Biological tissue internal temperature microwave chromatography method and system

Abstract

The invention discloses a biological tissue internal temperature microwave chromatography method and system, and belongs to the technical field of microwave measurement. The problem that the internal temperature of the biological tissue cannot be accurately obtained by adopting a microwave radiation temperature measurement technology nowadays is solved. The method comprises the following steps: acquiring environmental thermal radiation rates under different environmental conditions, and acquiring temperature distribution data of a human tissue profile to be subjected to temperature measurement along with depth change under different environmental conditions by utilizing a real three-dimensional anatomical model, a heat conduction equation and a thermal radiation equation of the human tissue to be subjected to temperature measurement; calculating dielectric constants of the human tissue to be subjected to temperature measurement under different frequencies, and obtaining radiation brightness temperature data of different frequencies under different environmental conditions by combining the temperature distribution data and a real three-dimensional anatomical model of the human tissue to be subjected to temperature measurement; constructing a brightness temperature-temperature conversion matrix by adopting a least square method; and acquiring brightness temperature data of different frequencies of human tissue to be subjected to temperature measurement, substituting the brightness temperature data into the brightness temperature-temperature conversion matrix, and performing inversion to obtain temperatures of different depths of the human tissue to be subjected to temperature measurement. The method is suitable for temperature measurement.

Description

Technical Field

[0001] This invention belongs to the field of microwave measurement technology. Background Technology

[0002] According to Planck's law of blackbody radiation, all objects in nature with a physical temperature above absolute zero radiate energy outward in the form of electromagnetic waves. By receiving the spontaneous microwave radiation signals emitted by these objects, the cross-sectional physical temperature information of a target from its surface to its depth can be obtained. In non-invasive human tissue temperature measurement scenarios, microwave radiation thermometry (MWR) technology developed based on this principle has advantages such as safety, non-invasiveness, ease of application, low measurement cost, and real-time measurement. Therefore, clinical detection of early physiological abnormalities in joints, lumbar spine, and other areas based on single-point measurements, such as neonatal hypothermia brain monitoring, vesicoureteral reflux detection, and these applications have been widely demonstrated to have significant potential for high-precision real-time monitoring.

[0003] Inversion of internal temperature in biological tissues is a crucial technical task, the core of which lies in the accurate mapping relationship between microwave radiation brightness temperature and physical temperature. Current research only relies on crude measurements at discrete single points, failing to obtain the temperature of internal layers. The uncertainty in the relationship between microwave radiation and temperature within human internal tissues, and the lack of algorithms for inverting profile temperatures in deep tissues, severely restrict the widespread application of MWR (Microwave Radiation Reduction) thermometry, resulting in the inability to accurately obtain temperatures at different depths within biological tissues. Summary of the Invention

[0004] This invention addresses the problem that current microwave radiation thermometry techniques cannot accurately obtain the internal temperature of biological tissues, and provides a microwave tomography method and system for measuring the internal temperature of biological tissues.

[0005] The microwave temperature chromatography method for biological tissues described in this invention includes:

[0006] Step 1: Collect the environmental thermal emissivity under different environmental conditions. Using the real three-dimensional anatomical model of the human tissue to be measured, the heat conduction equation and the heat radiation equation, obtain the temperature distribution data of the human tissue profile under different environmental conditions as a function of depth.

[0007] Step 2: Calculate the dielectric constant of the human tissue to be tested at different frequencies. Combine the temperature distribution data obtained in Step 1 and the real three-dimensional anatomical model of the human tissue to be tested to establish a radiation transfer model of the human tissue to be tested. Combine the incoherent model to obtain radiation brightness temperature data at different frequencies under different environmental conditions.

[0008] Step 3: Using the temperature distribution data described in Step 1 and the radiation brightness temperature data described in Step 2, construct the brightness temperature-temperature transformation matrix using the least squares method;

[0009] Step 4: Use a radiometer to collect brightness temperature data at different frequencies of the human tissue to be measured, input the brightness temperature-temperature conversion matrix, and invert to obtain the temperature of the human tissue at different depths.

[0010] Furthermore, in this invention, the method for obtaining the theoretical temperature distribution data of the human tissue profile with depth variation in the actual environment in step one is as follows:

[0011] Using the formula:

[0012] Formula 1

[0013] Formula 2

[0014] Acquire temperature distribution data of human tissue profiles as a function of depth, where ρ is tissue density, C is specific heat capacity, K is thermal conductivity, and Q is thermal conductivity. b It is a blood flow and heat production item, Q m This is the metabolic heat production term, where ε is the emissivity of the object's surface, and e is the emissivity of the surface. b (T) is the blackbody radiation calculated based on the actual temperature of the object; ρ d G is the surface reflectivity, and G is the amount of radiation received from the actual surrounding environment.

