Three-dimensional EIT imaging device, method and program product

Abstract

The invention relates to the field of intelligent medical treatment, in particular to a three-dimensional EIT imaging device and method and a program product. The electrode module comprises N electrodes, N is a natural number larger than or equal to 16, and the electrode module is used for being fixed to a measured part of a person to be measured; the acquisition module is used for applying constant-current excitation signals to the first electrode and the second electrode in the electrode module and measuring voltage signals between the second electrode and other electrodes; the transmission module is used for transmitting the voltage signal of the acquisition module; the data processing module is used for receiving the voltage signal of the transmission module and carrying out signal processing and image reconstruction; and the imaging module is used for receiving the data of the data processing module and displaying an EIT imaging result. According to the method, the three-dimensional EIT image can be quickly and effectively obtained, and the method has good clinical value.

Description

Technical Field

[0001] The present application relates to the field of intelligent medical treatment, and specifically to a three-dimensional EIT imaging device, method, program product and computer-readable storage medium. Background Art

[0002] Electrical Impedance Tomography (EIT) is an imaging technology that applies a safe current (voltage) on the surface of a living organism, measures the surface voltage (current), and reconstructs the electrical impedance distribution map inside the living organism, based on the phenomenon that different tissues in the living organism and the same tissue in different states have different electrical conductivities. In previous studies, electrical impedance tomography (EIT) was limited to the assumption that its imaging data came from a two-dimensional (2D) object. However, in reality, the research object is generally a three-dimensional (3D) structure, so that the excitation current is not only conducted in the measurement plane, but also in the three-dimensional space. This difference leads to the image affecting the existence of EIT in diagnosis and pathological analysis. Therefore, three-dimensional electrical impedance tomography (3D-EIT) was developed on this basis. In order to obtain more biological tissue information, it can perform three-dimensional scanning of the living organism, and can also perform three-dimensional imaging of the living organism through a three-dimensional imaging algorithm. However, the current three-dimensional EIT imaging technology has a relatively low spatial resolution, making it difficult to clearly display tiny lesions or fine tissue anatomical structures. It has insufficient detection capabilities for some early, tiny tumors or other subtle lesions. Secondly, reconstructing the internal electrical impedance distribution from the voltage or current data measured at the boundary is a highly ill-posed and ill-posed inverse problem with multiple possible solutions, which makes accurate solution very difficult and requires reliance on complex algorithms and a large amount of prior information, increasing the complexity and uncertainty of imaging. Summary of the invention

[0003] In view of the above problems, the present invention provides a three-dimensional EIT imaging device, which specifically includes:

[0004] The electrode module includes N electrodes, where N is a natural number greater than or equal to 16, and is used to be fixed on the measured part of the subject; the acquisition module is used to apply a constant current excitation signal to the first electrode and the second electrode in the electrode module and measure the voltage signal between the second electrode and the other electrodes;

[0005] Transmission module: used to transmit the voltage signal of the acquisition module;

[0006] Data processing module: receiving the voltage signal of the transmission module and performing signal processing and image reconstruction;

[0007] Imaging module: used to receive the data from the data processing module to display the EIT imaging results.

[0008] The electrodes of the electrode module include M electrodes fixed in an array on the measured area of ​​the subject to be measured, and NM electrodes fixed above and / or below the M array electrodes, where M is less than N and M is a natural number greater than or equal to 12;

[0009] Optionally, the number of the NM electrodes fixed above the M electrode arrays is greater than or equal to the number below;

[0010] Optionally, the NM electrode fixing areas include: a position of the right subclavian fossa close to the shoulder, a position of the left subclavian fossa close to the shoulder, the left lower abdomen, and the right lower abdomen;

[0011] Optionally, the N electrodes are 16 electrodes, M is 13 electrodes, and NM is 3 electrodes;

[0012] Optionally, the N electrodes are 16 electrodes, M is 12 electrodes, and NM is 4 electrodes;

[0013] Optionally, the N electrodes are 19 electrodes, M is 16 electrodes, and NM is 3 electrodes;

[0014] Optionally, the N electrodes are 20 electrodes, M is 16 electrodes, and NM is 4 electrodes.

[0015] The device also includes an ECG measurement module, which obtains ECG signal data by measuring NM electrodes, wherein the NM electrodes are distributed above and below the M array electrodes; after the ECG signal data is measured by the ECG measurement module, it is transmitted to the second imaging module for display through the transmission module.

[0016] The object of the present invention is to provide a three-dimensional EIT imaging method, comprising:

[0017] Acquiring a voltage signal after the electrode fixed on the measured part of the subject is stimulated;

[0018] The voltage signal is calculated and input into the conductivity distribution model to obtain conductivity distribution data; the conductivity distribution model is constructed based on the relationship between the voltage signal and the conductivity;

[0019] calculating a reconstruction matrix based on the conductivity distribution data;

[0020] Image reconstruction is performed based on the reconstruction matrix to obtain a three-dimensional EIT image.

