Human tissue dielectric property measurement data processing method, system, equipment and medium

Abstract

The present invention relates to the technical field of measuring dielectric properties of biological tissues, and in particular to a method, system, device and medium for processing data of dielectric property measurements of human tissues, including: acquiring dielectric property data, determining the data type of the dielectric property data; when detecting that the dielectric property data is of a first data type, preprocessing the dielectric property data to obtain first dielectric property data, and obtaining target data based on the first dielectric property data. The present invention obtains dielectric property feature information over the entire frequency band through data fitting, and then interpolates the fitting result to achieve frequency conversion of measurement data of different frequencies, solving the problem that different measurement data cannot be compared due to inconsistent frequencies of dielectric property measurements of human tissues. The method provided by the present invention is simple, can improve the efficiency of frequency conversion, and reduce costs at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of measuring dielectric properties of biological tissues, and in particular to a method, system, equipment and medium for processing data of measuring dielectric properties of human tissues. Background Art

[0002] Dielectric properties include conductivity and relative dielectric constant, which are inherent physical properties of matter. In human tissue, the value of dielectric properties is closely related to factors such as cell water content, cell membrane permeability, cell volume fraction, ion concentration in cell fluid, and tissue microenvironment. When the tissue is diseased, the value of the electrical properties will also change. Therefore, the dielectric property data reflects the physiological or pathological condition of the tissue to a certain extent. Obtaining the dielectric properties of human tissue can provide diagnostic information for clinicians. It is precisely because the dielectric properties of human tissue have attractive clinical application prospects that many scholars have explored and measured the dielectric properties of tissue for a long time. In the 1990s, Gabriel et al. systematically summarized the previous research and created a database of dielectric properties of healthy human tissue, which became one of the most important achievements in the field of medical physics.

[0003] As the research work on the measurement of dielectric properties of healthy tissues has gradually improved, researchers have shifted their focus to the measurement of diseased tissues, and have successively reported the measurement of dielectric properties of some common tumor types, further broadening the clinical application of dielectric properties of human tissues. In recent years, some scholars have proposed the idea of ​​distinguishing benign and malignant tissues based on dielectric property measurements during surgical tumor resection. That is, by measuring the dielectric properties of the tissue to be identified during surgery, and comparing the intraoperative measurement values ​​with the reported dielectric property measurement values ​​in the literature, and using the literature measurement values ​​as reference data, the classification and identification of whether the tissue to be identified is normal, benign, or malignant can be achieved. Among them, the intraoperative measurement values ​​of the dielectric properties of the tissues are compared with the literature measurement values. The comparison of the measured data in the literature is an important part of the identification process. However, since the dielectric properties are frequency-dependent, that is, the values ​​of the dielectric properties change with the measurement frequency, this requires that the comparison of the measured values ​​must be implemented at the same frequency point, and the measurement frequency of the dielectric properties is related to the measurement equipment and measurement settings. Although each measurement uses the same equipment and measurement settings as the literature measurement values, it can ensure that the measured values ​​are at the same frequency point as the literature measurement values. However, since the measurement equipment and settings used for different literature measurement values ​​are not the same, when implementing measurement identification for different organizations, it is necessary to purchase different equipment for measurement, which greatly increases the identification cost and causes waste of resources, and is not feasible.

[0004] In addition, magnetic resonance electrical imaging is a new technology developed in recent years. This technology can non-invasively obtain information on the dielectric properties of human tissue at the magnetic resonance Larmor frequency, where the Larmor frequency is the resonant operating frequency of magnetic resonance. For example, the magnetic resonance Larmor frequency of 3T field strength is 128MHz. In magnetic resonance electrical imaging technology, verification of dielectric property imaging results is an important method for evaluating imaging reconstruction algorithms. Usually, the dielectric property measurement values ​​of in vitro tissues with higher accuracy, such as the open-end coaxial method, are used as reference standards to calculate the errors of dielectric property imaging results; however, the measurement frequency of in vitro tissue dielectric properties is usually not precisely matched with the Larmor frequency, resulting in the inability to make a direct comparison.

[0005] In summary, since the values ​​of the dielectric properties of human tissue depend on the measurement frequency, when the dielectric property data is inconsistent with the reference data to be compared, comparative analysis cannot be performed. It is urgent to provide a method that can transform the dielectric property data at the measurement frequency to the target frequency of the data to be compared. Summary of the invention

[0006] The present invention provides a method, system, device and medium for processing data of dielectric property measurement of human tissue, and solves the technical problem that the inconsistency of existing human tissue dielectric property measurement frequencies leads to the inability to compare different measurement data, resulting in high identification cost and poor practicality.

[0007] In order to solve the above technical problems, the present invention provides a method, system, device and medium for processing data of dielectric property measurement of human tissue.

[0008] In a first aspect, the present invention provides a method for processing data of dielectric property measurement of human tissue, the method comprising the following steps:

[0009] Acquire dielectric characteristic data, and determine the data type of the dielectric characteristic data;

[0010] When it is detected that the dielectric characteristic data is of the first data type, preprocessing the dielectric characteristic data to obtain first dielectric characteristic data, and obtaining target data according to the first dielectric characteristic data;

[0011] The step of obtaining target data according to the first dielectric characteristic data comprises:

[0012] Obtaining a complex dielectric constant according to the first dielectric characteristic data;

[0013] Fitting the complex dielectric constant using a first model to obtain first fitting data;

[0014] Performing frequency mapping on the first fitting data and a preset first target frequency point to obtain a target complex dielectric constant, and obtaining target data according to the target complex dielectric constant;

[0015] The first data type is dielectric characteristic data including both conductivity and relative permittivity, and the target data includes a first target conductivity and a first target relative permittivity.