[0015] Furthermore, in this invention, the method for obtaining multi-frequency radiation brightness temperature data under different temperature conditions in step two is as follows:

[0016] Using the formula:

[0017] Formula 3

[0018] Calculate the dielectric constant ε of human tissue at the temperature to be measured. i , where ε ∞ It is the high-frequency limit of the dielectric constant, ω is the angular frequency, and α is the high-frequency limit of the dielectric constant. n It is the relaxation factor, τ n It is the organization's relaxation time, σ s The contribution of processes other than dielectric dispersion to conductivity is represented by ε0, where ε0 is the dielectric constant of free space, i represents the summation index of each relaxation process in the organization, and n represents the total number of relaxation processes in the organization.

[0019] Passed again:

[0020] Formula 4

[0021] Calculate the extinction coefficient of human tissue at the temperature to be measured, where κ ai It is the extinction coefficient of tissue layer i, μ i ε is the permeability of tissue layer i. i It is the dielectric constant of layer i;

[0022] Passed again:

[0023] Formula 5

[0024] Calculate the brightness temperature distribution of tissue layer i; where κ ai It is the extinction coefficient of tissue layer i, d i It is the thickness of tissue layer i, θ i T is the incident angle of the incident tissue layer i. i (z) represents the temperature distribution of the current tissue layer i, f(Г) i , L i ) represents the original brightness temperature and multiple reflection and transmission data within the tissue, z represents the depth of the tissue layer to be integrated, and l represents the index of different tissue layers.

[0025] Furthermore, in this invention, the method for constructing the brightness-temperature-temperature transformation matrix using the least squares method in step three is as follows:

[0026] Using the formula:

[0027]

[0028] By fitting the stratified temperature and multi-frequency brightness temperature data, a brightness temperature-temperature transformation matrix is ​​obtained, where β is the regression coefficient matrix and X... design Let be the brightness temperature-temperature transformation matrix for brightness temperature and physical temperature at different frequencies, λ be the regularization coefficient, I be the identity matrix, and Y be the target output data matrix.

[0029] Microwave tomography system for internal temperature analysis of biological tissues, including a radiometer and a data acquisition and processing device;

[0030] The radiometer includes a linearly polarized antenna and a radiation channel;

[0031] The linearly polarized antenna is used to align with the surface of the human tissue to be tested, receive the bright temperature radiation, and send the received bright temperature radiation signal to the radiation channel. The radiation channel extracts the bright temperature radiation at different depths and transmits the extracted bright temperature radiation at different depths to the data acquisition and processing device.

[0032] The data acquisition and processing device uses a brightness-temperature-temperature conversion matrix to convert brightness-temperature radiation at different depths into temperature data at different depths.

[0033] Furthermore, in this invention, the data acquisition and processing device includes a data collector, a data processor, and a data display;

[0034] The data acquisition device is used to collect brightness temperature radiation data at different depths and frequency bands;

[0035] The data processor is used to obtain layered temperature data of the tissue under test at different depths by inputting brightness temperature radiation data at different frequencies into a brightness temperature-temperature conversion matrix.

[0036] The data display is used to show the layered temperature data of the tissue at different depths.

[0037] Furthermore, in this invention, the radiation channels include a W-band radiometer channel, a C-band radiometer channel, and an S-band radiometer channel; the center frequency of the W-band radiometer channel is 94 GHz, the center frequency of the C-band radiometer channel is 4 GHz, and the center frequencies of the S-band radiometer channels are 2.2 GHz, 2.5 GHz, and 2.8 GHz.

[0038] This invention is the first to achieve temperature inversion at different depths of human tissue using multi-band microwave data. Because this method relies on passive observation, it presents greater challenges in retrieving internal physical parameters of the human body. Since brightness temperatures at different frequencies reflect biological tissue information at different depths, this invention also achieves joint temperature inversion across multiple frequency bands for the first time. It proposes an algorithm for acquiring human tissue temperature using a multi-frequency microwave radiometer, solving the problem of traditional temperature measurement methods struggling to obtain internal temperature information. Furthermore, this invention evaluated the algorithm's resistance to interference and error magnitude in different noise environments, and the final results demonstrate good robustness. Attached Figure Description

[0039] Figure 1 This is a flowchart of the method described in this invention;

[0040] Figure 2 Data on the three-dimensional thermodynamic temperature distribution of the human head surface under typical indoor conditions and a temperature profile comparison diagram;

[0041] Figure 3 This is a graph showing the temperature distribution of the human head as a function of depth at ten angles selected from the top of the head to the horizontal plane.

