Breast cancer detection sensor, detection device, and signal acquisition method

Abstract

The present invention discloses a breast cancer detection sensor, a detection device, and a signal acquisition method, which belong to the field of medical detection. The technical key points are: comprising: a conical chamber, a circumferential electrode, an array electrode, and a handle; wherein a layer of circumferential electrodes and two layers of array electrodes are arranged on the inner surface of the conical chamber; wherein the circumferential electrode is arranged at the opening end of the conical chamber, and the circumferential electrode is a grounding electrode. The present invention aims to provide a breast cancer detection sensor, a detection device, and a signal acquisition method to achieve accurate imaging of the relevant lesion area.

Description

Technical Field

[0001] The present invention belongs to the field of medical detection, and in particular relates to a breast cancer detection sensor, a detection device, and a signal acquisition method. Background Art

[0002] At present, breast cancer detection technologies mainly include mammography, CT, ultrasound and MRI. However, these detection methods have problems such as complex equipment, high radiation, high price and false positives, which makes breast cancer detection extremely difficult.

[0003] As a new detection technology, electrical impedance technology has been applied to the field of tumors.

[0004] For example:

[0005] Reference 1: Professor Li Yuhang from Hangzhou Dianzi University proposed a bladder filling degree detection method based on electrical impedance detection in CN114176557A.

[0006] Reference 2: Professor Chen Xiaoyan from Tianjin University of Science and Technology proposed a pulmonary electrical impedance imaging method based on VDD-Net in CN113902825A.

[0007] Reference 3: Professor Sun Shijie from Beijing University of Aeronautics and Astronautics proposed a three-dimensional dual-modal electrical impedance imaging sensor and its manufacturing method in CN112179950B.

[0008] Based on the above research on the prior art, it is found that:

[0009] (1) Currently, there is no research on the simultaneous use of electrical impedance technology to achieve breast cancer imaging and type identification.

[0010] (2) Electrical Impedance Tomography (EIT): Electrical Impedance Tomography (EIT) can distinguish normal tissue from cancerous tissue by their different physiological structures and electrical characteristics, thereby achieving three-dimensional image reconstruction of the breast and cancerous areas.

[0011] (3) Bio-electrical Impedance Spectroscopy (BIS): Bio-electrical Impedance Spectroscopy (BIS) can use the electrical impedance characteristics of biological tissues to extract relevant pathological information and use machine learning algorithms to process data to identify the type of breast cancer. Summary of the invention

[0012] The purpose of the present invention is to solve the problems existing in the above-mentioned prior art and to provide a breast cancer detection sensor, a detection device and a signal acquisition method.

[0013] The present invention is achieved through the following technical solutions:

[0014] A breast cancer detection sensor is a conical sensor, comprising: a conical chamber, a circumferential electrode, an array electrode, and a handle;

[0015] Wherein, a layer of circumferential electrodes and a multi-layer array electrode are arranged on the inner surface of the conical chamber;

[0016] Wherein, the circumferential electrode is arranged at the opening end of the conical chamber, and the circumferential electrode is a grounding electrode.

[0017] Furthermore, when the height of the conical sensor is X mm, the number of array electrode layers is selected as: [x / 20]+1.

[0018] Furthermore, the direction from the open end to the closed end of the conical chamber is called: the first layer of array electrodes, the second layer of array electrodes..., the Yth layer of array electrodes; the heights between the array electrodes are the same: the number of electrodes for any wth layer of array electrodes is 16w.

[0019] A detection device, comprising the aforementioned sensor; further comprising: an electrical impedance detection device; the cone sensor and the electrical impedance detection device are connected via a signal line;

[0020] The electrical impedance detection equipment includes: a signal generation and acquisition module, a gate switch control module, and a storage module;

[0021] The signal generation and acquisition module is used to generate a current signal with a constant amplitude for excitation and simultaneously acquire a response voltage signal and an electrical impedance signal of the tissue;

[0022] The gate switch control module is used to control the signal transmission between the signal generation and acquisition module and the cone sensor;

[0023] The storage module is used to store the data collected by the signal generation and collection module, that is, to store the voltage data at two different frequencies collected by the cone sensor and the collected multi-frequency electrical impedance data.

[0024] Furthermore, the voltage signal is used for EIT imaging, and the electrical impedance signal is used for BIS classification.