[0016] In a further embodiment, the step of preprocessing the dielectric property data to obtain the first dielectric property data is specifically:

[0017] The conductivity and relative dielectric constant in the dielectric characteristic data are respectively smoothed and filtered by a Gaussian smoothing filter to obtain first dielectric characteristic data;

[0018] The first dielectric characteristic data includes the conductivity and relative dielectric constant after filtering.

[0019] In a further embodiment, the first model is specifically:

[0020]

[0021] In the formula, ε * is the complex dielectric constant, ε ∞ ' represents the relative dielectric constant when the dielectric characteristic data is the first data type and the frequency is infinite, represents the first DC conductivity, ε 0 represents the vacuum dielectric constant, f′ represents the first measurement frequency when the dielectric characteristic data is of the first data type, j represents the sign of the complex imaginary part, Δε n ′ represents the first relative dielectric constant increment corresponding to the nth dispersion, τ n ′ represents the first average relaxation time corresponding to the nth dispersion, α n ′ represents the first relaxation time distribution coefficient corresponding to the nth dispersion, and the value range of n is [1, 4];

[0022] The first fitting data includes a first DC conductivity, a relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, a first relative dielectric constant increment, a first average relaxation time, and a first relaxation time distribution coefficient.

[0023] In a further embodiment, the calculation formula of the frequency mapping is:

[0024]

[0025] In the formula, ε * (f 0 ) represents the target complex dielectric constant, ε ∞ ' represents the relative dielectric constant when the dielectric characteristic data is the first data type and the frequency is infinite, ε0 represents the vacuum dielectric constant, f 0 ' represents the first target frequency point, j represents the symbol of the complex imaginary part, ε ∞ ′、Δε n ′、τ n ′、α n ′ all belong to the first fitting data, and respectively represent the first DC conductivity obtained by fitting, the relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, the first relative dielectric constant increment corresponding to the n-th dispersion, the first average relaxation time corresponding to the n-th dispersion, and the first relaxation time distribution coefficient corresponding to the n-th dispersion, and the value range of n is [1, 4].

[0026] In a further embodiment, the calculation formula of the step of obtaining target data according to the target complex dielectric constant is specifically:

[0027] σ′(f 0 )=-2πf 0 ′ε 0 Im{ε * (f 0 )}

[0028] ε r ′(f 0 )=Re{ε * (f 0 )}

[0029] In the formula, σ′(f 0 ) represents the first target conductivity, f 0 ′ represents the first target frequency point, ε 0 represents the vacuum dielectric constant, ε * (f 0 ) represents the target complex dielectric constant, ε r ′(f 0 ) represents the first target relative permittivity.

[0030] In a further embodiment, the method further comprises:

[0031] When it is detected that the dielectric characteristic data is of the second data type, smoothing and filtering the dielectric characteristic data to obtain second dielectric characteristic data, and acquiring a second target conductivity according to the second dielectric characteristic data;

[0032] The step of acquiring a second target conductivity according to the second dielectric characteristic data comprises:

[0033] Based on the second dielectric characteristic data and the second measurement frequency, fitting is performed through a second model to obtain second fitting data;

[0034] Performing frequency mapping on the second fitting data and a preset second target frequency point to obtain a second target conductivity;

[0035] Wherein, the second data type is dielectric characteristic data containing only conductivity, and the second dielectric characteristic data contains only filtered conductivity data;

[0036] The calculation formula of the second model is:

[0037]

[0038] Wherein, σ″ represents the second dielectric characteristic data, f″ represents the second measurement frequency when the dielectric characteristic data is the second data type, ε 0 represents the vacuum dielectric constant, sinh and cosh are hyperbolic sine and hyperbolic cosine functions respectively, Δε n ″、τ n ″、α n ″ all belong to the second fitting data, respectively representing the second DC conductivity, the second relative permittivity increment corresponding to the n-th dispersion, the second average relaxation time corresponding to the n-th dispersion, and the second relaxation time distribution coefficient corresponding to the n-th dispersion, and the value range of n is [1, 4].

[0039] In a further embodiment, the method further comprises:

[0040] When it is detected that the dielectric characteristic data is of a third data type, smoothing and filtering the dielectric characteristic data to obtain third dielectric characteristic data, and obtaining a second target relative dielectric constant according to the third dielectric characteristic data;

[0041] The step of obtaining a second target relative dielectric constant according to the third dielectric characteristic data comprises:

[0042] Based on the third dielectric characteristic data and the third measurement frequency, a third model is used for fitting to obtain third fitting data;

[0043] Performing frequency mapping on the third fitting data and a preset third target frequency point to obtain a second target relative permittivity;

[0044] Wherein, the third data type is dielectric characteristic data containing only relative dielectric constant, and the third dielectric characteristic data contains only filtered relative dielectric constant data;

[0045] The calculation formula of the third model is:

[0046]

[0047] In the formula, εr ″ represents the third dielectric characteristic data, ε ∞ ″ represents the relative dielectric constant when the dielectric characteristic data is of the third data type and the frequency is infinite, f″′ represents the third measurement frequency when the dielectric characteristic data is of the third data type, wherein the third fitting data includes the third relative dielectric constant increment Δε corresponding to the nth dispersion n ″′, the third average relaxation time τ corresponding to the nth dispersion n ″′, the third relaxation time distribution coefficient α corresponding to the nth dispersion n ″′, the dielectric characteristic data is the third data type and the relative dielectric constant ε when the frequency is infinite ∞ ″, the value range of n is [1, 4].

