data.

[0047] like Figure 5 As shown, each neuron is input into the hidden layer according to the time delay phase compensation rule, and the output signal can be obtained according to the compensated hidden layer weight.

[0048] In another implementation of the present invention, the microwave data after Laplace transformation is expressed as:

[0049] Where α is the amplitude constant; θ is the phase constant; x(s) is the microwave signal after Laplace transform; and x(t+θ) is the original microwave signal under the θ phase condition.

[0050] x(t) is the input microwave data, expressed as:

[0051] in, is the microwave signal after phase compensation; N is the number of received microwave signals.

[0052] In another implementation of the present invention, the feedforward controller is expressed as:

[0053] Wherein, x(s+θ) is a microwave signal with a phase error θ.

[0054] In another implementation of the present invention, the feedback controller is expressed as:

[0055] Wherein, τ is the time delay; β is the phase constant, which can be adjusted according to the actual situation. When β>1, it belongs to leading compensation, and when β<1, it belongs to lagging compensation.

[0056] In another implementation of the present invention, the output signal is represented by:

[0057] in, T is the transpose symbol of the matrix; is the Laplace transform of the microwave data received by each antenna; w i is the weight vector represented by each antenna; s iare the transformation vectors of the Laplace transform of the data; W is the weight, p is the control coefficient, and q is the weight update coefficient.

[0058] In another implementation of the present invention, Figure 7 As shown, Feko electromagnetic simulation software can be used for simulation, and FMCW waves of 2-5.5 GHz (the electric field strength threshold is 5 V / m, and the frequency is swept every 0.5 GHz) are used for simulation verification to obtain microwave scattering signals. After processing, the scattering signals are input as shown in Figure 6 In the neural network shown, the output signal is used to draw a regional heat map to obtain the imaging result. It can be seen that the microwave imaging result obtained by using this method is clearer than the imaging result not using this method.

[0059] It should be understood that during the research process, a microwave imaging device was used to obtain standard brain data of normal people, and a standard brain model for microwave brain imaging was constructed. Subsequently, data from patients with cerebral hemorrhage and cerebral infarction were obtained respectively and compared with the standard brain model. Based on the time delay of the received signal, an adaptive phase compensation neural network was used to re-superimpose and enhance the phase of the data after the time delay, and finally a brain image obtained by microwave scanning was formed.

[0060] For microwave brain imaging, each analyzed data in clinical applications is new data that is not in the database and has no prior knowledge of nuclear magnetic resonance. The present invention, by constructing a standard brain model and performing phase compensation, is able to generalize unseen data and produce more accurate imaging results. The adaptive phase compensation neural network has strong resistance to interference from small-scale head movement and electromagnetic noise during data acquisition, improving robustness. Based on the traditional microwave inverse scattering algorithm for signal phase processing, feedback compensation is performed on the measured phase of the target to be measured according to the standard brain model, thereby improving imaging accuracy.

[0061] Another aspect of the present invention provides a brain image generation system based on microwave data adaptive time delay and phase compensation, comprising: Data acquisition module: Configure antenna transceiver parameters, including the number of scanning points, frequency step, and starting frequency; collect frequency data based on the transceiver parameters to obtain a matrix data set; when the number of acquisition points of the matrix-form microwave data set is the same as the preset number of acquisition points, end the acquisition and save the matrix data set.

[0062] The data processing module inputs the microwave data of the microwave data set in the matrix form into the constructed adaptive phase compensation neural network; performs adaptive time delay phase compensation processing on the microwave data to obtain an output signal.

[0063] Imaging module: draws a regional thermal map according to the output signal to obtain microwave brain imaging results.

[0064] The brain image generation system based on adaptive delay and phase compensation of microwave data of the present invention realizes multi-frequency and multi-antenna sweep reception by controlling the signal transmission and reception format, uses the obtained microwave data as input, constructs an adaptive phase compensation neural network, transmits the data from the input layer to the hidden layer, performs nonlinear mapping on it through radial basis functions, compensates its antecedent according to the delay, and transmits the posterior term to the output layer for output, thereby realizing fast, accurate and effective microwave brain imaging.

[0065] In another aspect of the present invention, an electronic device includes a processor, a memory, a communication bus, and a communication interface.

[0066] in: The processor, memory and communication interface communicate with each other through a communication bus.

[0067] Communication interface, used to communicate with other electronic devices or servers.

[0068] The processor is used to execute the program, and specifically can execute the steps of any one of the brain image generation methods based on microwave data adaptive time delay phase compensation in the above embodiments.

[0069] Specifically, the program may include program codes including computer operation instructions.

[0070] The processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the smart device may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0071] Memory, used to store programs. Memory may include high-speed RAM (RAM) or non-volatile memory, such as at least one disk drive.

[0072] The program can be specifically configured to cause a processor to execute the steps of any of the brain image generation methods based on microwave data adaptive time delay and phase compensation described in the embodiments. The specific implementation of each step in the program can be found in the corresponding descriptions of the steps and units executed in any of the aforementioned brain image generation methods based on microwave data adaptive time delay and phase compensation, and will not be repeated here. Those skilled in the art will clearly understand that, for ease and brevity of description, the specific operating processes of the devices and modules described above can refer to the corresponding process descriptions in the aforementioned method embodiments.

[0073] The exemplary embodiments of the present application further provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the methods of the various embodiments of the present application.

