A three-dimensional EIT imaging apparatus, method, and program product

Abstract

The application relates to the field of intelligent medical treatment, in particular to a three-dimensional EIT imaging device, method and program product. The device comprises an electrode module, an acquisition module, a transmission module, a data processing module and an imaging module. The electrode module comprises N electrodes, N is a natural number greater than or equal to 16, and is used for fixing at a measured part of a to-be-measured person. The acquisition module is used for applying a constant current excitation signal to a first electrode and a 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 signals of the acquisition module. The data processing module receives the voltage signals of the transmission module and performs signal processing and image reconstruction. The imaging module is used for receiving data of the data processing module and displaying EIT imaging results. The application can quickly and effectively obtain a three-dimensional EIT image, and has good clinical value.

Description

TECHNICAL FIELD

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

[0002] Electrical impedance tomography (EIT) is an imaging technology that reconstructs the electrical impedance distribution map of the inside of a living body according to the phenomenon that different tissues in the living body and the same tissue in different states have different conductivities, by applying a safe current (voltage) to the surface of the living body and measuring the surface voltage (current). In previous studies, electrical impedance tomography (EIT) was limited to assuming that its imaging data came from a two-dimensional (2D) object. However, in practice, the research object is generally a three-dimensional (3D) structure, so that the excitation current not only conducts in the measurement plane, but also conducts in the three-dimensional space. This difference affects the existence of EIT in diagnosis and ill-posed analysis. Therefore, three-dimensional electrical impedance tomography (3D-EIT) has been developed on this basis. In order to obtain more information about biological tissues, three-dimensional scanning of the living body can be performed, and three-dimensional imaging of the living body can also be performed through a three-dimensional imaging algorithm. However, the spatial resolution of the current three-dimensional EIT imaging technology is relatively low, and it is difficult to clearly display small lesions or fine tissue anatomical structures. The detection capability for some early, small tumors or other subtle lesions is insufficient. Secondly, reconstructing the internal electrical impedance distribution from the boundary measured voltage or current data is a highly ill-posed and ill-conditioned inverse problem, and there are multiple possible solutions, which makes it very difficult to accurately solve, and it needs to rely on complex algorithms and a large amount of prior information, increasing the complexity and uncertainty of imaging. SUMMARY

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

[0004] An electrode module comprising N electrodes, N being a natural number greater than or equal to 16, for fixing to the measurement site of the subject to be measured; an acquisition module 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 each of the other electrodes;

[0005] A transmission module for transmitting the voltage signal of the acquisition module;

[0006] A data processing module for receiving the voltage signal of the transmission module and performing signal processing and image reconstruction;

[0007] An imaging module for receiving the data of the data processing module to display the EIT imaging result.

[0008] The electrodes of the electrode module include M electrodes fixed in an array on a measurement area of a subject, N-M electrodes fixed above and / or below the M array electrodes, M being less than N, M being a natural number greater than or equal to 12;

[0009] Optionally, the number of the N-M electrodes fixed above the M electrode array is greater than or equal to the number of the N-M electrodes fixed below the M electrode array.

[0010] Optionally, the N-M electrode fixing area includes: 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, the M electrodes are 13 electrodes, and the N-M electrodes are 3 electrodes.

[0012] Optionally, the N electrodes are 16 electrodes, the M electrodes are 12 electrodes, and the N-M electrodes are 4 electrodes.

[0013] Optionally, the N electrodes are 19 electrodes, the M electrodes are 16 electrodes, and the N-M electrodes are 3 electrodes.

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

[0015] The device further includes an ECG measurement module for measuring ECG signal data through the N-M electrodes distributed above and below the M array electrodes, and transmitting the ECG signal data measured by the ECG measurement module to the second imaging module for display through the transmission module.