[0048] In a second aspect, the present invention provides a human tissue dielectric property measurement data processing system, the system comprising:

[0049] A determination module, used to obtain dielectric characteristic data and determine the data type of the dielectric characteristic data;

[0050] A first processing module, configured to pre-process the dielectric characteristic data to obtain first dielectric characteristic data when detecting that the dielectric characteristic data is of a first data type;

[0051] a first analysis module, configured to obtain a complex dielectric constant according to the first dielectric characteristic data, and to fit the complex dielectric constant using a first model to obtain first fitting data; and to perform frequency mapping on the first fitting data and a preset first target frequency point to obtain a target complex dielectric constant, and to obtain target data according to the target complex dielectric constant;

[0052] A second processing module, configured to perform smoothing filtering on the dielectric characteristic data to obtain second dielectric characteristic data when detecting that the dielectric characteristic data is of a second data type;

[0053] A second analysis module is used to perform fitting through a second model based on the second dielectric characteristic data and the second measurement frequency to obtain second fitting data, and perform frequency mapping on the second fitting data and a preset second target frequency point to obtain a second target conductivity;

[0054] A third processing module, configured to perform smoothing filtering on the dielectric characteristic data to obtain third dielectric characteristic data when detecting that the dielectric characteristic data is of a third data type;

[0055] A third analysis module is used to perform fitting using a third model based on the third dielectric characteristic data and the third measurement frequency to obtain third fitting data, and to perform frequency mapping on the third fitting data and a preset third target frequency point to obtain a second target relative dielectric constant;

[0056] Among them, the first data type is dielectric property data including both conductivity and relative dielectric constant, the second data type is dielectric property data including only conductivity, the third data type is dielectric property data including only relative dielectric constant, and the target data includes a first target conductivity and a first target relative dielectric constant.

[0057] In a third aspect, the present invention further provides a computer device, comprising a processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory so that the computer device performs the steps of implementing the above method.

[0058] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0059] The present invention provides a method, system, device and medium for processing human tissue dielectric property measurement data. Through the method, a technical solution for frequency conversion of measurement data of different frequencies is realized. Compared with the prior art, the method can realize the target frequency conversion of dielectric property data containing only conductivity and relative dielectric constant by using an improved Cole-Cole model and frequency mapping. The method is simple and efficient. In addition, the present invention does not need to purchase the same equipment as the measurement data to be compared each time measurement is performed. The method provided by the present invention can be applied to any measurement equipment hardware, which greatly reduces costs and saves resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a schematic flow chart of a method for processing data of dielectric property measurement of human tissue provided by an embodiment of the present invention;

[0061] Figure 2 is a schematic diagram of a data curve represented by a first data type provided by an embodiment of the present invention;

[0062] Figure 3 is a schematic diagram of a process for obtaining target data provided by an embodiment of the present invention;

[0063] Figure 4 is a schematic diagram of a target data curve provided by an embodiment of the present invention;

[0064] Figure 5is a schematic diagram of a second target conductivity curve provided by an embodiment of the present invention;

[0065] Figure 6 is a schematic diagram of a second target relative dielectric constant curve provided by an embodiment of the present invention;

[0066] Figure 7 This is a block diagram of a data processing system for measuring dielectric properties of human tissue provided by an embodiment of the present invention;

[0067] Figure 8 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The following specifically illustrates the implementation mode of the present invention in conjunction with the accompanying drawings. The embodiments are provided for illustrative purposes only and cannot be understood as limiting the present invention. The accompanying drawings are provided for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0069] refer to Figure 1 , the embodiment of the present invention provides a method for processing data of dielectric property measurement of human tissue, such as Figure 1 As shown, the method includes:

[0070] S1. Acquire dielectric characteristic data and determine the data type of the dielectric characteristic data.

[0071] This embodiment determines the data type of the dielectric characteristic data based on the collected dielectric characteristic data. In this embodiment, the data type of the dielectric characteristic data includes a first data type, a second data type and a third data type, wherein the first data type is a dielectric characteristic data type that includes both conductivity and relative dielectric constant, the second data type is a dielectric characteristic data type that only includes conductivity, and the third data type is a dielectric characteristic data type that only includes relative dielectric constant.

[0072] Since the dielectric property data belonging to the first data type includes both conductivity and relative dielectric constant, and the dielectric property data belonging to the second data type or the third data type includes only one of the data, this embodiment classifies the dielectric property data belonging to the first data type as complete dielectric property data, and classifies the dielectric property data belonging to the second data type or the third data type as incomplete dielectric property data.

[0073] S2. When it is detected that the dielectric characteristic data is of the first data type, preprocess the dielectric characteristic data to obtain first dielectric characteristic data, and obtain target data according to the first dielectric characteristic data.

[0074] In this embodiment, dielectric property measurement data of healthy liver tissue of human body is collected to obtain dielectric property data to be processed, including both conductivity and relative dielectric constant, such as Figure 2 As shown, this embodiment collects dielectric property data within the measurement range of 10MHz to 1GHz, and collects data every 10MHz, with a total of 100 measurement frequency points. At the same time, in order to address the deficiencies of the prior art, this embodiment transforms the measurement frequency points to four first target frequency points, namely 16MHz, 64MHz, 128MHz, and 298MHz, that is, obtains the target dielectric property data at these four first target frequency points.

[0075] In one embodiment, based on the fact that the dielectric properties of biological tissues vary with frequency and present a smooth curve characteristic without mutation, this embodiment uses a Gaussian smoothing filter to smooth the conductivity and relative dielectric constant in the input dielectric property data to obtain first dielectric property data, wherein the first dielectric property data includes the filtered conductivity σ and relative dielectric constant ε r , this embodiment eliminates the interference of measurement noise through smoothing filtering, thereby providing high signal-to-noise ratio data for subsequent data fitting, wherein the formula of the high-pass smoothing filter is:

[0076]

[0077] In the formula, g(x) represents probability, d represents standard deviation, and in this embodiment, the standard deviation d is set to 1.

