Blood perfusion imaging method and device based on EIT equipment

Abstract

The invention relates to the technical field of image imaging, in particular to a blood perfusion imaging method and device based on EIT equipment, and the method comprises the steps: obtaining ventilation data in a monitoring period and a total impedance oscillogram corresponding to the ventilation data; selecting a first time period from the total impedance oscillogram, wherein the first time period is a time period during normal ventilation in the monitoring period; obtaining a first impedance oscillogram corresponding to the first time period and first total impedance waveform data corresponding to the first impedance oscillogram; generating a ventilation image according to the first total impedance waveform data; generating a blood perfusion impedance image according to the first total impedance waveform data and the total impedance oscillogram; and obtaining blood flow analysis data according to the ventilation image and the blood flow perfusion impedance image. According to the method, by processing the ventilation data and the total impedance oscillogram, the normal ventilation time period can be effectively recognized, the key impedance data can be extracted, then the accurate ventilation image and the blood perfusion impedance image are generated, and finally comprehensive and accurate blood flow analysis data are obtained.

Description

Technical Field

[0001] The present application relates to the field of image imaging technology, and in particular to a blood perfusion imaging method and device based on EIT equipment. Background Art

[0002] Currently, the main application of bioelectrical impedance tomography (EIT) devices in the medical field is to generate ventilation images by collecting and measuring the patient's ventilation status. However, most EIT devices on the market do not support the function of direct blood flow imaging, nor do they provide convenient ventilation and blood flow analysis functions. Only a few EIT devices can perform simultaneous blood flow analysis, which is usually achieved through the pulsation method. The principle of the pulsation method is to use frequency characteristics to extract the blood flow component from the measurement signal, while filtering out the ventilation component to generate a blood flow image. Subsequently, these blood flow images and ventilation images can be used for real-time or offline data analysis.

[0003] The existing technology has the following problems: First, if the EIT device lacks blood flow imaging function, it cannot fully utilize its potential, resulting in limited ability to accurately analyze and monitor patients; second, although some EIT devices support concentrated sodium blood flow imaging in hardware, the lack of an easy-to-use software operation interface makes it complicated to achieve accurate blood flow imaging. Users usually need to export device data and then perform offline analysis through data processing. This process is cumbersome and time-consuming, and requires users to have high software programming skills and mathematical knowledge, which greatly increases the threshold for use; finally, the pulsation method has difficulties in extracting blood flow signals, and the spectrum separation method is difficult to directly provide sufficiently accurate data. Therefore, the pulsation method can usually only be used for rough assessment of blood flow, but cannot provide accurate blood flow imaging and accurate ventilation and blood flow (VQ) analysis. Summary of the invention

[0004] An object of an embodiment of the present invention is to provide a blood perfusion imaging method and apparatus based on an EIT device, so as to solve the technical problems of equipment limitation, cumbersome operation and inaccurate detection in blood flow imaging and comprehensive analysis functions of the EIT device.

[0005] In a first aspect, an embodiment of the present invention provides a blood perfusion imaging method based on an EIT device, the method comprising:

[0006] Acquiring ventilation data within a monitoring period and a total impedance waveform graph corresponding to the ventilation data;

[0007] Selecting a first time period in the total impedance waveform diagram, the first time period being a time period of normal ventilation in the monitoring cycle;

[0008] Acquire a first impedance waveform graph corresponding to the first time period and first total impedance waveform data corresponding to the first impedance waveform graph;

[0009] generating a ventilation image according to the first total impedance waveform data;

[0010] generating a blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform graph;

[0011] Blood flow analysis data is obtained according to the ventilation image and the blood perfusion impedance image.

[0012] In a second aspect, an embodiment of the present invention provides a blood perfusion imaging device based on an EIT device, the device comprising:

[0013] An acquisition unit, used to acquire ventilation data within a monitoring period and a total impedance waveform graph corresponding to the ventilation data;

[0014] A selection unit, configured to select a first time period from the total impedance waveform diagram, wherein the first time period is a time period of normal ventilation in the monitoring cycle;

[0015] The acquisition unit is further used to acquire a first impedance waveform graph corresponding to the first time period and first total impedance waveform data corresponding to the first impedance waveform graph;

[0016] A generating unit, configured to generate a ventilation image according to the first total impedance waveform data;

[0017] The generating unit is further configured to generate a blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform diagram;

[0018] The generating unit is further used to obtain blood flow analysis data according to the ventilation image and the blood perfusion impedance image.

[0019] In a third aspect, an embodiment of the present invention provides a computer device, including:

[0020] at least one processor; and,

[0021] a memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to the first aspect.

[0023] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the method as described in the first aspect.

[0024] In the scheme implemented by the above-mentioned blood perfusion imaging method, device, equipment and storage medium based on EIT equipment, this method can more accurately reflect the patient's breathing and blood flow conditions, reduce errors, and ensure the comprehensiveness and accuracy of the data by acquiring ventilation data and the corresponding total impedance waveform within the monitoring period; selecting the first time period of normal ventilation in the total impedance waveform to ensure that the acquired data is carried out under normal breathing conditions of the patient, which helps to eliminate the interference of abnormal breathing on the data, thereby improving the reliability of the data; further acquiring the first impedance waveform and the first total impedance waveform data corresponding to the first time period, providing multi-dimensional data support, and facilitating subsequent image generation and analysis; generating ventilation images and blood perfusion impedance images based on the first total impedance waveform data, and intuitively displaying the patient's breathing and blood flow conditions in a graphical manner, which is convenient for doctors to diagnose and analyze, so this method realizes real-time monitoring and feedback of the patient's breathing and blood flow, and improves the accuracy and convenience of blood perfusion imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0026] Figure 1 It is a flow chart of a blood perfusion imaging method based on an EIT device in one embodiment of the present invention;

[0027] Figure 2 is a schematic diagram of a total impedance waveform diagram in one embodiment of the present invention;

[0028] Figure 3 It is a structural schematic diagram of a blood perfusion imaging device based on an EIT device in one embodiment of the present invention;

[0029] Figure 4 It is a schematic diagram of the structure of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0031] It should be noted that, if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, all within the scope of protection of the present invention. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order from the module division in the device or the flow chart. Furthermore, the words "first", "second", "third", etc. used in the present invention do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0032] The technical solution of the present application can be applied to software upgrade scenarios of various EIR devices.