[0016] The present application aims to provide a three-dimensional EIT imaging method, comprising:

[0017] Obtaining a voltage signal after the electrodes fixed on the measurement part of the subject are excited;

[0018] Calculating the voltage signal to obtain the electrical conductivity distribution data in the electrical conductivity distribution model; the electrical conductivity distribution model is constructed by the relationship between the voltage signal and the electrical conductivity;

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

[0020] Reconstructing an image based on the reconstruction matrix to obtain a three-dimensional EIT image.

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

[0022] Optionally, the reconstruction matrix includes two-dimensional electrical conductivity data, three-dimensional spatial structure data, and three-dimensional electrical conductivity data.

[0023] Optionally, the three-dimensional EIT image comprises a two-dimensional EIT image and a three-dimensional EIT image.

[0024] Optionally, when the number of electrodes distributed above the M-electrode array is equal to the number of electrodes distributed below the M-electrode array, 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 one electrode distributed on one side; the occurrence position comprises above the mapping plane of the two-dimensional imaging and below the mapping plane of the two-dimensional imaging.

[0025] Optionally, the mapping of the three-dimensional conductivity in the two-dimensional image obtains the occurrence position of the impedance change in the three-dimensional space through one electrode distributed below.

[0026] The construction method of the conductivity distribution model adopts one or more of the following: a finite element method, a boundary element method.

[0027] Optionally, the construction process of the conductivity distribution model is as follows:

[0028] Obtain a three-dimensional image of the measured region.

[0029] Correct the three-dimensional image to obtain corrected three-dimensional image data.

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

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

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

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

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

[0035] The method further comprises imaging optimization, wherein a region-of-interest reconstruction matrix is obtained by recalculating a reconstruction matrix by removing sensitivity of a non-region-of-interest, and a three-dimensional EIT image is obtained by image reconstruction based on the region-of-interest reconstruction matrix.

[0036] Optionally, the sensitivity of the non-region-of-interest is set to 0 in the reconstruction matrix.

[0037] Optionally, the region of interest comprises one or more of the following: a cardiac region, a lung region, a cardio-pulmonary region.

[0038] Optionally, the cardiac region comprises a left cardiac region, a right cardiac region.

[0039] Optionally, the lung region comprises a left lung region, a right lung region, a ventral region, a dorsal region.

[0040] The method further comprises ECG measurement, obtaining ECG signals through N-M electrodes;

[0041] Optionally, two-dimensional EIT images are obtained through EIT reconstruction by M electrodes;

[0042] Optionally, three-dimensional EIT images are obtained through three-dimensional EIT reconstruction by N electrodes;

[0043] Optionally, N electrodes obtain EIT voltage signals and ECG signals through different time windows, three-dimensional EIT images are obtained through the EIT voltage signals, and disease diagnosis is assisted based on the three-dimensional EIT images and / or ECG signals.

[0044] Optionally, when measuring ECG, N-M electrodes are used to measure ECG signals, and M electrodes are not used or are used to measure voltage signals required for two-dimensional EIT signal measurement; when measuring three-dimensional EIT, N electrodes are used to measure EIT voltage signals.

[0045] The purpose of the present application is to provide a computer program product comprising a computer program or instructions thereon, which are executed by a processor to realize the three-dimensional EIT imaging method described above.

[0046] The purpose of the present application is to provide a computer readable storage medium storing a computer program or instructions thereon, which are executed by a processor to realize the three-dimensional EIT imaging method described above.

[0047] Advantages of the present application:

[0048] 1. In the current three-dimensional imaging device, a three-dimensional (3D) distributed sensor array (multiple sensor arrays) is used. 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 constructed to track the changes of the measurement object. Therefore, the present application uses a two-dimensional EIT imaging array electrode and an additional three or four 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 amount of the inverse problem solving of imaging, which has good clinical use value.