[0078] In this embodiment, the filtering of the high-pass smoothing filter is preferably set to 7, so that the filter matrix A can be obtained as [0.0044, 0.0540, 0.2420, 0.3991, 0.2420, 0.0540, 0.0044]. In this embodiment, the conductivity and the relative dielectric constant are respectively convolved by the filter matrix A to achieve smooth filtering, and the conductivity σ and the relative dielectric constant ε after filtering are obtained. r .

[0079] In one embodiment, Figure 3 As shown, the step of obtaining target data according to the first dielectric characteristic data includes:

[0080] S21. Obtain a complex dielectric constant according to the first dielectric characteristic data.

[0081] In this embodiment, the complex dielectric constant is calculated based on the conductivity and relative dielectric constant after smoothing and filtering. The specific calculation formula is:

[0082]

[0083] In the formula, ε *is the complex dielectric constant, ε r represents the relative dielectric constant after filtering, j represents the sign of the complex imaginary part, σ represents the conductivity after filtering, f′ represents the first measurement frequency when the dielectric characteristic data is the first data type, ε 0 represents the dielectric constant of vacuum.

[0084] S22. Fitting the complex dielectric constant using a first model to obtain first fitting data.

[0085] Since the complex dielectric constant of the biological tissue obtained in this embodiment satisfies the Cole-Cole model, this embodiment preferentially sets the first model to be the Cole-Cole model. This embodiment uses the Cole-Cole model to fit the complex dielectric constant to obtain first fitting data, wherein the Cole-Cole model is specifically:

[0086]

[0087] In the formula, ε * is the complex dielectric constant, ε ∞ ' represents the relative dielectric constant when the dielectric characteristic data is the first data type and the frequency is infinite, represents the first DC conductivity, ε 0 represents the vacuum dielectric constant, f′ represents the first measurement frequency when the dielectric characteristic data is of the first data type, j represents the sign of the complex imaginary part, Δε n ′ represents the first relative dielectric constant increment corresponding to the nth dispersion, τ n ′ represents the first average relaxation time corresponding to the nth dispersion, α n ′ represents the first relaxation time distribution coefficient corresponding to the nth dispersion, and the value range of n is [1, 4].

[0088] The first fitting data includes a first DC conductivity σ s1 , the dielectric characteristic data is the first data type and the relative dielectric constant ε when the frequency is infinite ∞ ', the first relative dielectric constant increment Δε n ′, the first average relaxation time τ n ′ and the first relaxation time distribution coefficient α n ′.

[0089] In this embodiment, ε ∞ ′、Δε n ′、τ n ′、α n ′ are all unknown parameters, which need to be determined through fitting. The data fitting is implemented by the steepest descent method iteration. The fitting results are:

[0090] ε ∞ ′=4,Δε 1 ′=39,τ 1 ′=8.84×10 -12 , α 1 ′=0.1,Δε 2 ′=6000,τ 2 ′=5.3×10 -7 , α 2 ′=0.2,Δε 3 ′=5×10 4 , τ 3 ′=22.736×10 -6 , α 3 ′=0.2,Δε 4 ′=3×10 7 , τ 4 ′=15.915×10 -3 , α 4 ′=0.05.

[0091] S23. Perform frequency mapping on the first fitting data and the preset first target frequency point to obtain a target complex dielectric constant.

[0092] In this embodiment, the first target frequency points include 16 MHz, 64 MHz, 128 MHz, and 298 MHz. In this embodiment, the above parameters to be determined are ε ∞ ′、Δε n ′、τ n ′、α n 'The fitting result obtained by fitting is substituted into the frequency mapping formula, and the first target frequency point is substituted into the frequency mapping formula to obtain the complex dielectric constant after frequency mapping, that is, the target complex dielectric constant.

[0093] The calculation formula of the frequency mapping is:

[0094]

[0095] In the formula, ε * (f 0 ) represents the target complex dielectric constant, ε ∞ ' represents the relative dielectric constant when the dielectric characteristic data is the first data type and the frequency is infinite, ε 0 represents the vacuum dielectric constant, f 0 ' represents the first target frequency point, j represents the symbol of the complex imaginary part, ε ∞ ′、Δε n ′、τ n ′、α n′ all belong to the first fitting data, and respectively represent the first DC conductivity obtained by fitting, the relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, the first relative dielectric constant increment corresponding to the n-th dispersion, the first average relaxation time corresponding to the n-th dispersion, and the first relaxation time distribution coefficient corresponding to the n-th dispersion, and the value range of n is [1, 4].

[0096] S24. Obtain a first target conductivity and a first target relative permittivity according to the target complex permittivity, and the calculation formula is as follows:

[0097] σ′(f 0 )=-2πf 0 ′ε 0 Im{ε * (f 0 )}

[0098] ε r ′(f 0 )=Re{ε * (f 0 )}

[0099] In the formula, σ′(f 0 ) represents the first target conductivity, f 0 ′ represents the first target frequency point, ε 0 represents the vacuum dielectric constant, ε * (f 0 ) represents the target complex dielectric constant, ε r ′(f 0 ) represents the first target relative permittivity.

[0100] In this embodiment, the first target conductivity σ′(f 0 ) and the first target relative permittivity ε r ′(f 0 ), at this time, the first target conductivity σ′(f 0 ) and the first target relative permittivity ε r ′(f 0 ) has been transformed to the first target frequency point, such as Figure 4 As shown, at the four first target frequency points 16MHz, 64MHz, 128MHz, and 298MHz, the first target conductivity σ′ (f 0 ) are 0.3502S / m, 0.4480S / m, 0.5109S / m, 0.6089S / m respectively, and the first target relative dielectric constant ε r ′(f 0 ) are 156.8837, 80.5595, 64.2507 and 53.5713 respectively.