[0033] In view of this, the present application proposes a blood perfusion imaging method based on an EIT device to solve the above problems, which is described in detail below.

[0034] See also Figure 1 , Figure 1 A flow chart of a blood perfusion imaging method based on an EIT device provided in an embodiment of the present invention includes the following steps:

[0035] S10. Acquire ventilation data within a monitoring period and a total impedance waveform graph corresponding to the ventilation data.

[0036] The monitoring period refers to the period of time during which continuous measurement and observation are performed using the EIT device, which can be a few minutes, a few hours, or even longer, depending on clinical needs and research purposes.

[0037] Among them, electrical impedance tomography (EIT) is a type of non-invasive medical imaging. The basic principle is to apply a safe excitation current (voltage) signal to the surface of the target tissue to be measured, and simultaneously measure the voltage (current) signal on the surface of the target tissue. The impedance (or impedance change) image distribution in the detected tissue is obtained by using an image reconstruction algorithm based on the measured signal.

[0038] The ventilation data includes ventilation data before high-conductivity contrast agent is injected (reflecting ventilation conditions under normal conditions) and ventilation data after high-conductivity contrast agent is injected. The ventilation data reflects the patient's breathing conditions under different conditions.

[0039] Among them, the injection of high-conductivity contrast agent reflects the lung perfusion by injecting high-conductivity contrast agent (hypertonic saline) to cause changes in chest electrical impedance. Saline injection causes a significant decrease in resistance in a certain lung area, indicating that more contrast agent flows through the area, that is, more blood perfusion; conversely, the resistance decrease is not obvious, and the blood perfusion is low.

[0040] During the EIT measurement process, the system in the EIT will collect the impedance change data of the target tissue and generate the corresponding total impedance waveform. The total impedance waveform shows the dynamic changes of the impedance of the target tissue during the monitoring period.

[0041] Among them, Figure 2 As shown in Figure 2 The total impedance waveform is shown in the figure. As shown in the figure, the left part of the waveform shows the data of the patient's normal ventilation, and the middle part shows the process of holding the breath, injecting saline, and then the impedance drops rapidly, and the impedance gradually returns to the normal level as the contrast agent diffuses.

[0042] Specifically, in Figure 2 In the figure, the horizontal axis represents time in seconds (s), ranging from 0 to 40 seconds; the vertical axis represents global resistance in AU (Arbitrary Units), ranging from 0 to 5000. Between V0 and V1, the global resistance curve shows periodic fluctuations. After V1, the curve shows a plateau period (plateau limb), and then the curve drops significantly between P0 and P1, reaching a trough. After P1, the global resistance starts to rise, forming a rising limb. Before P2, the global resistance drops again, forming a falling limb. Finally, the curve returns to a periodic fluctuation similar to that between V0 and V1.

[0043] Among them, during the EIT measurement process, a pair of electrodes are used as excitation electrodes, and the other electrodes are used as measurement electrodes. Each sampling will obtain 208 data points, and these 208 data points can be regarded as the sampling results at the current moment. In the process of recording ventilation data, 208 data points will be sampled continuously, and each 208 data points constitute a frame. The sampling process is repeated continuously, and about 20 frames of data are recorded per second, thereby forming continuous ventilation data and a total impedance waveform. That is, the EIT device obtains a total impedance value each time it samples, and multiple continuous sampling points constitute the total impedance waveform.

[0044] For example, when using the device, the patient needs to tie an electrode belt. There are 16 electrodes on the electrode belt. When the EIT device is working normally, the adjacent injection method is usually used for impedance measurement. Taking a 16-electrode cylindrical conductor as an example, first, select electrode 1 and electrode 2 as excitation, and measure the voltage between electrode 3 and electrode 4, electrode 4 and electrode 5, ..., until electrode 15 and electrode 16, and obtain 13 measurement values. Then, select electrode 2 and electrode 3 as excitation, and measure the voltage between electrode 4 and electrode 5, electrode 5 and electrode 6, ..., until electrode 16 and electrode 1, and obtain another 13 measurement values. In this way, select electrode 3 and electrode 4, electrode 4 and electrode 5, electrode 5 and electrode 6, until electrode 16 and electrode 1 as excitation, and measure the voltages of other adjacent electrode pairs, and obtain a total of 13x 16 = 208 measurement values.

[0045] It can be seen that in this embodiment, the ventilation data and the corresponding total impedance waveform diagram within the monitoring period are obtained by using the EIT technology, which can provide accurate and real-time respiratory and blood flow monitoring data for clinical practice.

[0046] S20. Select a first time period in the total impedance waveform diagram, where the first time period is a time period of normal ventilation in the monitoring cycle.

[0047] The first time period refers to the time period during which the patient is in a normal ventilation state during the monitoring cycle. During this time period, the patient's breathing is stable and regular, without any external interference or special treatment (such as contrast agent injection, etc.).

[0048] The selection process can be manual selection by the user or automatic selection. Specifically, the manual selection process is that the user can manually select the time period representing normal ventilation as the first time period based on the display of the total impedance waveform; the automatic selection process is to automatically identify and select the time period during normal ventilation through preset algorithms and rules. The automatic selection method can improve efficiency and reduce human errors.

[0049] Specifically, the impedance waveform during normal ventilation usually has a certain regularity and stability, and can be identified by the amplitude, frequency and shape of the waveform changes.

[0050] It can be seen that in this embodiment, selecting the first time period in the total impedance waveform diagram, whether manually or automatically, can provide important reference data for doctors and researchers, helping them to better understand and deal with patients' breathing and blood flow problems.

[0051] S30, obtaining a first impedance waveform graph corresponding to the first time period and first total impedance waveform data corresponding to the first impedance waveform graph.

[0052] The first impedance waveform is an impedance waveform corresponding to the first time period, and each value in the figure represents the total impedance value measured by the EIT device at a specific time point. The total impedance value reflects the overall impedance change at that time point, including the impedance change caused by ventilation and the impedance change caused by blood perfusion. The first impedance waveform is an impedance waveform of impedance change under normal ventilation.