[0049] 2. More independent measurement data are needed for three-dimensional imaging to reduce the influence of underdetermination of inverse problem solving on imaging quality. The original two-dimensional imaging can only display two-dimensional cross-sectional information of the measured object, and ignores the three-dimensional field distribution, so it is necessary to further study the three-dimensional EIT imaging problem and provide more accurate three-dimensional information of the measured field. Therefore, the three-dimensional EIT imaging method is provided, which constructs a three-dimensional EIT image by exciting and measuring the voltage of 19 electrodes, greatly reduces the calculation amount of inverse problem solving, not only retains the characteristics of EIT time resolution, but also includes three-dimensional conductivity data, provides a powerful tool for clinical disease diagnosis, and has excellent clinical application value.

[0050] 3. The three-dimensional EIT imaging method of the present application obtains a three-dimensional EIT image, but cannot determine the position (above or below the two-dimensional detection area) where the three-dimensional resistance impedance changes. The three-dimensional EIT imaging is completed by using 20 electrodes (1 more than 19 electrodes), and the position where the three-dimensional resistance impedance changes can be obtained, which is helpful for accurate auxiliary clinical disease diagnosis.

[0051] 4. In the present application, 16 electrodes are used for three-dimensional EIT reconstruction, 13 of which are used for array form measurement of voltage signals, and the remaining 3 electrodes are fixed above and below the 13 array electrodes, or 12 electrodes are used for array form measurement of voltage signals, and the remaining 4 electrodes are fixed above and below the 12 array electrodes for signal excitation or collection. This method can collect three-dimensional EIT signals based on existing two-dimensional EIT signal collection equipment, without the need for additional equipment replacement. Updating the reconstruction algorithm can meet the three-dimensional EIT image imaging, and further, the signal collection of two-dimensional EIT and three-dimensional EIT can be met by adjusting the electrode fixing mode in a set of equipment, reducing the loss of consumables. At the same time, it can also meet the detection of ECG.

[0052] 5. In the image reconstruction process of the present application, the idealized modified training data are used to obtain the "expected image", the linear relationship between the expected image and the boundary voltage is calculated by combining the forward problem and the noise model, the finite element model is constructed, and the reconstruction matrix is further obtained by using the finite element model. The reconstruction algorithm allows linear expression of the reconstruction matrix, so less calculation cost is used.

[0053] In addition, the reconstruction matrix is further optimized in the present application, the information of the region of interest is introduced, the conductivity change is constrained, the calculation complexity is reduced, and the estimation accuracy is improved.

[0054] 6. The three-dimensional EIT imaging method of the present application can also measure ECG signals, and can select a measurement mode according to different requirements, including data required for measuring a two-dimensional EIT signal alone, data required for measuring a three-dimensional EIT signal, ECG signal data, data required for measuring an ECG signal and a two-dimensional EIT signal simultaneously, data required for measuring an ECG signal and a three-dimensional EIT signal at different time windows, and can provide help based on clinical diagnosis requirements, greatly improving the diagnosis efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0056] Figure 1 A three-dimensional EIT imaging device flowchart is provided for the embodiments of the present application.

[0057] Figure 2 A three-dimensional EIT imaging method diagram is provided for the embodiments of the present application.

[0058] Figure 3 A three-dimensional EIT imaging system diagram is provided for the embodiments of the present application.

[0059] Figure 4 A current excitation and measurement mode is provided for the embodiments of the present application.

[0060] Figure 5 A three-dimensional EIT imaging image and a two-dimensional imaging image are provided for the embodiments of the present application.

[0061] Figure 6 A computer simulation result of an imaging algorithm based on heart and lung region sensitivity constraint enhancement is provided for the embodiments of the present application.

[0062] Figure 7 A three-dimensional electrical impedance flow diagram is provided for the embodiments of the present application. DETAILED DESCRIPTION

[0063] In order to make those skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application.