[0021] The voltage signal is acquired by the above-mentioned three-dimensional EIT imaging device;

[0022] Optionally, the reconstructed matrix includes two-dimensional conductivity data, three-dimensional spatial structure data, and three-dimensional conductivity data;

[0023] Optionally, the three-dimensional EIT image includes a two-dimensional EIT image and a three-dimensional EIT image;

[0024] Optionally, when the electrode distribution is such that the number of NM electrodes fixed above the M electrode arrays is equal to the number below, the mapping of the three-dimensional conductivity of the three-dimensional EIT image in the two-dimensional image obtains the occurrence position of the impedance change in the three-dimensional space through an electrode distributed on one side; the occurrence position includes the upper side of the mapping plane of the two-dimensional imaging and the lower side of the mapping plane of the two-dimensional imaging;

[0025] Optionally, the three-dimensional conductivity is mapped in a two-dimensional image to obtain a location where impedance change occurs in three-dimensional space through an electrode distributed underneath.

[0026] The conductivity distribution model is constructed by one or more of the following methods: finite element method, boundary element method;

[0027] Optionally, the conductivity distribution model is constructed as follows:

[0028] Obtain a three-dimensional image of the measured area;

[0029] Correcting the three-dimensional image to obtain corrected three-dimensional image data;

[0030] Calculating a matrix equation based on the corrected three-dimensional image data to obtain a conductivity distribution model;

[0031] Optionally, the correction is to correct the region in the three-dimensional image data to an ideal tissue distribution based on prior knowledge;

[0032] Optionally, the conductivity distribution model further includes a noise removal module for removing noise;

[0033] Optionally, the noise removal module performs noise removal through a noise model.

[0034] Optionally, the conductivity distribution model is obtained by training a neural network, and the neural network includes one or more of the following: a convolutional neural network, a residual network, and a Transformer.

[0035] The method further includes imaging optimization, recalculating a reconstruction matrix by removing the sensitivity of non-interested regions to obtain an interest region reconstruction matrix, and reconstructing an image based on the interest region reconstruction matrix to obtain a three-dimensional EIT image;

[0036] Optionally, the sensitivity of removing the non-interested region is to set the conductivity and sensitivity of the non-interested region in the reconstruction matrix to 0;

[0037] Optionally, the region of interest includes one or more of the following: a heart region, a lung region, or a cardiopulmonary region.

[0038] Optionally, the heart region includes a left heart region and a right heart region.

[0039] Optionally, the lung regions include a left lung region, a right lung region, a ventral region, and a dorsal region.

[0040] The method also includes ECG measurement, obtaining ECG signals through NM electrodes;

[0041] Optionally, performing EIT reconstruction through M electrodes to obtain a two-dimensional EIT image;

[0042] Optionally, three-dimensional EIT reconstruction is performed through N electrodes to obtain a three-dimensional EIT image;

[0043] Optionally, the N electrodes acquire EIT voltage signals and ECG signals through different time windows, obtain a three-dimensional EIT image through the EIT voltage signal, and assist in disease diagnosis based on the three-dimensional EIT image and / or ECG signal;

[0044] Optionally, the different time windows are: when measuring ECG, NM electrodes are used to measure ECG signals, and M electrodes are not working or are used to measure voltage signals required for two-dimensional EIT signals; when measuring three-dimensional EIT, N electrodes are used to measure EIT voltage signals.

[0045] An object of the present invention is to provide a computer program product, which includes a computer program or instructions, and the computer program or instructions are executed by a processor to implement the above-mentioned three-dimensional EIT imaging method.

[0046] An object of the present invention is to provide a computer-readable storage medium having a computer program or instructions stored thereon, wherein the computer program or instructions are executed by a processor to implement the above-mentioned three-dimensional EIT imaging method.

[0047] Advantages of the present invention:

[0048] 1. In view of the three-dimensional (3D) distributed sensor array (multiple sensor arrays) used in current three-dimensional imaging devices, due to the increase in the number of electrodes, the single-frame data acquisition time is prolonged, and a faster data acquisition system needs to be built to track changes in the measured object. Therefore, the present invention uses one array electrode for two-dimensional EIT imaging and three or four additional electrodes for three-dimensional EIT imaging. The excitation and voltage generated by the device greatly reduce the use of electrodes or sensors, reduce consumables, and reduce the computational complexity of solving the inverse problem of imaging while meeting the basic requirements of three-dimensional EIT imaging, and has good clinical use value.