[0053] The first total impedance waveform data is a total impedance data sequence extracted from the first impedance waveform diagram. Each data point represents the total impedance value at a specific time point, forming a total impedance waveform that changes over time. The first total impedance waveform data is the impedance change under normal ventilation state, including the impedance change caused by air entering and leaving the lungs.

[0054] Among them, Figure 2 As shown, the first time period may be the time period corresponding to V0-V1 in the figure, and the first impedance waveform diagram is the waveform diagram displayed in the time period corresponding to V0-V1.

[0055] It can be seen that, in this embodiment, obtaining the first impedance waveform graph corresponding to the first time period and the corresponding first total impedance waveform data is an important step for detailed analysis and evaluation.

[0056] S40. Generate a ventilation image according to the first total impedance waveform data.

[0057] Wherein, the ventilation image is an image during normal ventilation. The ventilation image is based on the first total impedance waveform data, and through a specific imaging algorithm, the first total impedance waveform data is converted into a visual image, reflecting the patient's breathing condition under normal ventilation. The ventilation image can intuitively display the patient's breathing pattern and ventilation status. The ventilation image usually represents the level of impedance in different colors or grayscales, thereby intuitively displaying the distribution and degree of lung ventilation.

[0058] Among them, the imaging algorithm may include but is not limited to inverse problem solving, image reconstruction and other technologies.

[0059] Among them, under normal ventilation, the patient's breathing is stable and regular, and the impedance waveform data should also reflect this regularity. The ventilation image during normal ventilation should show a smooth and regular waveform, reflecting the patient's normal breathing pattern. The image may show periodic fluctuations, representing each breathing cycle.

[0060] It can be seen that in this embodiment, generating a ventilation image based on the first total impedance waveform data is an important step in evaluating and analyzing the patient's respiratory status. The ventilation image during normal ventilation can intuitively display the patient's breathing pattern and ventilation status, providing important reference information for doctors and researchers.

[0061] S50: Generate a blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform graph.

[0062] The image generated by analyzing the first total impedance waveform data and the total impedance waveform graph using a specific algorithm is used to display the pulmonary blood perfusion situation.

[0063] Among them, the blood perfusion impedance image reflects the blood flow distribution and perfusion degree in different areas of the lungs, and usually represents the impedance changes with different colors or grayscales.

[0064] Among them, the algorithm for generating the blood perfusion impedance image may be based on the frequency characteristics, phase characteristics or amplitude characteristics of the impedance change to distinguish the impedance change caused by ventilation from the impedance change caused by blood perfusion. The algorithm may include signal processing, pattern recognition, image reconstruction and other technologies to extract blood perfusion information from the total impedance data.

[0065] Optionally, blood perfusion impedance images can be used to evaluate pulmonary blood flow distribution, detect pulmonary lesions (such as pulmonary embolism, pulmonary hemorrhage, etc.), and monitor treatment effects.

[0066] It can be seen that in this embodiment, generating a blood perfusion impedance image based on the first total impedance waveform data and the total impedance waveform diagram is an important method for evaluating and analyzing the blood perfusion state. The blood perfusion impedance image can intuitively display the intensity and periodic changes of blood perfusion, providing important reference information for doctors and researchers.

[0067] S60: Obtain blood flow analysis data according to the ventilation image and the blood perfusion impedance image.

[0068] The blood flow analysis data is the quantitative or qualitative data about the pulmonary blood flow status extracted by combining the ventilation image and the blood perfusion impedance image. The blood flow analysis data may include blood perfusion volume, blood flow distribution uniformity, blood flow change trend, etc.

[0069] Among them, blood flow analysis data can be used to evaluate the blood perfusion status of the lungs and detect lung lesions, such as pulmonary embolism, pulmonary hemorrhage, etc. It can also be used to monitor the treatment effect and guide the formulation of clinical treatment plans.

[0070] It can be seen that in this embodiment, accurate and comprehensive blood flow analysis data can be obtained based on the ventilation image and the blood perfusion impedance image. The blood flow analysis data provides comprehensive evaluation information to help doctors evaluate the patient's blood perfusion and ventilation conditions, and promptly discover and diagnose related diseases, such as pulmonary embolism, chronic obstructive pulmonary disease, etc.

[0071] By acquiring ventilation data and the corresponding total impedance waveform graph within the monitoring period, the method can more accurately reflect the patient's breathing and blood flow conditions, reduce errors, and ensure the comprehensiveness and accuracy of the data; selecting the first time period of normal ventilation in the total impedance waveform graph ensures that the acquired data is carried out under the patient's normal breathing conditions, which helps to eliminate the interference of abnormal breathing on the data, thereby improving the reliability of the data; further acquiring the first impedance waveform graph and the first total impedance waveform data corresponding to the first time period provides multi-dimensional data support, which is convenient for subsequent image generation and analysis; generating ventilation images and blood perfusion impedance images based on the first total impedance waveform data, and intuitively displaying the patient's breathing and blood flow conditions in a graphical manner, which is convenient for doctors to diagnose and analyze, so the method realizes real-time monitoring and feedback of the patient's breathing and blood flow, and improves the accuracy and convenience of blood perfusion imaging.

[0072] In one embodiment, generating a ventilation image based on the first total impedance waveform data includes: acquiring all total impedance values ​​in the first total impedance waveform data to obtain a first total impedance value, wherein the first total impedance value is the sum of all total impedance values; performing mean calculation on the first total impedance value to obtain a target mean value; performing filtering processing on the first impedance waveform to obtain a filtered second impedance waveform; performing data analysis on the second impedance waveform according to the target mean value to obtain a first peak set corresponding to the end of inspiration and a first trough set corresponding to the end of expiration; generating a ventilation image according to the first peak set and the first trough set.

[0073] The first total impedance value refers to a sum obtained by adding each total impedance value in the first total impedance waveform data.

[0074] Before calculating the first total impedance value, the raw data may be preprocessed, such as removing outliers, correcting baseline drift, etc.

[0075] The target mean is the average value obtained by dividing the first total impedance value by the number of total impedance values. The target mean helps smooth the data and reduce the impact of noise on subsequent analysis.