[0064] In some of the flowcharts described in the specification and claims of the present application and in the above-mentioned drawings, a plurality of operations are included which occur in a particular order, but it should be clearly understood that these operations can be performed in the order in which they appear herein or in parallel, and the serial numbers of the operations, such as S101, S102, etc., are merely used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these flowcharts can include more or fewer operations, and the operations can be performed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. herein are used to distinguish different messages, devices, modules, etc., and do not represent the order of precedence, nor do "first" and "second" represent different types.

[0065] Figure 1 The three-dimensional EIT imaging device provided by the embodiment of the present application includes the following specific contents.

[0066] The electrode module includes N electrodes, N is a natural number greater than or equal to 16, and is used to be fixed on the measurement site of the subject; in an embodiment, the electrodes of the electrode module include M electrodes fixed on the measurement region of the subject in the form of an array, and N-M electrodes are 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 an embodiment, the number of the N-M electrodes fixed above the M electrode array is greater than or equal to the number of the N-M electrodes fixed below.

[0068] In an embodiment, the N-M electrode fixing region includes: a position close to the shoulder of the right subclavian fossa, a position close to the shoulder of the left subclavian fossa, the left lower abdomen, and the right lower abdomen.

[0069] In an embodiment, the measurement region includes a lung region.

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

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

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

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

[0074] 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 each of the 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 N-M electrodes, the second electrode is any one of the M electrodes, and the other electrodes include other electrodes of the N-M 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, the above process is repeated for measurement until the N-M electrodes are iterated as the first electrode. In a specific embodiment, the three-dimensional EIT imaging is performed as shown in Figure 4 As shown, the array electrodes are 16, marked with numbers 1-16, and distributed above and below the 16 array electrodes, marked as ABCD respectively. Among the four electrodes of ABCD, A is the first electrode, 1 is the second electrode among the 16 electrodes, and the voltage between the second electrode and other electrodes (except the first electrode and the second electrode, which at this time includes 2-15 and BCD electrodes) is measured through the first electrode and the second electrode. The first electrode is updated to B electrode, and the above steps are repeated until the iteration of ABCD as the first electrode is completed.

[0076] Transmission module: for transmitting 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: for receiving the data of the data processing module to display the EIT imaging result.

[0079] In a specific embodiment, on the basis of ordinary EIT, three electrodes are added above and below, of which the upper two and the lower one are used as three-lead ECG measurement, and EIT works in time. When measuring ECG, 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 above and below, of which the upper two and the lower one are used as three-lead ECG measurement, and EIT works in time. When measuring ECG, 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 further comprises an ECG measurement module, which measures ECG signal data through N-M electrodes distributed above and below the M array electrodes; the ECG signal data measured by the ECG measurement module 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, three electrode pads are connected to the corresponding interfaces of an electrocardiograph through electrode wires, ensuring firm connection without looseness or poor contact. After confirming correct electrode connection, the electrocardiograph is started to record. The electrocardiograph displays the electrocardiogram waveform on the recording paper or on the display screen. During recording, the quality of the waveform is observed to see whether there are obvious interference signals, such as baseline drift (possibly caused by patient respiratory movement or poor electrode contact), muscle interference (caused by patient muscle tension or tremor), etc. Generally, a long enough period of time needs to be recorded to obtain a complete cardiac electrical activity cycle. 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 after excitation and voltage signal acquisition through 20 electrodes are as shown in Figure 5

[0085] Figure 2 The three-dimensional EIT imaging method provided by the embodiment of the present application specifically includes:

[0086] S101: Obtain the voltage signal after the electrodes fixed on the measured part of the subject are excited;

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

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

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

[0090] In one embodiment, the construction method of the electrical conductivity distribution model adopts one or more of the following: finite element method, boundary element method.

[0091] In one embodiment, the construction process of the electrical conductivity distribution model is as follows: ​

[0092] acquiring a three-dimensional image of the region of interest;

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

[0094] calculating a matrix equation based on the corrected three-dimensional image data to obtain a conductivity distribution model.

[0095] In one embodiment, the correction is to correct a 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 comprises a noise removal module for removing noise.