[0101] This embodiment uses dielectric property data at frequency points within the measurement frequency range of 10 MHz to 1 GHz and at intervals of 10 MHz to obtain target dielectric property data at first target frequency points of 16 MHz, 64 MHz, 128 MHz, and 298 MHz, namely, first target conductivity and first target relative dielectric constant. It should be noted that the four first target frequency points of 16 MHz, 64 MHz, 128 MHz, and 298 MHz correspond to Larmor frequencies of four common field strength systems of 0.4 Tesla, 1.5 Tesla, 3 Tesla, and 7 Tesla, respectively. In magnetic resonance electrical imaging, dielectric property imaging results are usually evaluated based on dielectric property measurement values ​​of ex vivo tissues, and dielectric property measurement of ex vivo tissues may not include special frequency points of Larmor frequencies. Therefore, the method provided in this embodiment for complete dielectric property data can transform dielectric property measurement data with inconsistent frequencies to Larmor frequencies for magnetic resonance electrical imaging.

[0102] The method for processing human tissue dielectric property measurement data provided in this embodiment also includes:

[0103] S3. When it is detected that the dielectric characteristic data is of the second data type, preprocess the dielectric characteristic data to obtain second dielectric characteristic data, and obtain a second target conductivity according to the second dielectric characteristic data.

[0104] In this embodiment, the collected dielectric property data is the conductivity measurement data of healthy cerebrospinal fluid tissue of the human body. The second measurement frequency set in this embodiment is 10MHz~1GHz, the frequency interval is a frequency point on 20MHz, and the second target frequency point is a frequency point in the frequency range of 10MHz~1GHz, and the frequency interval is 2MHz.

[0105] In one embodiment, the step of preprocessing the dielectric characteristic data to obtain second dielectric characteristic data includes:

[0106] When it is detected that the dielectric characteristic data is of the second data type, the input conductivity measurement data is smoothed and filtered by a Gaussian smoothing filter to obtain the filtered conductivity. In this embodiment, the interference of measurement noise is eliminated by the Gaussian smoothing filter to provide high signal-to-noise ratio data for the subsequent data fitting step. In this embodiment, the conductivity is convolved by the above-mentioned filter matrix A to achieve smoothing filtering to obtain the second dielectric characteristic data. In this embodiment, the second dielectric characteristic data is the filtered conductivity.

[0107] In one embodiment, the step of obtaining the second target conductivity according to the second dielectric characteristic data comprises:

[0108] Based on the second dielectric characteristic data and the second measurement frequency, fitting is performed through a second model to obtain second fitting data;

[0109] Performing frequency mapping on the second fitting data and a preset second target frequency point to obtain a second target conductivity;

[0110] The second dielectric characteristic data is dielectric characteristic data containing only the conductivity after filtering.

[0111] It should be noted that, in this embodiment, since the input data only includes conductivity data, this embodiment cannot directly use the Cole-Cole model for fitting. This embodiment transforms the Cole-Cole model to obtain a model that only includes conductivity, that is, the second model. This embodiment uses the second model to fit the filtered conductivity.

[0112] In one embodiment, the second model is specifically:

[0113]

[0114] Wherein, σ″ represents the second dielectric characteristic data, f″ represents the second measurement frequency when the dielectric characteristic data is the second data type, ε 0 represents the vacuum dielectric constant, sinh and cosh are hyperbolic sine and hyperbolic cosine functions respectively, Δε n ″、τ n ″、α n ″ all belong to the second fitting data, respectively representing the second DC conductivity, the second relative permittivity increment corresponding to the n-th dispersion, the second average relaxation time corresponding to the n-th dispersion, and the second relaxation time distribution coefficient corresponding to the n-th dispersion, and the value range of n is [1, 4].

[0115] In one embodiment, the formula for frequency mapping the second fitting data and the preset second target frequency point is:

[0116]

[0117] In the formula, σ″(f 0 ) represents the second target conductivity, f 0 ″ indicates the second target frequency point.

[0118] In this embodiment, the second target conductivity is obtained by performing data fitting and frequency mapping on the dielectric characteristic data containing only the conductivity. Figure 5 As shown, the frequency of the second target conductivity has been extended to the second target frequency point.

[0119] The method for processing human tissue dielectric property measurement data provided in this embodiment also includes:

[0120] S4. When it is detected that the dielectric characteristic data is of the third data type, preprocess the dielectric characteristic data to obtain third dielectric characteristic data, and obtain a second target relative dielectric constant according to the third dielectric characteristic data.

[0121] In this embodiment, the collected dielectric property data is the relative dielectric constant measurement data of healthy cerebrospinal fluid tissue of the human body. The third measurement frequency set in this embodiment is 1MHz~100MHz, and the frequency interval is a frequency point on 2MHz. The second target frequency point is a frequency point in the frequency range of 100MHz~300MHz, and the frequency interval is 2MHz.

[0122] In one embodiment, the step of preprocessing the dielectric characteristic data to obtain third dielectric characteristic data includes:

[0123] Since the dielectric properties of biological tissues present a smooth curve feature without sudden changes as the frequency changes, when it is detected that the dielectric property data is the third data type, the present embodiment uses a Gaussian smoothing filter to smooth the input relative dielectric constant measurement data to obtain the third dielectric property data; the present embodiment eliminates the interference of the relative dielectric constant measurement data noise through smoothing filtering, and provides relative dielectric constant data with a high signal-to-noise ratio for subsequent fitting steps. At the same time, the present embodiment uses a filter matrix A to convolve the relative dielectric constant to obtain the filtered relative dielectric constant, thereby realizing smooth filtering of the relative dielectric constant. In the present embodiment, the third dielectric property data is the filtered relative dielectric constant.