[0025] Further, the electrical impedance detection device also includes: an EIT data processing module;

[0026] The EIT data processing module is used to normalize ΔV and the sensitivity matrix S to obtain ΔVnorm and S norm ;

[0027] The solution is:

[0028] ΔV is the boundary voltage difference obtained by performing the difference processing on the voltage values ​​of two different frequencies:

[0029] ΔV=V2-V1

[0030] ΔV norm =ΔV / norm(ΔV)

[0031] S norm =S / norm(S);

[0032] Where V2 and V1 represent the excitation frequency f T1 and f T2 is the boundary voltage signal obtained when , norm(ΔV) and norm(S) are the norms of the boundary voltage ΔV and the sensitivity matrix S respectively.

[0033] Furthermore, the electrical impedance detection device further includes: an EIT imaging module; the EIT imaging module is used to draw an EIT image.

[0034] Further, the electrical impedance detection device also includes: an electrical impedance calculation module, a BIS classification module;

[0035] The electrical impedance calculation module is used to read the electrical impedance data stored in the storage module and calculate the relaxation frequency;

[0036] The BIS classification module gives a relaxation frequency threshold.

[0037] A signal acquisition method comprises the following steps:

[0038] S100, cone-shaped sensor in contact with the skin;

[0039] S200, the signal generation and acquisition module relies on the gate switch control module to select the array electrode, so that the current flows into the 32 electrodes in sequence and flows out of the circumferential electrode. Each time the excitation is performed, the voltage of the other 31 electrodes on the circumferential electrode is measured. The excitation and acquisition are performed twice, and the signal frequencies of the two excitations are f T1 、f T2 ;

[0040] S300, using finite element simulation method to calculate the field at the excitation frequency f T1 The sensitivity matrix S at ;

[0041] S400, the storage module sets the excitation frequency to f T1 、f T2The boundary voltage obtained when S300 is sent to the data processing module, which calculates the boundary voltage difference ΔV and normalizes ΔV and the sensitivity matrix S calculated by S300 to ΔV. norm and S norm .

[0042] Furthermore, it also includes:

[0043] S500, EIT imaging module uses a hybrid regularization algorithm to calculate the relative conductivity distribution in the field and normalize it to σ norm , finally according to σ norm Plot the 3D conductivity distribution.

[0044] The advantages of the technical solution of the present invention are mainly reflected in:

[0045] First, the first invention point of this application lies in the "conical sensor", one of the core points of which is that "a layer of circumferential electrodes and two layers of array electrodes are arranged on the inner surface of the conical chamber". The research on array electrodes on the conical sensor was studied for the first time in this application.

[0046] Based on computer simulation research, the following design is proposed:

[0047] 1.1 When the height of the conical sensor 100 is x mm, its effective measurement height is x-5 mm;

[0048] 1.2 When the height of the conical sensor 100 is x mm, the number of array electrode layers is selected as: [x / 20]+1.

[0049] 1.3 The direction from the open end to the closed end of the conical chamber 101 is called: the first layer array electrode, the second layer array electrode..., the Yth layer array electrode; the heights of the array electrodes are the same: the number of electrodes for any wth layer array electrode is 16w.

[0050] This is the first time that the above rules have been discovered.

[0051] Second, the second invention point of the present application lies in the design of the "impedance detection device", which corresponds to the three modules including "signal generation and acquisition module, selection switch control module, and storage module". Its core design concept is to control the voltage value and impedance value required for measurement based on the selection switch control module.

[0052] Third, the third invention of this application lies in the design of the "electrical impedance detection device", which corresponds to the module containing the "EIT data processing module". Its core design concept is to calculate the conductivity and prepare for EIT imaging. The corresponding "signal acquisition method" (the processing method of the EIT data processing module) does not involve the diagnosis method of the disease (this method can only obtain the intermediate information ΔV norm , σ norm ; and this intermediate information cannot directly lead to a diagnostic result).

[0053] Fourth, the fourth invention point of this application is the design of "electrical impedance detection equipment", which corresponds to the three modules of "EIT imaging module, electrical impedance calculation module, BIS classification module", and its core design concept is to display the distribution of conductivity and electrical impedance, so as to obtain the distribution of lesion areas and lesion types in subsequent analysis. The protection type corresponding to this invention point is product, not a method for diagnosing diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The present invention will be further described in detail below in conjunction with the embodiments in the accompanying drawings, but this does not constitute any limitation to the present invention.