[0042] Figure 4 The spontaneous emission brightness temperature curves of the incoherent radiative transfer model in the range of 1 GHz to 100 GHz are shown.

[0043] Figure 5 The temperature inversion result curve is shown when the radiometer noise is 0K.

[0044] Figure 6(a) shows the temperature inversion results when the radiometer noise is 0.5K;

[0045] Figure 6(b) shows the temperature inversion results when the radiometer noise is 1K;

[0046] Figure 6(c) shows the temperature inversion results when the radiometer noise is 2K;

[0047] Figure 7 This is a schematic diagram of the structure of a millimeter-wave terahertz imaging system. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0049] Specific implementation method one: Refer to Figure 1 This embodiment specifically describes the microwave temperature chromatography method for biological tissues, which includes:

[0050] Step 1: Collect the environmental thermal emissivity under different environmental conditions. Using the real three-dimensional anatomical model of the human tissue to be measured, the heat conduction equation and the heat radiation equation, obtain the temperature distribution data of the human tissue profile under different environmental conditions as a function of depth.

[0051] Step 2: Calculate the dielectric constant of the human tissue to be tested at different frequencies. Combine the temperature distribution data obtained in Step 1 and the real three-dimensional anatomical model of the human tissue to be tested to establish a radiation transfer model of the human tissue to be tested. Combine the incoherent model to obtain radiation brightness temperature data at different frequencies under different environmental conditions.

[0052] Step 3: Using the temperature distribution data described in Step 1 and the radiation brightness temperature data described in Step 2, construct the brightness temperature-temperature transformation matrix using the least squares method;

[0053] Step 4: Use a radiometer to collect brightness temperature data at different frequencies of the human tissue to be measured, input the brightness temperature-temperature conversion matrix, and invert to obtain the temperature of the human tissue at different depths.

[0054] Furthermore, in this invention, the method for obtaining the theoretical temperature distribution data of the human tissue profile with depth variation in the actual environment in step one is as follows:

[0055] Using the formula:

[0056] Formula 1

[0057] Formula 2

[0058] Acquire temperature distribution data of human tissue profiles as a function of depth, where ρ is tissue density, C is specific heat capacity, K is thermal conductivity, and Q is thermal conductivity. b It is a blood flow and heat production item, Q m This is the metabolic heat production term, where ε is the emissivity of the object's surface, and e is the emissivity of the surface. b (T) is the blackbody radiation calculated based on the actual temperature of the object; ρ d G is the surface reflectivity, and G is the amount of radiation received from the actual surrounding environment.

[0059] Furthermore, in this invention, the method for obtaining the multi-frequency radiation brightness temperature under different temperature conditions in step two is as follows:

[0060] Using the formula:

[0061] Formula 3

[0062] Calculate the dielectric constant ε of human tissue at the temperature to be measured. i , where ε ∞ It is the high-frequency limit of the dielectric constant, ω is the angular frequency, and α is the high-frequency limit of the dielectric constant. n It is the relaxation factor, τ n It is the organization's relaxation time, σ s The contribution of processes other than dielectric dispersion to conductivity is represented by ε0, where ε0 is the dielectric constant of free space, i represents the summation index of each relaxation process in the organization, and n represents the total number of relaxation processes in the organization.

[0063] Passed again:

[0064] Formula 4

[0065] Calculate the extinction coefficient of human tissue at the temperature to be measured, where κ ai It is the extinction coefficient of tissue layer i, μ i ε is the permeability of tissue layer i. i It is the dielectric constant of layer i;

[0066] Passed again:

[0067] Formula 5

[0068] Calculate the brightness temperature distribution of tissue layer i; where κ ai It is the extinction coefficient of tissue layer i, d i It is the thickness of tissue layer i, θ i T is the incident angle of the incident tissue layer i. i (z) represents the temperature distribution of the current tissue layer i, f(Г) i , L i) represents the original brightness temperature and multiple reflection and transmission data within the tissue, z represents the depth of the tissue layer to be integrated, and l represents the index of different tissue layers.