[0124] In this embodiment, since the input data only includes relative dielectric constant data, this embodiment cannot directly use the Cole-Cole model for fitting. This embodiment transforms the Cole-Cole model to obtain a model that only includes the relative dielectric constant, that is, the third model. This embodiment uses the third model to fit the filtered relative dielectric constant.

[0125] In one embodiment, the step of obtaining a second target relative dielectric constant according to the third dielectric characteristic data comprises:

[0126] Based on the third dielectric characteristic data and the third measurement frequency, a third model is used for fitting to obtain third fitting data;

[0127] Performing frequency mapping on the third fitting data and a preset third target frequency point to obtain a second target relative permittivity;

[0128] Wherein, the third dielectric characteristic data is dielectric characteristic data including only relative dielectric constant;

[0129] In one embodiment, the third model is:

[0130]

[0131] In the formula, ε r ″ represents the third dielectric characteristic data, ε ∞ ″ represents the relative dielectric constant when the dielectric characteristic data is of the third data type and the frequency is infinite, f″′ represents the third measurement frequency when the dielectric characteristic data is of the third data type, wherein the third fitting data includes the third relative dielectric constant increment Δε corresponding to the nth dispersion n ″′, the third average relaxation time τ corresponding to the nth dispersion n ″′, the third relaxation time distribution coefficient α corresponding to the nth dispersion n ″′, the dielectric characteristic data is the third data type and the relative dielectric constant ε when the frequency is infinite ∞ ″, the value range of n is [1, 4].

[0132] In one embodiment, the formula for frequency mapping the third fitting data and the preset third target frequency point is:

[0133]

[0134] In the formula, ε r ″(f 0 ) represents the second target relative permittivity, f 0 ″′ represents the third target frequency point.

[0135] In this embodiment, the third target frequency point and the third fitting data ε obtained by fitting are ∞ ″、Δε n ″′、τ n ″′、α n Substituting ″′ into the above formula, we can get the relative dielectric constant after frequency expansion. At this time, Figure 6 As shown, the second target relative permittivity has been extended to the third target frequency point.

[0136] Among the above three data types, this embodiment obtains dielectric property data over the entire frequency band through fitting, and interpolates it through fitting, thereby realizing frequency transformation of measurement data of different frequencies. It should be noted that this embodiment can also expand the measured dielectric property data through interpolation or extrapolation methods.

[0137] A method for processing human tissue node characteristic measurement data provided by the present embodiment solves the problem that different measurement data cannot be compared due to inconsistent measurement frequencies of human tissue dielectric properties by transforming dielectric property data at the measurement frequency to a specified frequency. The method provided by the present embodiment performs different processing according to the type of dielectric property data to be processed, so that different dielectric property data can be better processed, and can be applied to the comparison between different measurement data in related applications, such as identification and classification in benign and malignant tissue identification applications based on dielectric properties, and evaluation of imaging result accuracy in magnetic resonance electrical property imaging applications. In addition, the present embodiment is applicable to any measurement equipment hardware, and there is no need to use the same equipment as the measurement data to be compared in each measurement, thereby avoiding waste of resources, saving hardware costs, and having high practicality.

[0138] It should be noted that the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0139] In one embodiment, Figure 7 As shown, a human tissue dielectric property measurement data processing system is provided, the system comprising:

[0140] A determination module 101 is used to obtain dielectric property data and determine the data type of the dielectric property data;

[0141] A first processing module 201 is used to pre-process the dielectric characteristic data to obtain first dielectric characteristic data when it is detected that the dielectric characteristic data is of a first data type;

[0142] A first analysis module 202 is used to obtain a complex dielectric constant according to the first dielectric characteristic data, and fit the complex dielectric constant using a Cole-Cole model to obtain first fitting data, perform frequency mapping on the first fitting data and a preset first target frequency point to obtain a target complex dielectric constant, and obtain a first target conductivity and a first target relative dielectric constant according to the target complex dielectric constant;

[0143] A second processing module 301 is used to perform smoothing filtering on the dielectric characteristic data to obtain second dielectric characteristic data when it is detected that the dielectric characteristic data is of a second data type;

[0144] The second analysis module 302 is used to perform fitting through a second model based on the second dielectric characteristic data and the second measurement frequency to obtain second fitting data, and perform frequency mapping on the second fitting data and a preset second target frequency point to obtain a second target conductivity;

[0145] A third processing module 401 is used to perform smoothing filtering on the dielectric characteristic data to obtain third dielectric characteristic data when it is detected that the dielectric characteristic data is a third data type;

[0146] The third analysis module 402 is used to perform fitting using a third model based on the third dielectric characteristic data and the third measurement frequency to obtain third fitting data, and to perform frequency mapping on the third fitting data and a preset third target frequency point to obtain a second target relative dielectric constant;

[0147] The first data type is dielectric property data including both conductivity and relative permittivity, the second data type is dielectric property data including only conductivity, and the third data type is dielectric property data including only relative permittivity.

[0148] For the specific definition of a human tissue dielectric property measurement data processing system, please refer to the above-mentioned definition of a human tissue dielectric property measurement data processing method, which will not be repeated here. A person of ordinary skill in the art will appreciate that the various modules and steps described in conjunction with the embodiments disclosed in this application can be implemented in hardware, software, or a combination of both. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can 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 this application.

[0149] Compared with the prior art, the human tissue dielectric property measurement data processing system provided in the present application transforms the dielectric property data at the measurement frequency to the specified frequency through various processing modules and analysis modules. The present embodiment performs different processing on complete dielectric property data and incomplete dielectric property data, and provides different frequency conversion methods. The system provided in the present embodiment can obtain dielectric property data at unmeasured frequency points based on the limited data measured by the hardware device, thereby reducing the performance requirements of the measurement device hardware and reducing the measurement cost.