[0049] 2. More independent measurement data is needed for three-dimensional imaging, and the impact of the underdetermination of the inverse problem solution on the imaging quality should be minimized. The original two-dimensional imaging can only display the two-dimensional cross-sectional information of the object being measured, ignoring the three-dimensional field distribution. It is necessary to further study the three-dimensional EIT imaging problem to provide more accurate three-dimensional information of the measured field. Therefore, the present invention proposes a three-dimensional EIT imaging method, which constructs a three-dimensional EIT image through the voltage of 19 electrodes for excitation and measurement, greatly reducing the amount of calculation for solving the inverse problem, not only retaining the characteristics of EIT time resolution, but also including three-dimensional conductivity data, providing a powerful tool for clinical disease diagnosis, and having excellent clinical application value.

[0050] 3. The present invention aims to solve the problem that the three-dimensional EIT imaging method can obtain a three-dimensional EIT image but cannot determine the position where the three-dimensional electrical impedance changes (above or below the two-dimensional detection area). The present invention uses 20 electrodes (one more than the 19 electrodes) to complete the three-dimensional EIT imaging and can obtain the position where the three-dimensional electrical impedance changes, which helps to accurately assist clinical disease diagnosis.

[0051] 4. The present invention uses 16 electrodes for 3D EIT reconstruction, wherein 13 electrodes are used to measure voltage signals in array form, and the remaining 3 electrodes are fixed above and below the 13 array electrodes, or 12 electrodes are used to measure voltage signals in array form, and the remaining 4 electrodes are fixed above and below the 12 array electrodes for signal excitation or acquisition. This method can perform 3D EIT signal acquisition on the basis of existing 2D EIT signal acquisition equipment, without the need to replace additional equipment, and the reconstruction algorithm can be updated to meet the requirements of 3D EIT imaging. Furthermore, in one set of equipment, the signal acquisition of 2D EIT and 3D EIT can be met by adjusting the electrode fixing mode, reducing the loss of consumables. At the same time, it can also meet the requirements of ECG detection.

[0052] In the process of image reconstruction, the present invention obtains the "expected image" by idealizing and correcting the training data, combines the positive problem and the noise model, calculates the linear relationship between the expected image and the boundary voltage, constructs a finite element model, and further uses the finite element model to obtain the reconstruction matrix. The reconstruction algorithm allows the linear expression of the reconstruction matrix, thereby using less computational cost.

[0053] In addition, the present invention further optimizes the reconstruction matrix, introduces the information of the region of interest, constrains the conductivity change, reduces the calculation complexity, and improves the estimation accuracy.

[0054] 6. The three-dimensional EIT imaging method of the present invention can also measure ECG signals, and can select measurement modes according to different needs, including separately measuring the data required for two-dimensional EIT signals, the data required for three-dimensional EIT signals, ECG signal data, simultaneously measuring the data required for ECG signals and two-dimensional EIT signals, and measuring the data required for ECG signals and three-dimensional EIT signals in different time windows. It can provide assistance based on clinical diagnosis needs and greatly improve diagnostic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0056] Figure 1 A schematic diagram of a three-dimensional EIT imaging device process provided by an embodiment of the present invention;

[0057] Figure 2 A schematic diagram of a three-dimensional EIT imaging method provided by an embodiment of the present invention;

[0058] Figure 3 A schematic diagram of a three-dimensional EIT imaging system provided by an embodiment of the present invention;

[0059] Figure 4 The current excitation and measurement mode provided by the embodiment of the present invention;

[0060] Figure 5 The three-dimensional EIT imaging image and the two-dimensional imaging image provided by the embodiment of the present invention;

[0061] Figure 6 Computer simulation effect of the imaging algorithm based on enhanced cardiopulmonary regional sensitivity constraints provided by the embodiment of the present invention;

[0062] Figure 7 A schematic diagram of three-dimensional electrical impedance flow provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0064] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The sequence numbers of the operations, such as S101, S102, etc., are only used to distinguish between different operations, and the sequence numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0065] Figure 1 A schematic diagram of a three-dimensional EIT imaging device provided in an embodiment of the present invention specifically includes:

[0066] Electrode module: includes N electrodes, N is a natural number greater than or equal to 16, and is used to be fixed on the measured part of the subject to be tested; in one embodiment, the electrodes of the electrode module include M electrodes fixed on the measured area of ​​the subject to be tested in the form of an array, and NM electrodes fixed above and / or below the M array electrodes, M is less than N, and M is a natural number greater than or equal to 12.

[0067] In one embodiment, the number of the NM electrodes fixed above the M electrode arrays is greater than or equal to the number below.

[0068] In one embodiment, the NM electrode fixing areas include: the position of the right subclavian fossa close to the shoulder, the position of the left subclavian fossa close to the shoulder, the left lower abdomen, and the right lower abdomen.