[0076] Optionally, in order to improve computational efficiency and reliability, the target mean can be calculated using a sliding average. The sliding average calculation formula is: mean[N] = a*mean[N-1] + (1-a)*x[n]. Where mean[N] represents the Nth sliding average value of the sequence x, and a is a number slightly less than 1, such as 0.99. x[n] represents the value of the nth data. The sliding average smoothes the random fluctuations and noise in the data by weighting the previous average and the current data point, thereby improving the reliability of the data.

[0077] The first impedance waveform is filtered to remove high-frequency noise and low-frequency drift, thereby obtaining a smoother and more accurate second impedance waveform. Common filtering methods include low-pass filtering, high-pass filtering, and band-pass filtering.

[0078] Among them, the peak refers to the local maximum value in the waveform, representing the impedance value at the end of inspiration. The trough refers to the local minimum value in the waveform, representing the impedance value at the end of expiration. Therefore, the peak in the first peak set is the peak corresponding to the end of inspiration identified in the second impedance waveform. The trough in the first trough set is the trough corresponding to the end of expiration identified in the second impedance waveform.

[0079] Among them, various algorithms can be used to accurately identify peaks and troughs, such as threshold method, peak detection algorithm, etc., to ensure the accuracy of recognition.

[0080] It can be seen that in this embodiment, by acquiring the first total impedance waveform data, calculating the total impedance value and the target mean value, performing filtering processing and data analysis, a ventilation image reflecting the ventilation condition can be accurately generated.

[0081] In one embodiment, the data analysis of the second impedance waveform is performed according to the target mean to obtain a first wave peak set corresponding to the end of inspiration and a first wave valley set corresponding to the end of expiration, including: according to a first judgment rule, traversing each second total impedance value in the second impedance waveform to obtain a first wave peak set corresponding to the end of inspiration, the first wave peak set including at least one third total impedance value, wherein the first judgment rule includes selecting a total impedance value continuously greater than the first five second total impedance values ​​and the last five second total impedance values ​​as the third total impedance value to be determined, when the third total impedance value to be determined is greater than the target mean and the last three total impedance values ​​are greater than the target mean, the third total impedance value to be determined is selected as the third total impedance value to be determined, and ... the first total impedance value to be determined is selected as the third total impedance value to be determined, when the first total impedance value to be determined is greater than the target mean and the last three total impedance values ​​are greater than the target mean, the first total impedance value to be determined is selected as the third total impedance value to be determined, and the first total impedance value to be determined is selected as the third total impedance value to be determined, When a peak-to-valley value is a trough, the third total impedance value to be determined is determined to be a third total impedance value; according to the second judgment rule, each second total impedance value in the second impedance waveform diagram is traversed to obtain a first trough set corresponding to the end of exhalation, and the first trough set corresponding to the end of exhalation includes at least one fourth total impedance value, wherein the second judgment rule includes selecting a total impedance value that is continuously smaller than the first five second total impedance values ​​and the last five second total impedance values ​​as the fourth total impedance value to be determined, and when the fourth total impedance value to be determined is smaller than the target mean and the previous peak-to-valley value is a peak, the fourth total impedance value to be determined is determined to be the fourth total impedance value.

[0082] The first judgment rule is used to determine the peak corresponding to the end of inspiration.

[0083] Specifically, traverse each second total impedance value in the second impedance waveform, that is, traverse each data point in the second impedance waveform, and check whether the current data point is larger than the five previous and five subsequent data points. If so, the point may be a peak, and check whether the point is greater than the target mean. If so, further judge whether the peak-to-valley value of the previous record is a trough. If so, determine that the current point is a peak. Record the point that meets the above first judgment rule as the third total impedance value and add it to the first peak set.

[0084] The second judgment rule is used to determine the trough corresponding to the end of exhalation.

[0085] Specifically, traverse each second total impedance value in the second impedance waveform, that is, traverse each data point in the second impedance waveform, and check whether the current data point is smaller than the five previous and five subsequent data points. If so, the point may be a trough, and check whether the point is less than the target mean. If so, further judge whether the peak-to-valley value of the previous record is a peak. If so, determine that the current point is a trough. Record the point that meets the above conditions as the fourth total impedance value and add it to the first trough set.

[0086] Furthermore, each data point in the waveform is traversed to ensure that each point is checked, and non-extreme points are filtered out by comparing the five previous and subsequent data points, ensuring that only true peaks and troughs are selected, ensuring that peaks and troughs appear alternately, and judging whether the current point meets the conditions by checking the type of the previous peak and trough value.

[0087] Optionally, other auxiliary judgment conditions may be introduced, such as a minimum time interval between a peak and a trough, to avoid misjudgment.

[0088] It can be seen that in this embodiment, the first judgment rule and the second judgment rule are used to accurately identify the peaks and troughs in the waveform diagram, thereby obtaining a set of total impedance values ​​corresponding to the end of inspiration and the end of expiration. In the specific judgment process, traversal, filtering and threshold judgment are performed to ensure the accuracy and reliability of data processing, which is suitable for the analysis and processing of various physiological signals.

[0089] In one embodiment, generating a ventilation image based on the first peak set and the first trough set includes: obtaining first ventilation data corresponding to each peak in the first peak set and second ventilation data corresponding to each trough in the first trough set; performing mean calculation on the total first ventilation data corresponding to all the peaks to obtain an end-inspiratory mean, wherein the first total ventilation data is the total value of the first ventilation data corresponding to all the peaks; performing mean calculation on the total second ventilation data corresponding to all the troughs to obtain an end-expiratory mean, wherein the second total ventilation data is the total value of the second ventilation data corresponding to all the troughs; taking the end-expiratory mean as a reference, calculating the impedance change between the first ventilation data corresponding to each peak in the first peak set and the end-expiratory mean; performing imaging processing on the impedance change according to a preset imaging algorithm to generate a ventilation image.

[0090] Among them, the first ventilation data corresponding to each peak is extracted from the first peak set, and the first ventilation data usually refers to ventilation parameters related to the peak (end of inspiration), such as lung volume, airflow, etc.