[0097] In one embodiment, the noise removal module removes noise through a noise model. The noise model comprises a Gaussian noise model.

[0098] In one embodiment, the conductivity distribution model is obtained by training a neural network, the neural network comprising one or more of a convolutional neural network, a residual network, and a Transformer. The three-dimensional electrical impedance and boundary voltage of the lung image are input to the neural network to train the conductivity distribution model.

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

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

[0101] In one embodiment, the method further comprises imaging optimization, recalculating the reconstruction matrix by removing sensitivity of a non-region 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 removing sensitivity of the non-region of interest is to set the conductivity and sensitivity of the non-region of interest in the reconstruction matrix to 0.

[0103] In one embodiment, the region of interest comprises one or more of a heart region, a lung region, and a heart-lung region.

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

[0105] In one embodiment, the new imaging intelligent algorithm abandons the classical inverse problem solving method, and generates more clinically applicable and easily explained imaging based on the consensus indicators in the EIT field. Through idealized correction of training data to obtain "expected image", combined with the positive problem and noise model, the linear relationship between its and the boundary voltage is calculated to obtain the reconstruction matrix R, and the algorithm details are as follows:

[0106]

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

[0108] The above formula uses the second norm because it allows the linear expression of R and less calculation cost. Based on the above formula, we can get:

[0109]

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

[0111] Because it is assumed that the weight w of each training data set is the same, B is no longer dependent on i, and R is solved:

[0112]

[0113] R = AB -1

[0114] wherein R represents the reconstruction matrix, i and j are the rows and columns of R, and l is the element of non-j column in the derivation process, A represents the previous summation term.

[0115] In one embodiment, based on the imaging algorithm enhanced by the sensitivity constraint of the heart and lung region, the 2D imaging displays the mapping of the 3D conductivity in the tomographic plane, and the 3D imaging contains the vertical structure information, which provides the basis for the imaging of the heart and lung region. The introduction of the heart and lung region information constrains the conductivity change, reduces the calculation complexity, and improves the estimation accuracy.

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

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

[0118] The computer simulation results of the imaging algorithm based on the enhanced sensitivity constraint of the cardiorespiratory region are shown in Figure 6

[0119] S104: 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 N-M electrodes fixed above the number of M electrode arrays equal to the number below, the mapping of three-dimensional conductivity in the two-dimensional image of the three-dimensional EIT image is obtained by one electrode distributed on one side to get the occurrence position of impedance change in three-dimensional space; the occurrence position includes above the mapping plane of two-dimensional imaging and below the mapping plane of two-dimensional imaging.

[0122] In one embodiment, the mapping of three-dimensional conductivity in the two-dimensional image is obtained by one electrode distributed below to get the occurrence position of impedance change in three-dimensional space.

[0123] In one embodiment, the method further comprises ECG measurement, and ECG signals are obtained by N-M electrodes.

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

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

[0126] In one embodiment, N electrodes are used to obtain EIT voltage signals and ECG signals through different time windows, three-dimensional EIT images are obtained through EIT voltage signals, and disease diagnosis is assisted based on the three-dimensional EIT images and / or ECG signals.

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

[0128] ​In one embodiment, the scheme of measuring 3D-EIT and ECG simultaneously uses three electrodes A, B, D to complete real-time three-lead ECG test while measuring 3D EIT. Since the current does not flow in a straight line, the impedance change outside the measurement plane can also be measured, but the problem is that the impedance change mapped to the measurement plane cannot be determined to be 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 C-x (x represents 1, 2,..., 16) current excitation and voltage measurement. If the impedance change occurs above the plane, C-x has no corresponding change, and it can be inferred that the impedance change occurs above the plane. As shown in Figure 7 the same line, the projection on the red plane is the same, and 2D EIT can only distinguish which line, but cannot distinguish where on the line. When the C electrode is added, the position of the impedance change can be distinguished.