[0069] In one embodiment, the measured region includes a lung region.

[0070] In one embodiment, the N electrodes are 16 electrodes, M is 13 electrodes, and NM is 3 electrodes.

[0071] In one embodiment, the N electrodes are 16 electrodes, M is 12 electrodes, and NM is 4 electrodes.

[0072] In one embodiment, the N electrodes are 19 electrodes, M is 16 electrodes, and NM is 3 electrodes.

[0073] In one embodiment, the N electrodes are 20 electrodes, M is 16 electrodes, and NM is 4 electrodes.

[0074] Acquisition module: used for applying a constant current excitation signal to the first electrode and the second electrode in the electrode module and measuring the voltage signal between the second electrode and other electrodes;

[0075] In one embodiment, the first electrode and the second electrode in the electrode module apply a constant current excitation signal and measure the voltage signal between the second electrode and other electrodes. The first electrode is any one of the NM electrodes, the second electrode is any one of the M electrodes, and the other electrodes include other electrodes of the NM electrodes and other electrodes of the M electrodes. After the first electrode and the second electrode apply a constant current excitation signal and measure the voltage signal between the second electrode and other electrodes, the first electrode and / or the second electrode are updated, and the above process is repeated for measurement until the NM electrodes are traversed to become the first electrode. In a specific embodiment, three-dimensional EIT imaging is performed for excitation and acquisition such as Figure 4 As shown, there are 16 array electrodes, marked with numbers 1-16, and 2 electrodes are distributed above and below the 16 array electrodes, marked as ABCD respectively. Among the four electrodes ABCD, A is the first electrode, and among the 16 electrodes, 1 is the second electrode. The first electrode and the second electrode are stimulated, and the voltage between the second electrode and other electrodes (including 2-15 and BCD electrodes except the first electrode and the second electrode) is measured, and the first electrode is updated to the B electrode. The above steps are repeated until ABCD is traversed and all are the first electrode.

[0076] Transmission module: used to transmit the voltage signal of the acquisition module;

[0077] Data processing module: receiving the voltage signal of the transmission module and performing signal processing and image reconstruction;

[0078] Imaging module: used to receive the data from the data processing module to display the EIT imaging results.

[0079] In a specific embodiment, on the basis of ordinary EIT, three electrodes are added, of which the upper two electrodes plus the lower one are used for three-lead ECG measurement, and the EIT works in time. When measuring ECG, the EIT does not work (or only works in two-dimensional mode). When not measuring ECG, it is combined with the other 16 EIT electrodes to work as current excitation and measurement electrodes.

[0080] In a specific embodiment, on the basis of ordinary EIT, two electrodes are added, one on the top and one on the bottom, for three-lead ECG measurement, and the EIT works in time. When measuring ECG, the EIT does not work (or only works in two-dimensional mode). When not measuring ECG, it is combined with the other 16 EIT electrodes to work as current excitation and measurement electrodes.

[0081] In one embodiment, the device also includes an ECG measurement module, which obtains ECG signal data by measuring NM electrodes, wherein the NM electrodes are distributed above and below the M array electrodes; after the ECG signal data is measured by the ECG measurement module, it is transmitted to the second imaging module for display through the transmission module.

[0082] In one embodiment, the second imaging module is used to display ECG signals, including P waves, T waves, and QRS complexes.

[0083] In one embodiment, the three electrode sheets are connected to the corresponding interfaces of the electrocardiograph through electrode wires to ensure that the connection is firm and there is no looseness or poor contact. After confirming that the electrodes are connected correctly, start the electrocardiograph to start recording. The electrocardiograph will display the electrocardiogram waveform on the recording paper or on the display screen. During the recording process, the quality of the waveform should be observed to see if there are obvious interference signals, such as baseline drift (which may be caused by the patient's breathing movement or poor electrode contact), myoelectric interference (caused by the patient's muscle tension or trembling), etc. It is usually necessary to record for a long enough time to obtain a complete cycle of cardiac electrical activity. It is generally recommended to record an electrocardiogram for at least 10-15 seconds so that multiple cardiac cycles can be observed.

[0084] In one embodiment, the three-dimensional EIT image and the two-dimensional EIT image reconstructed by performing excitation and voltage signal acquisition on 20 electrodes are as follows: Figure 5 shown.

[0085] Figure 2 A schematic diagram of a three-dimensional EIT imaging method provided by an embodiment of the present invention specifically includes:

[0086] S101: Acquiring a voltage signal after the electrode fixed on the measured part of the subject is stimulated;

[0087] In one embodiment, the voltage signal is acquired by collecting the above-mentioned three-dimensional EIT imaging device.

[0088] In one embodiment, the voltage signal is acquired by collecting a plurality of array electrodes.