[0091] Wherein, the second ventilation data corresponding to each trough is extracted from the first trough set. The second ventilation data usually refers to the ventilation parameters related to the trough (end of exhalation).

[0092] The first ventilation data corresponding to all the peaks are added together to obtain the first ventilation total data, and the mean of the first ventilation total data is calculated to obtain the end-inspiratory mean. Therefore, the end-inspiratory mean reflects the average ventilation state at the end of inspiration.

[0093] The second ventilation data corresponding to all troughs are added together to obtain the second ventilation total data, and the mean of the second ventilation total data is calculated to obtain the end-expiratory mean value. The end-expiratory mean value reflects the average ventilation state at the end of expiration.

[0094] The process of calculating the impedance change is to calculate the difference between the first ventilation data corresponding to each peak and the end-expiratory mean. The formula is: impedance change = first ventilation data - end-expiratory mean. Therefore, the first ventilation data corresponding to each peak corresponds to an impedance change.

[0095] Among them, according to the preset imaging algorithm, a suitable image reconstruction technology is selected. Common EIT imaging algorithms include linear back projection method, Newton-Raphson method, finite element method, etc. It should be noted that before imaging, the impedance change may need to be preprocessed, such as normalization, filtering, etc., to reduce noise and interference.

[0096] Furthermore, the preprocessed impedance change is input into the imaging model, and the preset imaging algorithm is applied to calculate the impedance value of each pixel or voxel. Based on the calculated impedance value, the ventilation image is reconstructed. Different colors or gray levels in the image represent different impedance values, thereby intuitively displaying the ventilation distribution.

[0097] It can be seen that in this embodiment, by obtaining the ventilation data corresponding to the peaks and troughs, the mean values ​​at the end of inspiration and expiration are calculated, and the impedance change is calculated based on this, and finally a ventilation image is generated. That is, through precise data processing and imaging algorithms, the changes in the breathing process can be accurately and intuitively reflected.

[0098] In one embodiment, generating a blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform graph includes: acquiring a third impedance waveform graph, wherein the third impedance waveform graph is an impedance waveform graph other than the first impedance waveform graph in the total impedance waveform graph; filtering the third impedance waveform graph to obtain a filtered fourth impedance waveform graph; traversing each fifth total impedance value in the fourth impedance waveform graph according to a first judgment rule and a second judgment rule to obtain a second peak set corresponding to an end of inspiration and a second trough set corresponding to an end of expiration, wherein the first judgment rule is used to obtain the second peak set, and the second judgment rule is used to obtain the second trough set; determining a first target point and a second target point according to the first total impedance waveform data, the second peak set, and the second trough set, wherein the first target point represents a point after breath holding and before the second target point, and the second target point is a point corresponding to the impedance minimum value in the fourth impedance waveform graph; generating a blood perfusion impedance image according to the impedance change between the first target point and the second target point.

[0099] The third impedance waveform is the remaining part of the total impedance waveform after removing the first impedance waveform. The third impedance waveform may include but is not limited to impedance changes in normal breathing, breath holding state, and impedance waveform after contrast agent injection.

[0100] Among them, after the injection of contrast agent, the conductivity of blood may increase, resulting in a decrease in impedance value. This change can be observed on the impedance waveform graph, usually manifested as a sudden drop or change in the waveform, such as Figure 2 shown.

[0101] Among them, filtering is used to remove noise and unnecessary frequency components to obtain a clearer impedance waveform. Various filters can be used for filtering, such as low-pass filters, high-pass filters or band-pass filters, and the specific selection depends on the signal characteristics and noise type. Therefore, the fourth impedance waveform is the third impedance waveform after filtering, at which time the noise is removed and the signal is smoother.

[0102] The fifth total impedance value is the total impedance value of each data point in the fourth impedance waveform diagram.

[0103] Among them, the first judgment rule is used to identify the second peak set, that is, the peak at the end of inspiration. The first judgment rule is consistent with the first judgment rule in the above embodiment and is not repeatedly limited here.

[0104] The second judgment rule is used to identify the second trough set, that is, the trough at the end of exhalation. The second judgment rule is consistent with the second judgment rule in the above embodiment and is not repeatedly defined here.

[0105] The first target point may be a reference point, which is a certain moment before contrast agent injection; the second target point may be an imaging target point, which is a moment when the minimum impedance value is selected between the reference point and the start of impedance recovery.

[0106] Among them, impedance changes can reflect blood flow and tissue perfusion.

[0107] It can be seen that in this embodiment, specific parts are extracted and processed from the total impedance waveform, key peaks and troughs are identified, target points are determined, and blood perfusion images are generated according to impedance changes, which further improves the accuracy and automation of generating blood perfusion impedance images.

[0108] In one embodiment, the determining of the first target point and the second target point according to the first total impedance waveform data, the second peak set and the second trough set includes: acquiring a first peak set and a first trough set obtained from the first total impedance waveform data, wherein the first peak set includes a plurality of peaks, each of which represents the end of inspiration, and the first trough set includes a plurality of troughs, each of which represents the end of exhalation; performing data processing on the first peak set and the first trough set to obtain a first respiratory parameter for each breath, wherein the first respiratory parameter includes a first respiratory frequency and a first respiratory amplitude; performing data processing on the second peak set and the second ... first peak set and the second trough set to obtain a first respiratory parameter for each breath, wherein the first respiratory parameter includes a first respiratory frequency and a first respiratory amplitude; performing data processing on the first peak set and the second trough set to obtain a first respiratory parameter for each breath, wherein the first respiratory parameter includes a first respiratory frequency and a first respiratory amplitude; Data processing is performed to obtain a second breathing parameter for each breath, wherein the second breathing parameter includes a second breathing frequency and a second breathing amplitude; the second breathing parameter for each breath is compared with the first breathing parameter to obtain a first target breathing point that complies with the breath-holding rule, wherein the compliance with the breath-holding rule is that the frequency difference between any of the second breathing frequencies and the first breathing frequency is lower than a preset frequency threshold, and the impedance amplitude between any of the second breathing amplitude and the first breathing amplitude is lower than a preset impedance amplitude threshold; data processing is performed on the fourth impedance waveform to obtain a second target breathing point; and a first target point and a second target point are obtained based on the first target breathing point and the second target breathing point.