[0055] Figure 1 It is a structural diagram of the detection system of the present application.

[0056] Figure 2 It is a schematic diagram of the design of the breast cancer detection sensor of the present application.

[0057] Figure 3 It is the influence of the number of array electrode layers of the conical sensor on the imaging quality when the diameter is 40mm.

[0058] Figure 4a This is the imaging result when the target is at a height of 10 mm (four-layer electrode).

[0059] Figure 4b This is the imaging result when the target is at a height of 15 mm (four-layer electrode).

[0060] Figure 4c This is the imaging result when the target is at a height of 20 mm (four-layer electrode).

[0061] Figure 4d This is the imaging result when the target is at a height of 25 mm (four-layer electrode).

[0062] Figure 4e This is the imaging result when the target is at a height of 30 mm (four-layer electrode).

[0063] Figure 4f This is the imaging result when the target is at a height of 35 mm (four-layer electrode).

[0064] Figure 5 It is the influence of the number of array electrode layers of the conical sensor on the imaging quality when the diameter is 65mm.

[0065] Figure 6 It is an application diagram of the detection system of the present application.

[0066] Figure 7 It is a design drawing of an electrical impedance testing device.

[0067] The following are the descriptions of the reference numerals:

[0068] Conical sensor 100, conical chamber 101, circumferential electrode 102, array electrode 103, handle 104;

[0069] Electrical impedance detection device 200 , signal generation and acquisition module 201 , selection switch control module 202 , storage module 203 , EIT data processing module 204 , EIT imaging module 205 , electrical impedance calculation module 206 , BIS classification module 207 . DETAILED DESCRIPTION

[0070] The purpose, advantages and features of the present invention will be explained by the non-limiting description of the following preferred embodiments. These embodiments are only typical examples of the application of the technical solution of the present invention, and any technical solution formed by equivalent replacement or equivalent transformation falls within the scope of protection claimed by the present invention.

[0071] Example 1: A breast cancer detection sensor

[0072] Combined with Figure 1-2 As shown, a breast cancer detection sensor comprises: a conical sensor 100; wherein the conical sensor is used to contact a surface to be detected.

[0073] The conical sensor 100 includes: a conical chamber 101 , a circumferential electrode 102 , an array electrode 103 , and a handle 104 ; a plurality of circumferential electrodes 102 and array electrodes 103 are evenly arranged on the inner surface of the conical chamber 101 .

[0074] More specifically, a layer of circumferential electrodes is disposed on the inner surface of the conical chamber 101 , and a layer of array electrodes is disposed at the opening end of the conical chamber 101 ; the circumferential electrodes are ground electrodes.

[0075] Simulation test Figure 3 to Figure 5As shown in the figure, the image correlation coefficient ICC is a common indicator used to evaluate the quality of EIT imaging (to illustrate the influence of different numbers of array electrode layers on imaging quality). The calculation result of IC is between -1 and 1, and its value indicates the correlation between the real conductivity distribution and the calculated conductivity distribution. The larger the absolute value of IC, the greater the correlation between the two, which means the higher the imaging quality. Its calculation expression is as follows:

[0076]

[0077] Where η is the true conductivity distribution vector, σ is the conductivity distribution vector calculated in the inverse problem, and are the average values ​​of η and σ respectively.

[0078] based on Figure 3 , Figure 4a to Figure 4f , Figure 5 , the following basic rules were discovered:

[0079] First, the higher the number of array electrode layers, the better the quality of breast cancer imaging. However, as the number of array layers continues to increase, the imaging quality is not significantly improved.

[0080] Second, H represents the distance between the end of the cone sensor 100 and the target object. Figure 3 It can be seen that when the conical sensor 100 is 40 mm, its effective measurement height is 10 to 35 mm.

[0081] And from Figure 5 It can be seen that when the conical sensor 100 is 65 mm, its effective measurement height is 10 to 60 mm.

[0082] In fact, the inventors have also done other numerical simulations and proposed the following design:

[0083] When the height of the conical sensor 100 is x mm, its effective measurement height is x-5 mm; the number of array electrode layers is selected as: [x / 20]+1.

[0084] The direction from the open end to the closed end of the conical chamber 101 is called: the first layer array electrode, the second layer array electrode, ..., the Yth layer array electrode; the heights of the array electrodes are the same;

[0085] The number of electrodes in the Y-th layer array electrode is 16Y.