[0089] S102: Calculate the voltage signal and input it into a conductivity distribution model to obtain conductivity distribution data; the conductivity distribution model is constructed based on the relationship between the voltage signal and the conductivity;

[0090] In one embodiment, the conductivity distribution model is constructed by one or more of the following methods: finite element method, boundary element method.

[0091] In one embodiment, the process of constructing the conductivity distribution model is:

[0092] Obtain a three-dimensional image of the measured area;

[0093] Correcting the three-dimensional image to obtain corrected three-dimensional image data;

[0094] The conductivity distribution model is obtained by calculating the matrix equation based on the corrected three-dimensional image data.

[0095] In one embodiment, the correction is to correct the region in the three-dimensional image data to an ideal tissue distribution based on prior knowledge.

[0096] In one embodiment, the conductivity distribution model further includes a noise removal module for removing noise.

[0097] In one embodiment, the noise removal module performs noise removal by using a noise model, wherein the noise model comprises a Gaussian noise model.

[0098] In one embodiment, the conductivity distribution model is obtained by training a neural network, wherein the neural network includes one or more of the following: a convolutional neural network, a residual network, and a Transformer. The conductivity distribution model is obtained by inputting the three-dimensional electrical impedance and boundary voltage of the lung image to the neural network for training.

[0099] S103: Calculating a reconstruction matrix based on the conductivity distribution data;

[0100] In one embodiment, the reconstruction matrix includes two-dimensional conductivity data, three-dimensional spatial structure data, and three-dimensional conductivity data.

[0101] In one embodiment, the method further includes imaging optimization, recalculating a reconstruction matrix by removing the sensitivity of non-regions of interest to obtain a region of interest reconstruction matrix, and performing image reconstruction based on the region of interest reconstruction matrix to obtain a three-dimensional EIT image.

[0102] In one embodiment, the sensitivity of removing non-interest regions is to set the conductivity and sensitivity of the non-interest regions in the reconstruction matrix to zero.

[0103] In one embodiment, the region of interest includes one or more of the following: a heart region, a lung region, or a cardiopulmonary region.

[0104] In one embodiment, the heart region includes a left heart region and a right heart region, and the lung region includes a left lung region, a right lung region, a ventral region, and a dorsal region.

[0105] In a specific embodiment, the new imaging intelligent algorithm abandons the classic inverse problem solving method and is guided by the consensus indicators in the field of EIT to generate more clinically appropriate, easy-to-interpret and practical imaging. The "expected image" is obtained by idealizing and correcting the training data, combining the positive problem and the noise model, calculating its linear relationship with the boundary voltage, and obtaining the reconstruction matrix R. The algorithm details are as follows:

[0106]

[0107] Among them, ε is the error, is the expected image for the kth training, y (k) is the boundary voltage of the kth training, w (k) is the weighted proportion of the kth training, i and j are the rows and columns of R.

[0108] The second-order norm is used in the above formula because it allows linear expression of R and less computational cost. Based on the above formula, we can get:

[0109]

[0110] Where R is the reconstruction matrix, ε is the error, is the expected image for the kth training, y (k) is the boundary voltage of the kth training, w (k) is the weighted proportion of the k-th training, i and j are the rows and columns of R, l is the element of the non-j column in the derivation process, and A and B represent the previous summation terms respectively.

[0111] Because we assume that the weight w of each training data set is the same, B no longer depends on i, and we can solve R:

[0112]

[0113] R=AB -1

[0114] Where R represents the reconstructed matrix, i and j are the rows and columns of R, l is the element not in the j column during the derivation process, and A represents the previous summation term.

[0115] In a specific embodiment, based on the imaging algorithm enhanced by the cardiopulmonary regional sensitivity constraint, 2D imaging displays the mapping of 3D conductivity on the tomographic plane, and 3D imaging contains vertical structural information, providing a basis for cardiopulmonary regional imaging. The introduction of cardiopulmonary regional information constrains the conductivity change, reduces the computational complexity, and improves the estimation accuracy.

[0116] The conductivity change and sensitivity of the non-cardiopulmonary region are set to 0, only the changes in the cardiopulmonary region are estimated, and the reconstruction matrix R is recalculated to achieve 3D cardiopulmonary region sensitivity constraint enhanced imaging:

[0117] R=[A]ROI [B] ROI -1

[0118] Computer simulation results of imaging algorithm based on cardiopulmonary regional sensitivity constraint enhancement are shown in Figure 2. Figure 6 shown.

[0119] S104: Perform image reconstruction based on the reconstruction matrix to obtain a three-dimensional EIT image.

[0120] In one embodiment, the three-dimensional EIT image includes a two-dimensional EIT image and a three-dimensional EIT image.