[0109] Among them, in the process of obtaining the first peak set and the first trough set obtained from the first total impedance waveform data, it is consistent with the process of the above-mentioned embodiment of "performing data analysis on the second impedance waveform according to the target mean to obtain the first peak set corresponding to the end of inspiration and the first trough set corresponding to the end of exhalation", and will not be repeated here.

[0110] The first respiratory frequency is the number of breaths per minute, the first respiratory amplitude is the impedance change amplitude between the end of inspiration and the end of expiration, the second respiratory frequency is the number of breaths per minute, and the second respiratory amplitude is the impedance change amplitude between the end of inspiration and the end of expiration.

[0111] Among them, the respiratory rate meter converts the time interval between adjacent peaks or troughs into the number of times per minute; the respiratory amplitude is obtained by calculating the impedance difference between adjacent peaks and troughs.

[0112] Among them, the preset frequency threshold and the preset impedance amplitude threshold are set according to clinical experience or experimental data, and are used to determine whether the breath-holding rules are met.

[0113] Among them, the breath-holding rule is used to detect whether the patient holds his breath during the measurement process; the breath-holding rule is used to determine the rule for the first target breathing point, requiring that the difference between the second breathing frequency and the first breathing frequency is lower than the preset frequency threshold, and the difference between the second breathing amplitude and the first breathing amplitude is lower than the preset impedance amplitude threshold.

[0114] For example, if a breathing starts, the frequency is much lower than the normal breathing frequency (such as less than 10%), and the respiratory impedance amplitude is much smaller than the normal respiratory impedance amplitude (such as less than 10%), then the area is determined to be the time period for the start of breath holding.

[0115] It can be seen that in this embodiment, the impedance waveform data is used to identify the key moments in the respiratory cycle, calculate the respiratory parameters, and compare them to determine the target respiratory points that meet the breath-holding rules. Finally, through data processing and comparison, the first target point and the second target point are obtained, which improves the accuracy and intelligence of subsequent imaging.

[0116] In one embodiment, obtaining the first target point and the second target point based on the first target breathing point and the second target breathing point includes: selecting either the first target breathing point and the second target breathing point to obtain the first target point; in the fourth impedance waveform graph, traversing the impedance waveform graph after the first target point to determine the second target point, the second target point being the point corresponding to the minimum impedance value in the impedance waveform graph after the first target point.

[0117] Starting from the first target point, the subsequent impedance waveform data is traversed, and during the traversal process, the point corresponding to the minimum impedance value is found, that is, the second target point. Figure 2 In the figure, P2 is the second target point, and P0 or P1 is the first target point.

[0118] Optionally, a linear traversal or other optimized traversal algorithm may be used to ensure that the exact minimum point is found.

[0119] In a specific implementation, the first-order derivative of the ventilation data corresponding to the fourth impedance waveform is calculated, and the "inflection point" of the impedance waveform is found according to the change of the first-order derivative, that is, the moment when the contrast agent injection begins. If the absolute values ​​of three consecutive first-order derivatives are significantly greater than the first-order derivative in the breath-holding stage, and the first-order derivative is negative, then this moment is determined to be the "inflection point"; any point between the start of breath-holding and the "inflection point" is selected as the reference point; continue to traverse the subsequent waveforms (that is, the impedance waveform after traversing the first target point), and the moment when the impedance begins to recover can be calculated according to the value of the impedance. The moment when the impedance is the minimum between the reference point and the beginning of the impedance recovery is selected, and this moment is used as the imaging target point.

[0120] Among them, the first-order derivative can be calculated by numerical differentiation methods, such as the difference method.

[0121] It can be seen that the present embodiment can accurately identify the key physiological moments of respiratory and blood flow changes, thereby improving the generation quality of blood perfusion impedance images. At the same time, by automatically identifying the minimum impedance value, the data processing efficiency is optimized, manual intervention is reduced, and faster and more accurate measurement and analysis can be achieved.

[0122] In one embodiment, the method of generating a blood perfusion impedance image based on the impedance change between the first target point and the second target point includes: processing the impedance change between the first target point and the second target point according to a preset imaging algorithm to obtain an impedance change image of the blood flow; acquiring a set of peak positions in the impedance change image of the blood flow, the peak position set including at least one peak position; determining whether the peak positions in the peak position set are within a preset heart prior position range; if not, determining that the impedance change image of the blood flow is a blood perfusion impedance image; or, if yes, performing cardiac artifact removal processing on the impedance change image of the blood flow to obtain a blood perfusion impedance image.

[0123] Among them, the preset imaging algorithm is consistent with the preset imaging algorithm mentioned above, such as Fourier transform, filtering, interpolation and other imaging algorithms, and will not be repeated here.

[0124] In the impedance change image of the blood flow, all peak positions are found, and the peak positions reflect the maximum value points of the impedance, thereby obtaining a peak position set.

[0125] Among them, the method for obtaining the peak position is to use a peak detection algorithm, local extreme value detection, or image processing technology, such as edge detection, peak detection, etc., to automatically identify and extract the peak position in the image.

[0126] In a specific implementation, in the process of determining whether the peak position in the peak position set is located within a preset heart priori position range, each extracted peak position is compared with the preset heart priori position range to perform determination.

[0127] The heart prior position range is determined based on physiological knowledge and prior data, and represents the area where the heart may appear in the image.

[0128] Specifically, if the peak position is not within the heart a priori position range, it means that these peaks are mainly caused by blood flow rather than heart activity. In this case, the blood flow impedance change image can be directly determined as a blood flow perfusion impedance image.

[0129] Specifically, if the peak positions are within the heart a priori position range, it means that these peaks may be affected by cardiac activity, forming artifacts. At this time, the image needs to be further processed to remove these cardiac artifacts.

[0130] Among them, the removal of cardiac artifacts uses specific image processing techniques, such as filtering, masking, etc., to suppress or eliminate the impact of cardiac activity on the blood flow impedance change image, thereby obtaining a more accurate blood flow perfusion impedance image.