[0069] Furthermore, in this invention, the method for constructing the brightness-temperature-temperature transformation matrix using the least squares method in step three is as follows:

[0070] Using the formula:

[0071]

[0072] By fitting the stratified temperature and multi-frequency brightness temperature data, a brightness temperature-temperature transformation matrix is ​​obtained, where β is the regression coefficient matrix and X... design Let be the brightness temperature-temperature transformation matrix for brightness temperature and physical temperature at different frequencies, λ be the regularization coefficient, I be the identity matrix, and Y be the target output data matrix.

[0073] Specific Implementation Method Two: Refer to Figure 7 This embodiment is described in detail. The system described in this embodiment is based on the microwave tomography method for internal temperature of biological tissues described in Specific Embodiment 1. The microwave tomography system for internal temperature of biological tissues described in this embodiment includes a radiometer and a data acquisition and processing device 3.

[0074] The radiometer includes a linearly polarized antenna 1 and a radiation channel 2;

[0075] The linearly polarized antenna 1 is used to align with the surface of the human tissue to be tested, receive the bright temperature radiation, and send the received bright temperature radiation signal to the radiation channel 2. The radiation channel 2 extracts the bright temperature radiation at different depths and transmits the extracted bright temperature radiation at different depths to the data acquisition and processing device 3.

[0076] The data acquisition and processing device 3 uses a brightness-temperature-temperature conversion matrix to convert brightness-temperature radiation at different depths into temperature data at different depths.

[0077] Furthermore, in this embodiment, the data acquisition and processing device 3 includes a data collector 31, a data processor 32, and a data display 33;

[0078] The data acquisition unit 31 is used to collect brightness temperature radiation data at different depths and frequency bands;

[0079] The data processor 32 is used to obtain layered temperature data of the tissue under test at different depths by inputting the brightness temperature radiation data at different frequencies into the brightness temperature-temperature conversion matrix.

[0080] The data display 33 is used to display the layered temperature data of the tissue at different depths.

[0081] Furthermore, in this embodiment, the radiation channel 2 includes a W-band radiometer channel, a C-band radiometer channel, and an S-band radiometer channel; the center frequency of the W-band radiometer channel is 94 GHz, the center frequency of the C-band radiometer channel is 4 GHz, and the center frequencies of the S-band radiometer channels are 2.2 GHz, 2.5 GHz, and 2.8 GHz.

[0082] This invention also includes a method for uncertainty analysis of the temperature inversion results, and a process for analyzing and verifying the brightness temperature-temperature transformation matrix, specifically as follows:

[0083] Step 41: Calculate the posterior covariance matrix of the temperature at different depths of the human tissue to be measured, and use the posterior covariance matrix to calculate the confidence level of the brightness temperature-temperature transformation matrix for the parameters.

[0084] Step 42: Derive the predicted distribution for each temperature value obtained through the brightness-temperature transformation matrix, calculate its predicted mean and variance, construct a 95% confidence interval, and evaluate the uncertainty value of each temperature value;

[0085] Step 4.3: Add various amplitude errors to the input brightness temperature data, and use the Monte Carlo method to evaluate the stability of the brightness temperature-temperature conversion matrix under different noise environments; if the stability meets the requirements, the stability analysis of the brightness temperature-temperature conversion matrix is ​​completed; otherwise, return to step 1 until a stable brightness temperature-temperature conversion matrix is ​​obtained.

[0086] This invention utilizes a high-precision anatomical 3D model, heat conduction equations, and thermal radiation equations to obtain profile data of temperature distribution changes with depth in the human body; based on the obtained temperature distribution data, a multi-layer tissue radiation transmission model of the human body is established, and multi-frequency radiation brightness temperature data under different temperature conditions is obtained using an incoherent model; furthermore, using microwave radiation brightness temperature and corresponding temperature distribution data in multiple frequency bands, a brightness temperature-temperature conversion matrix is ​​constructed using the least squares method; finally, uncertainty analysis of the brightness temperature-temperature conversion matrix is ​​performed based on the temperature results obtained from the inversion, effectively ensuring the accuracy of the obtained temperature.

[0087] This invention solves the problem of difficulty in obtaining temperatures at different depths within biological tissues. The algorithm is applicable to multi-layered human tissues and is the first to realize the inversion of internal temperature of biological tissues based on multi-frequency microwave radiation brightness temperature.