[0121] In one embodiment, when the electrode distribution is NM electrodes fixed above the M electrode array, the number is equal to the number below, the mapping of the three-dimensional conductivity of the three-dimensional EIT image in the two-dimensional image obtains the occurrence position of the impedance change in the three-dimensional space through an electrode distributed on one side; the occurrence position includes the top of the mapping plane of the two-dimensional imaging and the bottom of the mapping plane of the two-dimensional imaging.

[0122] In one embodiment, the three-dimensional conductivity is mapped in a two-dimensional image to obtain the location where the impedance change occurs in the three-dimensional space through an electrode distributed underneath.

[0123] In one embodiment, the method further comprises ECG measurement, wherein ECG signals are obtained through NM electrodes.

[0124] In one embodiment, EIT reconstruction is performed using M electrodes to obtain a two-dimensional EIT image.

[0125] In one embodiment, three-dimensional EIT reconstruction is performed using N electrodes to obtain a three-dimensional EIT image.

[0126] In one embodiment, N electrodes acquire EIT voltage signals and ECG signals through different time windows, obtain a three-dimensional EIT image through the EIT voltage signal, and assist disease diagnosis based on the three-dimensional EIT image and / or ECG signal.

[0127] In one embodiment, the different time windows are: when measuring ECG, NM electrodes are used to measure ECG signals, and M electrodes are not working or are used to measure voltage signals required for two-dimensional EIT signals; when measuring three-dimensional EIT, N electrodes are used to measure EIT voltage signals.

[0128] In a specific embodiment, the solution for simultaneously measuring 3D-EIT and ECG is to use electrodes A, B, and D, a total of three electrodes, to complete the real-time three-lead ECG test while measuring 3D EIT, because the current 2D EIT actually includes 3D stereoscopic content (because the current does not flow in a straight line, the impedance changes outside the measurement plane can also be measured), but the problem is that the impedance changes mapped to the measurement plane cannot be determined whether they occur above or below the measurement plane. When electrode C is added outside the measurement plane, if the impedance change occurs below the plane, it can be detected by Cx (x represents 1, 2, ..., 16) current excitation and voltage measurement. If the impedance change occurs above the plane, there is no corresponding change in Cx, and it can be inferred that the impedance change occurs above the plane. Specifically, Figure 7 As shown, the projection of the changes on the same black line on the red plane is the same. 2DEIT can only identify which black line it is, but cannot identify where on the black line. When the C electrode is added, the location where the impedance change occurs can be identified.

[0129] In a specific embodiment, the current SCI literature also uses D-EIT. The simplest method is to tie 2-3 straps (each strap consists of 16 electrode arrays), but this method cannot be used clinically because: when a layer of electrodes is 16, 16 current injections and 14 voltage measurements are performed (the current injection electrode pairs are not measured). One frame of the image is 16*14=208 voltage measurements. Assuming that a certain device can measure 20 frames per second, it can achieve 320 current injections and 4160 voltage measurements.

[0130] Taking two strips and two layers with 16 electrodes in each layer as an example, there are two ways to achieve 3D:

[0131] Two independent circuit systems (integrated into one EIT machine) measure the data of two layers separately, and supplement the information of the area between the two layers with ML or AI ("pseudo 3D imaging").

[0132] Advantages: Simple structure. Disadvantages: The information supplemented in the middle area is not the real measured information, but the information obtained by the model based on experience, which cannot achieve individualized measurement.

[0133] Two layers of electrodes work together:

[0134] Advantages: True 3D imaging. Disadvantages: The amount of calculation increases greatly and cannot be processed in real time. To form a frame of image, the number of current injections per electrode pair in two layers increases from 16 times in pseudo 3D to (16*16+16*2)=288 (18 times) in true 3D, and the number of voltage measurements increases from 208 times in pseudo 3D to 16*16*15*15+208+208=58016 in true 3D. In addition, the 3D spatial expression assumes that the 3D lung is simply cut into 10 layers, and the hardware processing capacity of the device remains unchanged, then the imaging speed will change from the original 20 frames per second to 0.007 frames per second (1 frame in 142 seconds), which is equivalent to 1 / 2840 of the existing imaging speed, and cannot capture the dynamics of breathing and perfusion.

[0135] In a specific embodiment, ECG information can provide assistance for the blood flow information of EIT, and adding a three-lead ECG ABD tri-electrode to the 16-electrode array can significantly improve the spatial resolution based on the simple 3D EIT.

[0136] In a specific embodiment, two electrodes are added to the upper and lower electrodes on the basis of ordinary EIT. The upper two electrodes plus the lower one are measured in time periods as three-lead ECG measurement, and the EIT works in time. When measuring ECG, EIT does not work (or only works in two-dimensional mode). When ECG is not measured, it is combined with other 16 EIT electrodes to work as current excitation and measurement electrodes.