[0129] In one embodiment, the current SCI literature also uses D-EIT. The simplest method is to bind 2-3 strips (each strip consists of 16 electrode arrays), but this method cannot be used in clinical practice because: when there are 16 electrodes in one layer, 16 current injections and 14 voltage measurements (non-measurement of injection electrode pairs) are required. One frame of picture is 16*14 = 208 voltage measurements. Assuming that a 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 methods to achieve 3D:

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

[0132] Advantages: simple structure. Disadvantages: the information supplemented in the middle area is not real measured information, but a model obtained from experience, and individualized measurement cannot be achieved.

[0133] Two layers of electrodes work together:

[0134] Advantages: true 3D imaging. Disadvantages: greatly increased computation, unable to process in real time. The number of images formed, two-layer electrode injection current electrode pairs, from the pseudo-3D 16 injection current, surge to the true 3D (16*16+16*2) = 288 (18 times), the number of times the measured voltage from the pseudo-3D 208 times, surge to the true 3D 16*16*15*15+208+208 = 58016, in addition, the 3D space expression hypothesis simply cut the 3D lung into 10 layers, assuming that the device hardware processing capacity does not change, the imaging speed will change from the original 20 frames per second to 0.007 frames per second (142 seconds per frame) Imaging speed is equivalent to 1 / 2840 of the existing, unable to capture the dynamics of respiration and perfusion.

[0135] In one embodiment, ECG information can help EIT blood flow information, and adding three-lead ECG ABD three electrodes on a 16-electrode array can greatly improve the spatial resolution based on simple 3D EIT.

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

[0137] In one embodiment, 2D EIT or 3D EIT can be used alone for one or more of the following, but not limited to: 1. Intensive care / emergency - respiratory support mode selection, ventilator mode selection, sputum suction, prone position, etc. Effect of ventilation, ventilator parameter adjustment, off-line, evaluation of regional lung perfusion information. Solve the pain point - reduce mortality, improve prognosis (confidence 90%, evidence 90%);

[0138] 2. Department of Anesthesiology - preoperative lung function assessment, anesthetic intubation, postoperative anesthetic support setting, postoperative anesthetic recovery monitoring, lung function assessment. Solve the pain point - reduce postoperative complications, improve prognosis (confidence 90% evidence 95%);

[0139] 3. Department of Respiratory Medicine - lung function test, chronic disease diagnosis and treatment, rehabilitation training. Solve the pain point - earlier detection of lesions than traditional lung function, guide lung disease treatment, judge treatment effect, guide rehabilitation training (confidence 90% evidence 80%).

[0140] 3D EIT and ECG measured in time window: in stable condition, after determining information such as QRS wave information, heartbeat variability and the like through ECG, 20-electrode 3D EIT is measured, so as to further improve 3D blood flow information based on EIT (the information of EIT only has relative change value, and the information of ECG is equivalent to providing heartbeat-related absolute value information, which is used in cooperation with the spatial information provided by EIT, so that both absolute value and spatial distribution information are obtained).

[0141] 2D EIT and ECG are collected simultaneously: when it is necessary to obtain pulsation-related signals, cooperation is required, such as calculation of changes in cardiac output (stroke volume).

[0142] 3D EIT and ECG are collected simultaneously: when it is necessary to obtain pulsation-related signals, cooperation is required, and the spatial information of 3D is taken into account, so that the application is more comprehensive.

[0143] The embodiment of the present application also provides a computer program product or system, comprising a computer program, which realizes the method steps described above when executed by a processor.

[0144] Figure 3 The three-dimensional EIT imaging system provided by the embodiment of the present application specifically comprises:

[0145] The acquisition unit acquires the voltage signal after the electrode fixed on the measured part of the person to be measured is excited;

[0146] The model unit calculates the voltage signal and obtains the conductivity distribution data in the conductivity distribution model; the conductivity distribution model is constructed by the relationship between the voltage signal and the conductivity;

[0147] The calculation unit calculates the reconstruction matrix based on the conductivity distribution data;

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

[0149] The embodiment of the present application also provides a computer readable storage medium, which stores a computer program, and the computer program realizes the three-dimensional EIT imaging method described above when executed by a processor.