[0131] It can be seen that in this embodiment, by judging whether the peak position is within the preset heart prior position range, the impedance changes related to the heart can be effectively distinguished. If the peak position is within the heart prior position range, the heart artifact removal processing is performed to ensure that the final blood perfusion impedance image is not interfered by heart artifacts, thereby improving the accuracy and reliability of the image.

[0132] In one embodiment, the root performs cardiac artifact removal processing on the impedance change image of the blood flow to obtain a blood perfusion impedance image, including: performing partial differential processing on each pixel point in the impedance change image of the blood flow to obtain a first partial differential and a second partial differential corresponding to each pixel point; performing gradient calculation on the first partial differential and the second partial differential corresponding to each pixel point to obtain an impedance gradient of each pixel point and a gradient direction corresponding to the impedance gradient; traversing an area corresponding to each peak position in the peak position set to obtain at least one pixel point to be confirmed, and the gradient direction corresponding to the pixel point to be confirmed is the same as the gradient direction corresponding to the peak position. The angle between the value directions is greater than a preset angle; among the at least one pixel point to be confirmed, the pixel point to be confirmed that is shortest to the peak position in the peak position set is selected as the target pixel point; with the distance between the target pixel point and the peak position in the peak position set as the radius, and the peak position in the peak position set as the center of the circle, a heart area to be processed is obtained, and the heart area to be processed is located in the impedance change image of the blood flow; the impedance change amount of all pixels in the heart area to be processed is set to 0, and a blood perfusion impedance image is obtained, and the blood perfusion impedance image is the impedance change image of the blood flow after the heart area to be processed is removed.

[0133] Among them, the purpose of partial differential processing is to calculate the local change rate of the pixel in the image. Partial differential refers to the derivative calculation of the impedance value of each pixel in the impedance change image of blood flow. The first partial differential usually represents the rate of change in a certain direction (such as the x direction), and the second partial differential represents the rate of change in another direction (such as the y direction). Numerical differential methods, such as the finite difference method, are usually used to approximate the partial differential.

[0134] The gradient indicates the degree and direction of change of a point in the image, and the gradient direction indicates the direction of the most dramatic change. That is, the impedance gradient (i.e., change intensity) and gradient direction (i.e., change direction) of each pixel are calculated using the first partial differential and second partial differential of the pixel.

[0135] Among them, in the traversal process, those pixels whose angle between the gradient direction and the peak direction corresponding to the peak position is greater than the preset angle are found as the pixels to be determined. The pixels to be determined may be points affected by cardiac artifacts. The angle between the gradient direction of the pixel to be confirmed and the peak direction of the peak position is greater than the preset angle.

[0136] The preset angle can be determined based on physiological knowledge and actual data to effectively distinguish cardiac artifacts from real blood flow signals. The preset angle can be 90° or other angles, which are not limited here.

[0137] Among the pixels to be confirmed, the point with the shortest distance to the peak position in the peak position set is selected as the target pixel, which is considered to be the point most directly affected by the cardiac artifact.

[0138] The heart region to be processed may be a circular region, which is formed by the distance between the target pixel and the peak position as the radius and the peak position as the center. The heart region to be processed is located in the blood flow impedance change image and is considered to be an area affected by cardiac artifacts.

[0139] The impedance variation of all pixels in the heart region to be processed is set to 0, thereby eliminating the influence of heart artifacts on the image.

[0140] For example, if the peak of the impedance change image of blood flow is located within the a priori position of the heart, the partial differentials of the impedance in the x-axis and y-axis directions in the image are calculated respectively. Based on these two partial differentials, the gradient of impedance in each pixel can be calculated. If the angle between the gradient direction and the peak direction is less than 90°, it means that the pixel is close to the peak and the impedance is rising; if the angle between the gradient direction and the peak direction is ≥90°, it means that the pixel is far away from the peak and the impedance is rising. Traverse the area around the peak, find the position closest to the peak, where the angle between the gradient direction and the peak direction is ≥90°, and calculate the distance r between this position and the peak point. With the peak point as the center and r as the radius, set it as the heart area, record the impedance change in this area as 0, and obtain the blood perfusion impedance image.

[0141] It can be seen that in this embodiment, by removing the cardiac artifacts, a blood perfusion impedance image with the cardiac artifacts removed is obtained. The image more accurately reflects the impedance changes caused by the blood flow, thereby improving the accuracy and intelligence of the imaging.

[0142] It should be noted that in each of the above-mentioned embodiments, there is not necessarily a certain order between the above-mentioned steps. A person of ordinary skill in the art can understand, based on the description of the embodiments of the present application, that in different embodiments, the above-mentioned steps may have different execution orders, that is, they may be executed in parallel, may be executed interchangeably, and so on.

[0143] As another aspect of the embodiment of the present application, the embodiment of the present application provides a blood perfusion imaging device based on an EIT device. The blood perfusion imaging device based on the EIT device can be a software module, and the software module includes a plurality of instructions, which are stored in a memory, and the processor can access the memory and call the instructions for execution to complete the blood perfusion imaging method based on the EIT device described in the above-mentioned various embodiments.

[0144] See also Figure 3 , Figure 3Schematic diagram of the structure of a blood perfusion imaging device based on an EIT device provided in an embodiment of the present application. Figure 3 As shown, the blood perfusion imaging device 300 based on the EIT device includes:

[0145] An acquisition unit 301 is used to acquire ventilation data within a monitoring period and a total impedance waveform corresponding to the ventilation data;

[0146] A selection unit 302 is used to select a first time period in the total impedance waveform diagram, where the first time period is a time period of normal ventilation in the monitoring cycle;

[0147] The acquisition unit 301 is further configured to acquire a first impedance waveform graph corresponding to the first time period and first total impedance waveform data corresponding to the first impedance waveform graph;

[0148] A generating unit 303, configured to generate a ventilation image according to the first total impedance waveform data;

[0149] The generating unit 303 is further configured to generate a blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform diagram;

[0150] The generating unit 303 is further configured to obtain blood flow analysis data according to the ventilation image and the blood perfusion impedance image.