[0086] In addition, the apex of the conical chamber is rounded to ensure full contact with the breast.

[0087] Embodiment 2: A detection device

[0088] The detection device includes the sensor of embodiment 1, and further includes: an electrical impedance detection device 200. The cone sensor and the electrical impedance detection device are connected via a signal line; the electrical impedance detection device outputs the excitation signal required for EIT imaging and BIS classification and collects and processes the electrical signal obtained by the measurement;

[0089] like Figure 7 As shown, the electrical impedance detection device 200 includes: a signal generation and acquisition module 201, a gate switch control module 202, a storage module 203, an EIT data processing module 204, an EIT imaging module 205, an electrical impedance calculation module 206, and a BIS classification module 207.

[0090] 1) The signal generation and acquisition module 201 is used to generate a current signal with a constant amplitude to stimulate and simultaneously acquire the response voltage signal and electrical impedance signal of the tissue, wherein the voltage signal is used for EIT imaging and the electrical impedance signal is used for BIS classification;

[0091] 2) The gate switch control module 202 is used to control the signal transmission of the signal generation and acquisition module 201 and the cone sensor 100;

[0092] 3) The storage module 203 is used to store the data of the signal generation and acquisition module 201, that is, to store the two different frequencies (f T1 , f T2 ) voltage data and multi-frequency electrical impedance data collected during BIS classification;

[0093] 4) The EIT data processing module 204 is used to perform difference processing on the voltage values ​​of two different frequencies to obtain the boundary voltage difference ΔV, and normalize ΔV and the sensitivity matrix S obtained in advance by finite element simulation to obtain ΔV norm and S norm ,in:

[0094] ΔV=V2-V1

[0095]

[0096] ΔV norm =ΔV / norm(ΔV)

[0097] S norm =S / norm(S);

[0098] Where V2 and V1 represent the excitation frequency f T1 and f T2 The boundary voltage signal obtained at s ijis an element in the sensitivity matrix S, norm(ΔV) and norm(S) are the norms of the boundary voltage ΔV and the sensitivity matrix S respectively.

[0099] 5) The EIT imaging module 205 is used to draw an EIT image, including the following steps:

[0100] Step 1, calculate the relative conductivity σ of each pixel point to generate the EIT image:

[0101] σ=(S T S+μI+ηdiag(S T S)) -1 S T ΔV

[0102] Where: σ is the relative conductivity distribution, S is the sensitivity matrix, S T is the transposed matrix of S, ΔV is the boundary voltage difference, I is the identity matrix, μ and η are regularization coefficients, diag(S T S) is S T The diagonal matrix of S;

[0103] Step 2, normalize the relative conductivity value obtained in step 1 to generate a binary image of EIT:

[0104] σ norm =(σ-min(σ)) / (max(σ)-min(σ))

[0105] In the formula, σ norm is the result after the relative conductivity value is normalized, max(σ) and min(σ) represent the maximum and minimum values ​​in the relative conductivity matrix σ respectively;

[0106] Step 3: Based on the binary image obtained in Step 2, the coordinates of each node in the lesion area (x i ,y i ,z i ) and the conductivity value σ corresponding to the node coordinates i , then the center coordinates (X j ,Y j ,Z j )for:

[0107]

[0108] Step 4: According to the center coordinates of the jth lesion area (X j ,Y j ,Z j) and the Euclidean distance between each electrode, and determining the two electrodes with the closest Euclidean distance as the impedance spectrum excitation-measurement electrodes of the j-th cancerous area;

[0109] Step 5, the host computer controls the selection switch control module 202 to switch the acquisition channel, collect the multi-frequency electrical impedance data and save it to the storage module. The multi-frequency electrical impedance data is a frequency-impedance amplitude-phase matrix:

[0110]

[0111] Among them, Z i For and f i The corresponding impedance amplitude is, For and f i The corresponding phase angle;

[0112] 6) The electrical impedance calculation module 206 is used to read the multi-frequency electrical impedance data collected during the BIS classification stored in the storage module, and calculate the relaxation frequency required in the BIS classification module, which can be divided into the following steps:

[0113] Step 1, calculate the frequency-real part of the electrical impedance value-imaginary part matrix corresponding to the lesion area:

[0114]

[0115] Where:

[0116] With frequency f i The corresponding real part of the electrical impedance

[0117] With frequency f i The corresponding imaginary part of the electrical impedance

[0118] Step 2: Calculate the relaxation frequency f of the impedance data relax , the relaxation frequency is the frequency corresponding to when the imaginary part of the electrical impedance value reaches a maximum value.