[0137] In a specific embodiment, the 2DEIT or 3D EIT calculated separately can be used for one or more of the following, but not limited to: 1. Critical care medicine / emergency-respiratory support mode selection, ventilator mode selection, the effect of suction, prone position and other techniques on ventilation, ventilator parameter adjustment, weaning, and evaluation of regional lung perfusion information. Solve pain points-reduce mortality and improve prognosis (confidence 90%, evidence 90%);

[0138] 2 Department of Anesthesiology - pre-operative pulmonary function assessment, anesthesia intubation, post-anesthesia respiratory support setting, post-operative anesthesia recovery monitoring, pulmonary function assessment. Solve pain points - reduce postoperative complications and improve prognosis (confidence 90% evidence 95%);

[0139] 3 Respiratory Department - pulmonary function test, diagnosis and treatment of chronic diseases, rehabilitation training. Solve pain points - detect lesions earlier than traditional pulmonary function tests, guide lung disease treatment, judge treatment effects, and guide rehabilitation training (confidence 90% evidence 80%).

[0140] 3D EIT and ECG measured in different time windows: When the patient's condition is stable, after determining information such as QRS wave information and heart rate variability through ECG, switch to measuring 20-electrode 3D EIT to further improve the 3D blood flow information based on EIT (EIT information only has relative change values, not absolute values. ECG information is equivalent to providing absolute value information related to the heartbeat. When used with the spatial information provided by EIT, both absolute value and spatial distribution information are available).

[0141] 2D EIT and ECG acquisition simultaneously: They need to work together when pulse-related signals need to be obtained, such as calculating changes in cardiac output (stroke volume).

[0142] Simultaneously collected 3D EIT and ECG: They need to work together when pulse-related signals need to be obtained, taking into account 3D spatial information, making them more comprehensive.

[0143] The disclosed embodiments of the present invention further provide a computer program product or system, including a computer program, which implements the above method steps when executed by a processor.

[0144] Figure 3 A schematic diagram of a three-dimensional EIT imaging system provided by an embodiment of the present invention specifically includes:

[0145] Acquisition unit: acquires the voltage signal after the electrode fixed on the measured part of the subject is stimulated;

[0146] Model unit: calculates the voltage signal and inputs it into the conductivity distribution model to obtain conductivity distribution data; the conductivity distribution model is constructed based on the relationship between the voltage signal and the conductivity;

[0147] A calculation unit: calculating a reconstruction matrix based on the conductivity distribution data;

[0148] Reconstruction unit: performs image reconstruction based on the reconstruction matrix to obtain a three-dimensional EIT image.

[0149] The disclosed embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, any one of the above-mentioned three-dimensional EIT imaging methods is implemented.

[0150] The verification results of this verification embodiment show that assigning inherent weights to indications can improve the performance of the method relative to the default setting. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units. A person of ordinary skill in the art may understand that all or part of the steps in the various methods of the above-mentioned embodiments may be completed by instructing the relevant hardware through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0151] A person of ordinary skill in the art can understand that all or part of the steps in the above-mentioned embodiment method can be implemented by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. The above-mentioned medium storage can be a read-only memory, a disk or an optical disk, etc.

[0152] The above is a detailed introduction to a computer device provided by the present invention. For a person skilled in the art, according to the concept of the embodiments of the present invention, there may be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A three-dimensional EIT imaging device, characterized in that: include: Electrode module: comprising N electrodes, where N is a natural number greater than or equal to 16, and is used to be fixed on the measured part of the subject; Acquisition module: used for applying a constant current excitation signal to the first electrode and the second electrode in the electrode module and measuring the voltage signal between the second electrode and other electrodes; Transmission module: used to transmit the voltage signal of the acquisition module; Data processing module: receiving the voltage signal of the transmission module and performing signal processing and image reconstruction; Imaging module: used to receive the data from the data processing module to display the EIT imaging results.

2. The three-dimensional EIT imaging device according to claim 1, characterized in that: The electrodes of the electrode module include M electrodes fixed in an array on the measured area of ​​the subject to be measured, and NM electrodes fixed above and / or below the M array electrodes, where M is less than N and M is a natural number greater than or equal to 12; Optionally, the number of the NM electrodes fixed above the M electrode arrays is greater than or equal to the number below; Optionally, the NM electrode fixing areas include: a position of the right subclavian fossa close to the shoulder, a position of the left subclavian fossa close to the shoulder, the left lower abdomen, and the right lower abdomen; Optionally, the N electrodes are 16 electrodes, M is 13 electrodes, and NM is 3 electrodes; Optionally, the N electrodes are 16 electrodes, M is 12 electrodes, and NM is 4 electrodes; Optionally, the N electrodes are 19 electrodes, M is 16 electrodes, and NM is 3 electrodes; Optionally, the N electrodes are 20 electrodes, M is 16 electrodes, and NM is 4 electrodes.