[0150] Figure 8 A computer device provided by an embodiment of the present invention includes a memory, a processor and a transceiver, which are connected via a bus; the memory is used to store a set of computer program instructions and data, and can transmit the stored data to the processor, and the processor can execute the program instructions stored in the memory to perform the steps of the above method.

[0151] The memory may include a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories; the processor may be a central processing unit, a microprocessor, an application-specific integrated circuit, a programmable logic device, or a combination thereof. By way of example but not limitation, the programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0152] Additionally, the memory may be a physically separate unit or may be integrated with the processor.

[0153] It can be understood by those skilled in the art that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have the same component arrangement.

[0154] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0155] The embodiments of the present invention provide a method, system, device and storage medium for processing data on dielectric property measurements of human tissue. The method for processing data on dielectric property measurements of human tissue utilizes the calculation of the Cole-Cole mathematical model to perform curve fitting on dielectric property data and obtain model parameters, thereby achieving the technical effect of transforming dielectric property data at a measured frequency to data at a specified frequency. The method provided by the embodiments of the present invention is simple to calculate, avoids complex calculation work, and can achieve rapid frequency conversion.

[0156] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., an SSD), etc.

[0157] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods.

[0158] The above-mentioned embodiments only express several preferred implementation modes of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in the technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be based on the protection scope of the claims.

Claims

1. A method for processing data of dielectric property measurement of human tissue, characterized in that: The following steps are involved: Acquire dielectric characteristic data, and determine the data type of the dielectric characteristic data; When it is detected that the dielectric characteristic data is of the first data type, preprocessing the dielectric characteristic data to obtain first dielectric characteristic data, and obtaining target data according to the first dielectric characteristic data; The step of obtaining target data according to the first dielectric characteristic data comprises: Obtaining a complex dielectric constant according to the first dielectric characteristic data; Fitting the complex dielectric constant using a first model to obtain first fitting data; Performing frequency mapping on the first fitting data and a preset first target frequency point to obtain a target complex dielectric constant, and obtaining target data according to the target complex dielectric constant; Wherein, the first data type is dielectric characteristic data including both conductivity and relative dielectric constant, and the target data includes a first target conductivity and a first target relative dielectric constant; The step of preprocessing the dielectric characteristic data to obtain the first dielectric characteristic data is specifically: smoothing the conductivity and relative dielectric constant in the dielectric characteristic data by using a Gaussian smoothing filter to obtain the first dielectric characteristic data; wherein the first dielectric characteristic data includes the conductivity and relative dielectric constant after filtering; The first model is specifically: In the formula, ε * is the complex dielectric constant, ε ∞ ′ represents the relative dielectric constant when the dielectric characteristic data is the first data type and the frequency is infinite, σ s1 represents the first DC conductivity, ε0 ​​represents the vacuum dielectric constant, f′ represents the first measurement frequency when the dielectric characteristic data is the first data type, j represents the sign of the complex imaginary part, Δε n ′ represents the first relative dielectric constant increment corresponding to the nth dispersion, τ n ′ represents the first average relaxation time corresponding to the nth dispersion, α n ' represents the first relaxation time distribution coefficient corresponding to the nth type of dispersion, and the value range of n is [1, 4]; wherein the first fitting data includes the first DC conductivity, the relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, the first relative dielectric constant increment, the first average relaxation time, and the first relaxation time distribution coefficient; The calculation formula of the frequency mapping is: In the formula, ε * (f0) represents the target complex dielectric constant, ε ∞ ′ represents the relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, ε0 represents the vacuum dielectric constant, f0′ represents the first target frequency point, j represents the sign of the complex imaginary part, σ s1 , ε ∞ ′、Δε n ′、τ n ′、α n ′ all belong to the first fitting data, and respectively represent the first DC conductivity obtained by fitting, the relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, the first relative dielectric constant increment corresponding to the n-th dispersion, the first average relaxation time corresponding to the n-th dispersion, and the first relaxation time distribution coefficient corresponding to the n-th dispersion, and the value range of n is [1, 4]; The calculation formula of the step of obtaining target data according to the target complex dielectric constant is specifically: σ′(f0)=-2πf0′ε0Im{ε * (f0)} ε r ′(f0)=Re{ε * (f0)} Where σ′(f0) represents the first target conductivity, f0′ represents the first target frequency point, ε0 represents the vacuum dielectric constant, and ε * (f0) represents the target complex dielectric constant, ε r '(f0) represents the first target relative permittivity.

2. A method for processing human tissue dielectric property measurement data as claimed in claim 1, characterized in that: The method further comprises: When it is detected that the dielectric characteristic data is of the second data type, smoothing and filtering the dielectric characteristic data to obtain second dielectric characteristic data, and acquiring a second target conductivity according to the second dielectric characteristic data; The step of acquiring a second target conductivity according to the second dielectric characteristic data comprises: Based on the second dielectric characteristic data and the second measurement frequency, fitting is performed through a second model to obtain second fitting data; Performing frequency mapping on the second fitting data and a preset second target frequency point to obtain a second target conductivity; Wherein, the second data type is dielectric characteristic data containing only conductivity, and the second dielectric characteristic data contains only filtered conductivity data; The calculation formula of the second model is: Wherein, σ″ represents the second dielectric characteristic data, f″ represents the second measurement frequency when the dielectric characteristic data is the second data type, ε0 represents the vacuum dielectric constant, sinh and cosh are hyperbolic sine and hyperbolic cosine functions respectively, σ s2 , Δε n ″、τ n ″、α n ″ all belong to the second fitting data, respectively representing the second DC conductivity, the second relative permittivity increment corresponding to the n-th dispersion, the second average relaxation time corresponding to the n-th dispersion, and the second relaxation time distribution coefficient corresponding to the n-th dispersion, and the value range of n is [1, 4].