[0119] 7) The BIS classification module 207 obtains the relaxation frequency obtained by the electrical impedance calculation module and obtains the electrical characteristic division threshold f of different cancerous areas through training and testing the machine learning model thresh1 , f thresh2 , the relaxation frequency f of any j-th cancerous region relax ,

[0120] When f relax <f thresh1 When it is hormone receptor-positive breast cancer;

[0121] When f thresh1 <f relax <fthresh2 When it is hormone receptor HER2-positive breast cancer;

[0122] When f relax >f thresh2 It is hormone receptor triple-negative breast cancer.

[0123] Embodiment 3: A signal acquisition method

[0124] Place the cone-shaped sensor over the patient's breast and apply gentle pressure to ensure that the sensor is in close contact with the breast.

[0125] A detection method of a detection system for breast cancer detection, corresponding to an operation method of a software system, comprises the following steps:

[0126] S100, place the cone-shaped sensor cover on the patient's breast and press gently to ensure that the sensor is in close contact with the breast;

[0127] S200, the signal generation and acquisition module 201 selects the array electrodes by means of the selection switch control module 202, so that the current flows into the 64 electrodes in sequence and flows out of the circumferential electrodes. During each excitation, the voltage of the other 63 electrodes to the circumferential electrodes is measured. The breast is excited and collected twice, and the signal frequencies of the two excitations are f and f respectively. T1 、f T2 ;

[0128] S300, using finite element simulation method to calculate the field at the excitation frequency f T1 The sensitivity matrix S at ;

[0129] S400, the storage module 203 sets the excitation frequencies to f T1 、f T2 The boundary voltage obtained when S300 is sent to the data processing module, which calculates the boundary voltage difference ΔV and normalizes ΔV and the sensitivity matrix S calculated by S300 to ΔV. norm and S norm ;

[0130] S500, EIT imaging module uses a hybrid regularization algorithm to calculate the relative conductivity distribution in the field and normalize it to σ norm , finally according to σ norm Draw 3D conductivity distribution images;

[0131] S600, searching for cancerous tissue areas through a 3D conductivity distribution image generated by an EIT imaging module;

[0132] If there is a cancerous area, execute S700;

[0133] If no cancerous areas exist, the procedure is exited;

[0134] S700, the storage module sends the collected multi-frequency electrical impedance data to the BIS classification module, and the BIS classification module classifies the multi-frequency electrical impedance data through a machine learning algorithm to achieve identification of breast cancer types;

[0135] S800, exit the program.

[0136] The above embodiments are preferred implementation modes of the present invention and are only used to facilitate the description of the present invention. They are not intended to limit the present invention in any form. Any person with ordinary knowledge in the relevant technical field, if they do not depart from the scope of the technical features of the present invention, can make equivalent embodiments by partial changes or modifications to the technical contents disclosed in the present invention, and they still fall within the scope of the technical features of the present invention without departing from the technical features of the present invention.