3. The three-dimensional EIT imaging device according to claim 2, characterized in that: The device also includes an ECG measurement module, which obtains ECG signal data by measuring NM electrodes, wherein the NM electrodes are distributed above and below the M array electrodes; after the ECG signal data is measured by the ECG measurement module, it is transmitted to the second imaging module for display through the transmission module.

4. A three-dimensional EIT imaging method, characterized in that: include: Acquiring a voltage signal after the electrode fixed on the measured part of the subject is stimulated; Calculating the voltage signal and inputting it into the conductivity distribution model to obtain conductivity distribution data; The conductivity distribution model is constructed based on the relationship between the voltage signal and the conductivity; calculating a reconstruction matrix based on the conductivity distribution data; Image reconstruction is performed based on the reconstruction matrix to obtain a three-dimensional EIT image.

5. The three-dimensional EIT imaging method according to claim 4, characterized in that: The voltage signal is acquired by collecting the three-dimensional EIT imaging device according to any one of claims 1 to 2; Optionally, the reconstructed matrix includes two-dimensional conductivity data, three-dimensional spatial structure data, and three-dimensional conductivity data; Optionally, the three-dimensional EIT image includes a two-dimensional EIT image and a three-dimensional EIT image; Optionally, when the electrode distribution is such that the number of NM electrodes fixed above the M electrode arrays is equal to the number below, the mapping of the three-dimensional conductivity of the three-dimensional EIT image in the two-dimensional image obtains the occurrence position of the impedance change in the three-dimensional space through an electrode distributed on one side; the occurrence position includes the upper side of the mapping plane of the two-dimensional imaging and the lower side of the mapping plane of the two-dimensional imaging; Optionally, the three-dimensional conductivity is mapped in a two-dimensional image to obtain a location where impedance change occurs in three-dimensional space through an electrode distributed underneath.

6. The three-dimensional EIT imaging method according to claim 4, characterized in that: The conductivity distribution model is constructed by one or more of the following methods: finite element method, boundary element method; Optionally, the conductivity distribution model is constructed as follows: Obtain a three-dimensional image of the measured area; Correcting the three-dimensional image to obtain corrected three-dimensional image data; Calculating a matrix equation based on the corrected three-dimensional image data to obtain a conductivity distribution model; Optionally, the correction is to correct the region in the three-dimensional image data to an ideal tissue distribution based on prior knowledge; Optionally, the conductivity distribution model further includes a noise removal module for removing noise; Optionally, the noise removal module performs noise removal through a noise model; Optionally, the conductivity distribution model is obtained by training a neural network, and the neural network includes one or more of the following: a convolutional neural network, a residual network, and a Transformer.

7. The three-dimensional EIT imaging method according to claim 4, characterized in that: The method further includes imaging optimization, recalculating a reconstruction matrix by removing the sensitivity of non-interested regions to obtain an interest region reconstruction matrix, and reconstructing an image based on the interest region reconstruction matrix to obtain a three-dimensional EIT image; Optionally, the sensitivity of removing the non-interested region is to set the conductivity and sensitivity of the non-interested region in the reconstruction matrix to 0; Optionally, the region of interest includes one or more of the following: heart region, lung region, cardiopulmonary region; Optionally, the heart region includes a left heart region and a right heart region; Optionally, the lung regions include a left lung region, a right lung region, a ventral region, and a dorsal region.

8. The three-dimensional EIT imaging method according to claim 5, characterized in that: The method also includes ECG measurement, obtaining ECG signals through NM electrodes; Optionally, performing EIT reconstruction through M electrodes to obtain a two-dimensional EIT image; Optionally, three-dimensional EIT reconstruction is performed through N electrodes to obtain a three-dimensional EIT image; Optionally, the N electrodes acquire EIT voltage signals and ECG signals through different time windows, obtain a three-dimensional EIT image through the EIT voltage signal, and assist in disease diagnosis based on the three-dimensional EIT image and / or ECG signal; Optionally, the different time windows are: when measuring ECG, NM electrodes are used to measure ECG signals, and M electrodes are not working or are used to measure voltage signals required for two-dimensional EIT signals; when measuring three-dimensional EIT, N electrodes are used to measure EIT voltage signals.

9. A computer program product comprising a computer program or instructions, characterized in that: The computer program or instructions are executed by a processor to implement the three-dimensional EIT imaging method according to any one of claims 1 to 5.

10. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: The computer program or instructions are executed by a processor to implement the three-dimensional EIT imaging method according to any one of claims 1 to 5.

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