[0150] The verification result of the verification embodiment shows that assigning inherent weights to the indications can improve the performance of the method compared with the default setting. It can be clearly understood by those skilled in the art that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the foregoing method embodiments, which will not be described here. In the several embodiments provided by the present 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. The division of the units is only a logical function division. There can be another division manner in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms. The units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e. can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme. In addition, each functional unit in the various embodiments of the present application can be integrated in one processing unit, or each unit can be a physically independent unit, or two or more units can be integrated in one unit. The integrated unit can be implemented in the form of hardware, or in the form of software functional units. Those skilled in the art can understand that all or part of the steps of the various methods in the above embodiments can be completed by programs instructing relevant hardware, and the programs can be stored in a computer readable storage medium, which can include read only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0151] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiment methods can be completed by programs instructing relevant hardware, and the programs can be stored in a computer readable storage medium, and the above-mentioned medium storage can be read only memory, magnetic disk or optical disk, etc.

[0152] The computer device provided by the present application has been described in detail above. For those skilled in the art, according to the idea of the embodiment of the present application, there will be changes in specific implementation and application range. In view of the above, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A three-dimensional EIT imaging device, characterized in that, include: Electrode module: consists of N electrodes, where N is a natural number greater than or equal to 16, used to fix the electrodes to the measurement site on the subject. The electrode module comprises M electrodes fixed in an array in the measurement area of ​​the subject, 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. The number of NM electrodes fixed above the M electrode array is greater than or equal to the number below it; The NM electrode fixing areas include: the right subclavian fossa near the shoulder, the left subclavian fossa near the shoulder, the left lower abdomen, and the right lower abdomen; Acquisition module: used to apply constant current excitation signals to the first and second electrodes in the electrode module and to measure the voltage signals between the other electrodes besides the first and second electrodes; Transmission module: Used to transmit voltage signals from the acquisition module; Data processing module: Receives the voltage signal from the transmission module, calculates the voltage signal and inputs it into the conductivity distribution model to obtain conductivity distribution data, calculates a reconstruction matrix based on the conductivity distribution data, and performs image reconstruction based on the reconstruction matrix; Imaging module: Used to receive the data from the data processing module and display the EIT imaging results.

2. The three-dimensional EIT imaging device according to claim 1, characterized in that, The N electrodes are 16 electrodes, M is 13 electrodes, and NM is 3 electrodes; Alternatively, the N electrodes may be 16 electrodes, M may be 12 electrodes, and NM may be 4 electrodes; Alternatively, the N electrodes may be 19 electrodes, M may be 16 electrodes, and NM may be 3 electrodes; Alternatively, N electrodes may be 20 electrodes, M may be 16 electrodes, and NM may be 4 electrodes.

3. The three-dimensional EIT imaging device according to claim 1, characterized in that, The device also includes an ECG measurement module, which measures ECG signal data using 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 via a transmission module.

4. A three-dimensional EIT imaging method, characterized in that, include: The voltage signal of the electrode fixed at the measurement site of the subject after excitation is obtained; the voltage signal is acquired by the three-dimensional EIT imaging device according to any one of claims 1-3; The voltage signal is calculated and then 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 conductivity. Calculate the reconstruction matrix based on the conductivity distribution data; A three-dimensional EIT image is obtained by reconstructing the image based on the reconstruction matrix.

5. The three-dimensional EIT imaging method according to claim 4, characterized in that, The reconstructed matrix includes two-dimensional conductivity data, three-dimensional spatial structure data, and three-dimensional conductivity data.