[0088] First, after obtaining a high-precision 3D anatomical model of the human body, typical 3D temperature distribution profile data of the human head under a normal indoor environment is obtained using the following heat conduction and heat radiation equations. In this embodiment, the obtained temperature distribution image is shown below. Figure 2 As shown, Figure 2 From left to right are the three-dimensional head surface temperature distribution data and the profile temperature distribution data.

[0089]

[0090]

[0091] Then, based on the obtained three-dimensional temperature distribution data, ten temperature curves varying with depth were selected according to the angle from the top of the head to the horizontal plane, such as... Figure 3 As shown. Based on this temperature curve, the radiative brightness temperature at multiple frequencies is calculated using the following formula. The calculation results for the brightness temperature from 1 GHz to 100 GHz are as follows. Figure 4 As shown.

[0092]

[0093] Then, multi-band brightness temperature data were selected: S-band (center frequencies 2.2 GHz, 2.5 GHz, 2.8 GHz), C-band (center frequency 4 GHz) for obtaining shallower brightness temperatures, and W-band (center frequency 94 GHz) for obtaining surface temperature information, along with the corresponding temperature data. A brightness temperature-temperature transformation matrix was constructed using the following formula combined with the least squares method. The inversion results of the brightness temperatures at the five selected center frequencies, without considering radiometer noise, are shown below. Figure 5 As shown.

[0094]

[0095] Subsequently, by adding radiometer observation noise to the brightness temperature, the temperature results obtained by using multi-band brightness temperature were also inverted, as shown in Figure 6. The radiometer noise added from left to right in Figure 6 are 0.5K, 1K, and 2K, respectively.

[0096] Subsequently, Monte Carlo simulations were performed on different radiometer noise amplitudes to obtain the standard deviation of the inversion results, and the stability of the algorithm was evaluated, as shown in the table below.

[0097] Table 1. The Influence of Different Radiometer Sensitivity on the Standard Deviation of Temperature Inversion in Each Tissue Layer

[0098]

[0099] Furthermore, in an exemplary embodiment of this disclosure, a biological tissue internal temperature microwave tomography system is also provided to perform the aforementioned biological tissue internal temperature microwave tomography method for obtaining the temperature of deep tissues within the human body, thereby obtaining the temperature of internal human tissues. Please refer to... Figure 7 In this exemplary embodiment, the biological tissue internal temperature microwave tomography system includes a linearly polarized antenna, a radiometer channel, and a data acquisition and processing device.

[0100] Specifically, a linearly polarized antenna is configured to be positioned above the specific biological tissue to be measured on the test object, used to receive the spontaneous emission brightness temperature of the test object. The received signal is then processed via the W-band, C-band, and S-band radiometer channels to obtain brightness temperature information at each center frequency. Finally, the brightness temperature is inverted by the data acquisition and processing device to generate the layered temperature information of the object. Specifically, the data acquisition and processing device includes a data acquisition unit, a data processor, and a data display. The data acquisition unit is configured to collect multi-frequency brightness temperature data from specific parts of the test object; the data processor is configured to process the brightness temperature information at different frequencies to obtain layered temperature data at various depths; and the data display is configured to display the corresponding layered temperatures at different depths.

[0101] While the invention has been described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the invention. Therefore, it should be understood that many modifications can be made to the exemplary embodiments, and other arrangements can be designed without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that different dependent claims and features described herein can be combined in ways different from those described in the original claims. It is also understood that features described in conjunction with individual embodiments can be used in other described embodiments.

Claims

1. A microwave chromatography method for the internal temperature of biological tissues, characterized in that, include: Step 1: Collect the environmental thermal emissivity under different environmental conditions. Using the real three-dimensional anatomical model of the human tissue to be measured, the heat conduction equation and the heat radiation equation, obtain the temperature distribution data of the human tissue profile under different environmental conditions as a function of depth. Step 2: Calculate the dielectric constant of the human tissue to be tested at different frequencies. Combine the temperature distribution data obtained in Step 1 and the real three-dimensional anatomical model of the human tissue to be tested to establish a radiation transfer model of the human tissue to be tested. Combine the incoherent model to obtain radiation brightness temperature data at different frequencies under different environmental conditions. Step 3: Using the temperature distribution data described in Step 1 and the radiation brightness temperature data described in Step 2, construct the brightness temperature-temperature transformation matrix using the least squares method; Step 4: Use a radiometer to collect brightness temperature data at different frequencies of the human tissue to be measured, input the brightness temperature-temperature conversion matrix, and invert to obtain the temperature of the human tissue at different depths.