3. A method for processing human tissue dielectric property measurement data as claimed in claim 1, characterized in that: The method comprises: When it is detected that the dielectric characteristic data is of a third data type, smoothing and filtering the dielectric characteristic data to obtain third dielectric characteristic data, and obtaining a second target relative dielectric constant according to the third dielectric characteristic data; The step of obtaining a second target relative dielectric constant according to the third dielectric characteristic data comprises: Based on the third dielectric characteristic data and the third measurement frequency, a third model is used for fitting to obtain third fitting data; Performing frequency mapping on the third fitting data and a preset third target frequency point to obtain a second target relative permittivity; Wherein, the third data type is dielectric characteristic data containing only relative dielectric constant, and the third dielectric characteristic data contains only filtered relative dielectric constant data; The calculation formula of the third model is: In the formula, ε r ″ represents the third dielectric characteristic data, ε ∞ ″ represents the relative dielectric constant when the dielectric characteristic data is of the third data type and the frequency is infinite, f″′ represents the third measurement frequency when the dielectric characteristic data is of the third data type, wherein the third fitting data includes the third relative dielectric constant increment Δε corresponding to the nth dispersion n ″′, the third average relaxation time τ corresponding to the nth dispersion n ″′, the third relaxation time distribution coefficient α corresponding to the nth dispersion n ″′, the dielectric characteristic data is the third data type and the relative dielectric constant ε when the frequency is infinite ∞ ″, the value range of n is [1, 4].

4. A human tissue dielectric property measurement data processing system, characterized in that: The system comprises: A determination module, used to obtain dielectric characteristic data and determine the data type of the dielectric characteristic data; A first processing module, configured to pre-process the dielectric characteristic data to obtain first dielectric characteristic data when detecting that the dielectric characteristic data is of a first data type; a first analysis module, configured to obtain a complex dielectric constant according to the first dielectric characteristic data, and to fit the complex dielectric constant using a first model to obtain first fitting data; and to perform frequency mapping on the first fitting data and a preset first target frequency point to obtain a target complex dielectric constant, and to obtain target data according to the target complex dielectric constant; A second processing module, configured to perform smoothing filtering on the dielectric characteristic data to obtain second dielectric characteristic data when detecting that the dielectric characteristic data is of a second data type; A second analysis module is used to perform fitting through a second model based on the second dielectric characteristic data and the second measurement frequency to obtain second fitting data, and perform frequency mapping on the second fitting data and a preset second target frequency point to obtain a second target conductivity; A third processing module, configured to perform smoothing filtering on the dielectric characteristic data to obtain third dielectric characteristic data when detecting that the dielectric characteristic data is of a third data type; A third analysis module is used to perform fitting using a third model based on the third dielectric characteristic data and the third measurement frequency to obtain third fitting data, and to perform frequency mapping on the third fitting data and a preset third target frequency point to obtain a second target relative dielectric constant; The first data type is dielectric property data including both conductivity and relative permittivity, the second data type is dielectric property data including only conductivity, the third data type is dielectric property data including only relative permittivity, and the target data includes a first target conductivity and a first target relative permittivity; The preprocessing of the dielectric characteristic data to obtain the first dielectric characteristic data is specifically: smoothing the conductivity and relative dielectric constant in the dielectric characteristic data by using a Gaussian smoothing filter to obtain the first dielectric characteristic data; wherein the first dielectric characteristic data includes the conductivity and relative dielectric constant after filtering; The first model is specifically: In the formula, ε * is the complex dielectric constant, ε ∞ ' represents the relative dielectric constant when the dielectric characteristic data is the first data type and the frequency is infinite, represents the first DC conductivity, ε0 ​​represents the vacuum dielectric constant, f′ represents the first measurement frequency when the dielectric characteristic data is the first data type, j represents the sign of the complex imaginary part, Δε n ′ represents the first relative dielectric constant increment corresponding to the nth dispersion, τ n ′ represents the first average relaxation time corresponding to the nth dispersion, α n ' represents the first relaxation time distribution coefficient corresponding to the nth type of dispersion, and the value range of n is [1, 4]; wherein the first fitting data includes the first DC conductivity, the relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, the first relative dielectric constant increment, the first average relaxation time, and the first relaxation time distribution coefficient; The calculation formula of the frequency mapping is: In the formula, ε * (f0) represents the target complex dielectric constant, ε ∞ ′ represents the relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, ε0 represents the vacuum dielectric constant, f0′ represents the first target frequency point, j represents the sign of the complex imaginary part, σ s1 , ε ∞ ′、Δε n ′、τ n ′、α n ′ all belong to the first fitting data, and respectively represent the first DC conductivity obtained by fitting, the relative dielectric constant when the dielectric characteristic data is of the first data type and the frequency is infinite, the first relative dielectric constant increment corresponding to the n-th dispersion, the first average relaxation time corresponding to the n-th dispersion, and the first relaxation time distribution coefficient corresponding to the n-th dispersion, and the value range of n is [1, 4]; The calculation formula of the step of obtaining target data according to the target complex dielectric constant is specifically: σ′(f0)=-2πf0′ε0Im{ε * (f0)} ε r ′(f0)=Re{ε * (f0)} Where σ′(f0) represents the first target conductivity, f0′ represents the first target frequency point, ε0 represents the vacuum dielectric constant, and ε * (f0) represents the target complex dielectric constant, ε r '(f0) represents the first target relative permittivity.

5. A computer device, characterized in that: The computer device comprises a processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the computer device executes the method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the method according to any one of claims 1 to 3 is implemented.

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