6. The three-dimensional EIT imaging method according to claim 4, characterized in that, The three-dimensional EIT image includes a two-dimensional EIT image and a three-dimensional EIT image.

7. The three-dimensional EIT imaging method according to claim 4, characterized in that, When the number of NM electrodes fixed above an M-electrode array is equal to the number below it, the mapping of the three-dimensional conductivity of the three-dimensional EIT image in the two-dimensional image is obtained through an electrode distributed on one side, which shows the location of the impedance change in three-dimensional space; the location includes above the mapping plane of the two-dimensional imaging and below the mapping plane of the two-dimensional imaging.

8. The three-dimensional EIT imaging method according to claim 7, characterized in that, The three-dimensional conductivity is mapped in the two-dimensional image to obtain the location of impedance change in three-dimensional space through an electrode distributed below.

9. The three-dimensional EIT imaging method according to claim 4, characterized in that, The conductivity distribution model is constructed using one or more of the following methods: finite element method and boundary element method.

10. The three-dimensional EIT imaging method according to claim 9, characterized in that, The construction process of the conductivity distribution model is as follows: Acquire a 3D image of the area to be measured; The three-dimensional image is corrected to obtain corrected three-dimensional image data; The conductivity distribution model is obtained by calculating the matrix equation based on the corrected three-dimensional image data.

11. The three-dimensional EIT imaging method according to claim 10, characterized in that, The correction is based on prior knowledge to correct regions in 3D image data to an ideal tissue distribution.

12. The three-dimensional EIT imaging method according to claim 10, characterized in that, The conductivity distribution model also includes a noise removal module for removing noise; the noise removal module removes noise through a noise model.

13. The three-dimensional EIT imaging method according to claim 4, characterized in that, The conductivity distribution model is obtained by training a neural network, which includes one or more of the following: convolutional neural network, residual network, and Transformer.

14. The three-dimensional EIT imaging method according to claim 4, characterized in that, The method also includes imaging optimization, which involves recalculating the reconstruction matrix by removing the sensitivity of non-interest regions to obtain the region of interest reconstruction matrix, and then performing image reconstruction based on the region of interest reconstruction matrix to obtain a three-dimensional EIT image.

15. The three-dimensional EIT imaging method according to claim 14, characterized in that, The sensitivity for removing non-interested regions is achieved by setting the conductivity and sensitivity of the non-interested regions in the reconstruction matrix to 0.

16. The three-dimensional EIT imaging method according to claim 14, characterized in that, The region of interest includes one or more of the following: the heart region, the lung region, and the cardiopulmonary region.

17. The three-dimensional EIT imaging method according to claim 16, characterized in that, The heart region includes the left heart region and the right heart region.

18. The three-dimensional EIT imaging method according to claim 16, characterized in that, The lung regions include the left lung region, the right lung region, the ventral region, and the dorsal region.

19. The three-dimensional EIT imaging method according to claim 4, characterized in that, A two-dimensional EIT image is obtained by EIT reconstruction using M electrodes.

20. The three-dimensional EIT imaging method according to claim 4, characterized in that, A 3D EIT image is obtained by reconstructing a 3D EIT image using N electrodes.

21. The three-dimensional EIT imaging method according to claim 4, characterized in that, The method also includes ECG measurement, where N electrodes acquire EIT voltage signals through different time windows and ECG signals are acquired through NM electrodes, and a three-dimensional EIT image is obtained from the EIT voltage signals. The three-dimensional EIT image and / or ECG signal are used to assist in disease diagnosis.

22. The three-dimensional EIT imaging method according to claim 21, characterized in that, The different time windows are as follows: when measuring ECG, NM electrodes are used to measure the ECG signal, and M electrodes are either not working or used to measure the voltage signal required for the two-dimensional EIT signal; when measuring three-dimensional EIT, N electrodes are used to measure the EIT voltage signal.

23. 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 4-22.

24. A computer-readable storage medium having a computer program or instructions 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 4-22.

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