Claims

1. A detection device, characterized in that: include: Breast cancer detection sensors and electrical impedance detection equipment; The breast cancer detection sensor is a conical sensor, comprising: a conical chamber, a circumferential electrode, an array electrode, and a handle; wherein a layer of circumferential electrode and array electrode is arranged on the inner surface of the conical chamber; the circumferential electrode is a layer; when the height of the conical sensor is xmm, the number of array electrode layers is selected as: [x / 20]+1; wherein the circumferential electrode is arranged at the open end of the conical chamber, and the circumferential electrode is a ground electrode; wherein the direction from the open end to the closed end of the conical chamber is called: the first layer array electrode, the second layer array electrode..., the Yth layer array electrode; the heights of the array electrodes are the same: The cone sensor is connected to the electrical impedance detection device via a signal line; The electrical impedance detection equipment includes: a signal generation and acquisition module, a gate switch control module, a storage module, an EIT data processing module, an EIT imaging module, an electrical impedance calculation module, and a BIS classification module; Wherein, the signal generation and acquisition module is used to generate a current signal with a constant amplitude to excite and simultaneously acquire a response voltage signal and an electrical impedance signal of the tissue, wherein the voltage signal is used for EIT imaging and the electrical impedance signal is used for BIS classification; Wherein, the gate switch control module is used to control the signal transmission between the signal generation and acquisition module and the cone sensor; Wherein, the storage module is used to store the data collected by the signal generation and acquisition module, that is, to store the voltage data at two different frequencies collected by the cone sensor and the collected multi-frequency electrical impedance data; The EIT data processing module is used to normalize ΔV and the sensitivity matrix S to obtain the parameter ΔV norm and S norm ; The solution method is: ΔV is the boundary voltage difference obtained by performing difference processing on the voltage values ​​of two different frequencies: ΔV=V2-V1,ΔV norm =ΔV / norm(ΔV),S norm =S / norm(S); Where V2 and V1 represent the excitation frequency f T1 and f T2 The boundary voltage signal obtained when , norm(ΔV) and norm(S) are the norms of the boundary voltage ΔV and the sensitivity matrix S respectively; The EIT imaging module draws the EIT image including the following steps: Step 1, calculate the relative conductivity σ of each pixel point to generate the EIT image: σ=(S T S+μI+ηdiag(S T S)) -1 S T ΔV Where: σ is the relative conductivity distribution, S is the sensitivity matrix, S T is the transposed matrix of S, ΔV is the boundary voltage difference, I is the identity matrix, μ and η are regularization coefficients, diag(S T S) is S T The diagonal matrix of S; Step 2, normalize the relative conductivity value obtained in step 1 to generate a binary image of EIT: s norm =(σ-min(σ)) / (max(σ)-min(σ)) In the formula, σ norm is the result after the relative conductivity value is normalized, max(σ) and min(σ) represent the maximum and minimum values ​​in the relative conductivity matrix σ respectively; Step 3: Based on the binary image obtained in Step 2, the coordinates of each node in the lesion area (x i ,y i ,z i ) and the conductivity value σ corresponding to the node coordinates i , then the center coordinates (X j ,Y j ,Z j ); Step 4: According to the center coordinates of the jth lesion area (X j ,Y j ,Z j ) and the Euclidean distance between each electrode, and determining the two electrodes with the closest Euclidean distance as the impedance spectrum excitation-measurement electrodes of the j-th cancerous area; Step 5, switch the acquisition channel through the host computer control gate switch control module, collect multi-frequency electrical impedance data and save it to the storage module. The multi-frequency electrical impedance data is a frequency-impedance amplitude-phase matrix: In the formula, Z i is the frequency f i The corresponding impedance amplitude is, is the frequency f i The corresponding phase angle; n represents the total number of frequencies; The electrical impedance calculation module is used to read the multi-frequency electrical impedance data collected during the BIS classification stored in the storage module, and calculate the relaxation frequency required in the BIS classification module, which is divided into the following steps: Step 1, calculate the frequency-real part of the electrical impedance value-imaginary part matrix corresponding to the lesion area: Where: and frequency f i The corresponding real part of the electrical impedance With frequency f i The corresponding imaginary part of the electrical impedance Step 2: Calculate the relaxation frequency f of the impedance data relax , the relaxation frequency is the frequency corresponding to when the imaginary part of the electrical impedance value reaches a maximum value; Wherein, the BIS classification module provides a relaxation frequency threshold.

2. A signal acquisition method, characterized in that: The detection device as claimed in claim 1 is used to collect signals, comprising the following steps: S100, cone-shaped sensor in contact with the skin; S200, the signal generation and acquisition module selects the array electrodes by means of the selection switch control module, so that the current flows into the m array electrodes in sequence and flows out of the circumferential electrodes. Each time the excitation is performed, the voltage of the other m-1 array electrodes to the circumferential electrodes is measured. The excitation and acquisition are performed twice, and the signal frequencies of the two excitations are f T1 、f T2 ; S300, using finite element simulation method to calculate the field at the excitation frequency f T1 The sensitivity matrix S at ; S400, the storage module sets the excitation frequency to f T1 、f T2 The boundary voltage obtained when S300 is sent to the data processing module, which calculates the boundary voltage difference ΔV and normalizes ΔV and the sensitivity matrix S calculated by S300 to ΔV. norm and S norm ; S500, EIT imaging module uses a hybrid regularization algorithm to calculate the relative conductivity distribution in the field and normalize it to σ norm , finally according to σ norm Plot the 3D conductivity distribution.

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