[0074] The methods according to the embodiments of the present invention described above can be implemented in hardware, firmware, or as software or computer code that can be stored on a recording medium (such as a CD ROM, RAM, floppy disk, hard disk, or magneto-optical disk), or as computer code originally stored on a remote recording medium or non-transitory machine-readable medium downloaded over a network and then stored on a local recording medium. Thus, the methods described herein can be processed by such software stored on a recording medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware (such as an ASIC or FPGA). It will be understood that a computer, processor, microprocessor controller, or programmable hardware includes a storage component (e.g., RAM, ROM, flash memory, etc.) that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods described herein are implemented. Furthermore, when a general-purpose computer accesses the code for implementing the methods described herein, the execution of the code transforms the general-purpose computer into a dedicated computer for performing the methods described herein.

[0075] Thus far, specific embodiments of the present invention have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. Additionally, the processes depicted in the accompanying drawings do not necessarily require the specific order shown, or sequential order, to achieve the desired results.

[0076] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, back, etc.) are only used to explain the relative position relationship between the components in a certain specific order (as shown in the accompanying drawings). If the specific order changes, the directional indication will also change accordingly.

[0077] In the description of the present invention, the terms "first" and "second" are used solely to facilitate description of different components or names and should not be construed as indicating or implying a sequential relationship, relative importance, or implicitly specifying the quantity of the technical features being described. Therefore, features specified as "first" or "second" may explicitly or implicitly include at least one of such features.

[0078] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0079] It should be noted that although the specific embodiments of the present invention are described in detail in conjunction with the accompanying drawings, this should not be construed as limiting the scope of protection of the present invention. Within the scope described by the claims, various modifications and variations that can be made by those skilled in the art without creative effort still fall within the scope of protection of the present invention.

[0080] The examples of the embodiments of the present invention are intended to briefly illustrate the technical features of the embodiments of the present invention so that those skilled in the art can intuitively understand the technical features of the embodiments of the present invention, and are not intended to improperly limit the embodiments of the present invention.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A brain image generation method based on microwave data adaptive time delay phase compensation, characterized in that: include: Configure antenna transceiver parameters, including scan points, frequency step, and starting frequency; Collecting microwave data at the frequency points based on the transmitting and receiving parameters to obtain a microwave data set in a matrix form; When the number of acquisition points of the microwave data set in the matrix form is the same as the preset number of acquisition points, the acquisition is terminated and the matrix data set is saved; Inputting the microwave data of the microwave data set in matrix form into the constructed adaptive phase compensation neural network; performing adaptive time delay and phase compensation processing on the microwave data to obtain an output signal; A regional thermal map is drawn according to the output signal to generate a microwave brain image.

2. The method according to claim 1, characterized in that After inputting the microwave data of the microwave data set in matrix form into the constructed adaptive phase compensation neural network, the method further includes: The microwave data is transferred from the input layer of the adaptive phase compensation neural network to the hidden layer, and is nonlinearly mapped by a radial basis function.

3. The method according to claim 1, characterized in that The performing adaptive time delay and phase compensation processing on the microwave data to obtain an output signal includes: By using a priori given amplitude constant and phase constant, a feedforward controller is obtained based on the Laplace transformed microwave data when there is a phase error caused by the time delay when the microwave passes through different tissues. The feedforward controller is used as a compensation controller, and the feedforward controller is combined with a feedback controller to obtain an output signal.

4. The method according to claim 3, characterized in that The microwave data after Laplace transformation is expressed as: Where α is the amplitude constant; θ is the phase constant; x(s) is the microwave signal after Laplace transformation; x(t+θ) is the original microwave signal under the θ phase condition; x(t) is the input microwave data, expressed as: in, is the microwave signal after phase compensation; N is the number of received microwave signals.

5. The method according to claim 4, characterized in that The feedforward controller is expressed as: Wherein, x(s+θ) is a microwave signal with a phase error θ.

6. The method according to claim 4, characterized in that The feedback controller is expressed as: Wherein, τ is the time delay; β is the phase constant, which can be adjusted according to the actual situation. When β>1, it belongs to leading compensation, and when β<1, it belongs to lagging compensation.

7. The method according to claim 4, characterized in that The output signal is expressed as: in, T is the transpose symbol of the matrix; is the Laplace transform of the microwave data received by each antenna; w i is the weight vector represented by each antenna; s i are the transformation vectors of the Laplace transform of the data; W is the weight, p is the control coefficient, and q is the weight update coefficient.

8. A brain image generation system based on microwave data adaptive time delay phase compensation, characterized in that: include: Data acquisition module: configure antenna transceiver parameters, including scanning points, frequency step, and starting frequency; Collecting microwave data at the frequency points based on the transmitting and receiving parameters to obtain a microwave data set in a matrix form; When the number of acquisition points of the microwave data set in the matrix form is the same as the preset number of acquisition points, the acquisition is terminated and the matrix data set is saved; Data processing module: inputting the microwave data of the microwave data set in matrix form into the constructed adaptive phase compensation neural network; performing adaptive time delay and phase compensation processing on the microwave data to obtain an output signal; Imaging module: draws a regional thermal map according to the output signal to generate a microwave brain image.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of a brain image generation method based on microwave data adaptive time delay phase compensation as described in any one of claims 1 to 7 are implemented.

10. A computer storage medium, characterized in that The computer storage medium stores a computer program, which, when executed by a processor, implements the steps of a brain image generation method based on microwave data adaptive time delay phase compensation according to any one of claims 1 to 7.

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