2. The method for microwave chromatography of internal temperature in biological tissues according to claim 1, characterized in that, In step one, the method for obtaining the theoretical temperature distribution data of the human tissue profile under test with depth in the actual environment is as follows: Using the formula: Formula 1 Formula 2 Acquire temperature distribution data of human tissue profiles as a function of depth, where ρ is tissue density, C is specific heat capacity, K is thermal conductivity, and Q is thermal conductivity. b It is a blood flow and heat production item, Q m This is the metabolic heat production term, where ε is the emissivity of the object's surface, and e is the emissivity of the surface. b (T) is the blackbody radiation calculated based on the actual temperature of the object; ρ d G is the surface reflectivity, and G is the amount of radiation received from the actual surrounding environment.

3. The method for microwave chromatography of internal temperature in biological tissues according to claim 1, characterized in that, In step two, the method for obtaining multi-frequency radiation brightness temperature data under different temperature conditions is as follows: Using the formula: Formula 3 Calculate the dielectric constant ε of human tissue at the temperature to be measured. i , where ε ∞ It is the high-frequency limit of the dielectric constant, ω is the angular frequency, and α is the high-frequency limit of the dielectric constant. n It is the relaxation factor, τ n It is the organization's relaxation time, σ s The contribution of processes other than dielectric dispersion to conductivity is represented by ε0, where ε0 is the dielectric constant of free space, i represents the summation index of each relaxation process in the organization, and n represents the total number of relaxation processes in the organization. Passed again: Formula 4 Calculate the extinction coefficient of human tissue at the temperature to be measured, where κ ai It is the extinction coefficient of tissue layer i, μ i ε is the permeability of tissue layer i. i It is the dielectric constant of layer i; Passed again: Formula 5 Calculate the brightness temperature distribution of tissue layer i; where κ ai It is the extinction coefficient of tissue layer i, d i It is the thickness of tissue layer i, θ i T is the incident angle of the incident tissue layer i. i (z) represents the temperature distribution of the current tissue layer i, f(Г) i , L i ) represents the original brightness temperature and multiple reflection and transmission data within the tissue, z represents the depth of the tissue layer to be integrated, and l represents the index of different tissue layers.

4. The method for microwave chromatography of internal temperature in biological tissues according to claim 1, characterized in that, In step three, the method for constructing the brightness-temperature-temperature transformation matrix using the least squares method is as follows: Using the formula: By fitting the stratified temperature and multi-frequency brightness temperature data, a brightness temperature-temperature transformation matrix is ​​obtained, where β is the regression coefficient matrix and X... design Let be the brightness temperature-temperature transformation matrix for brightness temperature and physical temperature at different frequencies, λ be the regularization coefficient, I be the identity matrix, and Y be the target output data matrix.

5. A biological tissue internal temperature microwave chromatography system, wherein the system is implemented based on any of the biological tissue internal temperature microwave chromatography methods described in claims 1 to 4, characterized in that, Includes a radiometer and a data acquisition and processing device (3); The radiometer includes a linearly polarized antenna (1) and a radiation channel (2); The linearly polarized antenna (1) is used to align with the surface of the human tissue to be tested, receive the bright temperature radiation, and send the received bright temperature radiation signal to the radiation channel (2). The radiation channel (2) extracts the bright temperature radiation at different depths and transmits the extracted bright temperature radiation at different depths to the data acquisition and processing device (3). The data acquisition and processing device (3) uses a brightness-temperature-temperature conversion matrix to convert brightness-temperature radiation at different depths into temperature data at different depths.

6. The biological tissue internal temperature microwave chromatography system according to claim 5, characterized in that, The data acquisition and processing device (3) includes a data collector (31), a data processor (32), and a data display (33); The data acquisition unit (31) is used to collect brightness temperature radiation data at different depths and frequency bands; The data processor (32) is used to obtain layered temperature data of the tissue under test at different depths by inputting the brightness temperature radiation data at different frequencies into the brightness temperature-temperature conversion matrix; The data display (33) is used to display the layered temperature data of the tissue at different depths.

7. The biological tissue internal temperature microwave chromatography system according to claim 5 or 6, characterized in that, The radiation channel (2) includes a W-band radiometer channel, a C-band radiometer channel and an S-band radiometer channel; the center frequency of the W-band radiometer channel is 94 GHz, the center frequency of the C-band radiometer channel is 4 GHz, and the center frequencies of the S-band radiometer channels are 2.2 GHz, 2.5 GHz and 2.8 GHz.

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