[0151] By acquiring ventilation data and the corresponding total impedance waveform graph within the monitoring period, the method can more accurately reflect the patient's breathing and blood flow conditions, reduce errors, and ensure the comprehensiveness and accuracy of the data; selecting the first time period of normal ventilation in the total impedance waveform graph ensures that the acquired data is carried out under the patient's normal breathing conditions, which helps to eliminate the interference of abnormal breathing on the data, thereby improving the reliability of the data; further acquiring the first impedance waveform graph and the first total impedance waveform data corresponding to the first time period provides multi-dimensional data support, which is convenient for subsequent image generation and analysis; generating ventilation images and blood perfusion impedance images based on the first total impedance waveform data, and intuitively displaying the patient's breathing and blood flow conditions in a graphical manner, which is convenient for doctors to diagnose and analyze, so the method realizes real-time monitoring and feedback of the patient's breathing and blood flow, and improves the accuracy and convenience of blood perfusion imaging.

[0152] In one embodiment, in generating a ventilation image according to the first total impedance waveform data, the generating unit 303 is further used to: obtain all total impedance values ​​in the first total impedance waveform data to obtain a first total impedance value, wherein the first total impedance value is the sum of all total impedance values; perform mean calculation on the first total impedance value to obtain a target mean value; perform filtering processing on the first impedance waveform to obtain a filtered second impedance waveform; perform data analysis on the second impedance waveform according to the target mean value to obtain a first peak set corresponding to the end of inspiration and a first trough set corresponding to the end of expiration; and generate a ventilation image according to the first peak set and the first trough set.

[0153] In one embodiment, in the step of performing data analysis on the second impedance waveform according to the target mean to obtain a first wave peak set corresponding to the end of inspiration and a first wave valley set corresponding to the end of expiration, the generation unit 303 is further used to: according to a first judgment rule, traverse each second total impedance value in the second impedance waveform to obtain a first wave peak set corresponding to the end of inspiration, wherein the first wave peak set includes at least one third total impedance value, wherein the first judgment rule includes selecting a total impedance value that is continuously greater than the first five second total impedance values ​​and the last five second total impedance values ​​as the third total impedance value to be determined, and when the third total impedance value to be determined is greater than the target The third total impedance value to be determined is the third total impedance value when the last peak-to-valley value is a trough, and the third total impedance value to be determined is determined to be the third total impedance value; according to the second judgment rule, each second total impedance value in the second impedance waveform is traversed to obtain the first trough set corresponding to the end of exhalation, and the first trough set corresponding to the end of exhalation includes at least one fourth total impedance value, wherein the second judgment rule includes selecting a total impedance value that is continuously smaller than the first five second total impedance values ​​and the last five second total impedance values ​​as the fourth total impedance value to be determined, and when the fourth total impedance value to be determined is smaller than the target mean and the last peak-to-valley value is a peak, determining the fourth total impedance value to be determined is the fourth total impedance value.

[0154] In one embodiment, in generating a ventilation image according to the first wave peak set and the first wave trough set, the generating unit 303 is further used to: obtain first ventilation data corresponding to each wave peak in the first wave peak set and second ventilation data corresponding to each wave trough in the first wave trough set; average the first ventilation total data corresponding to all wave peaks to obtain an end-inspiratory mean, wherein the first ventilation total data is the total value of the first ventilation data corresponding to all the wave peaks; average the second ventilation total data corresponding to all the wave troughs to obtain an end-expiratory mean, wherein the second ventilation total data is the total value of the second ventilation data corresponding to all the wave troughs; calculate the impedance change between the first ventilation data corresponding to each wave peak in the first wave peak set and the end-expiratory mean with the end-expiratory mean as a reference; and perform imaging processing on the impedance change according to a preset imaging algorithm to generate a ventilation image.

[0155] In one embodiment, in the generation of the blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform graph, the generation unit 303 is further used to: obtain a third impedance waveform graph, the third impedance waveform graph being an impedance waveform graph other than the first impedance waveform graph in the total impedance waveform graph; filter the third impedance waveform graph to obtain a filtered fourth impedance waveform graph; traverse each fifth total impedance value in the fourth impedance waveform graph according to a first judgment rule and a second judgment rule to obtain a second peak set corresponding to the end of inspiration and a second trough set corresponding to the end of expiration, the first judgment rule being used to obtain the second peak set, and the second judgment rule being used to obtain the second trough set; determine a first target point and a second target point according to the first total impedance waveform data, the second peak set, and the second trough set, the first target point representing a point after breath holding and before the second target point, and the second target point being a point corresponding to the impedance minimum value in the fourth impedance waveform graph; and generate the blood perfusion impedance image according to the impedance change between the first target point and the second target point.

[0156] In one embodiment, in the determination of the first target point and the second target point based on the first total impedance waveform data, the second peak set and the second trough set, the generation unit 303 is further used to: obtain a first peak set and a first trough set obtained from the first total impedance waveform data, the first peak set including a plurality of peaks, each of which represents the end of inspiration, and the first trough set including a plurality of troughs, each of which represents the end of expiration; perform data processing on the first peak set and the first trough set to obtain a first respiratory parameter for each breath, the first respiratory parameter including a first respiratory frequency and a first respiratory amplitude; perform data processing on the second peak set and the second trough set to obtain a first respiratory parameter for each breath, the first respiratory parameter including a first respiratory frequency and a first respiratory amplitude; perform data processing on the second peak set and the second The trough set is subjected to data processing to obtain a second breathing parameter for each breath, wherein the second breathing parameter includes a second breathing frequency and a second breathing amplitude; the second breathing parameter for each breath is compared with the first breathing parameter to obtain a first target breathing point that complies with the breath-holding rule, wherein the compliance with the breath-holding rule is that the frequency difference between any of the second breathing frequencies and the first breathing frequency is lower than a preset frequency threshold, and the impedance amplitude between any of the second breathing amplitude and the first breathing amplitude is lower than a preset impedance amplitude threshold; the fourth impedance waveform is subjected to data processing to obtain a second target breathing point; and a first target point and a second target point are obtained according to the first target breathing point and the second target breathing point.

[0157] In one embodiment, in obtaining the first target point and the second target point according to the first target breathing point and the second target breathing point, the generating unit 303 is further used to: select between the first target breathing point and the second target breathing point to obtain the first target point; in the fourth impedance waveform graph, traverse the impedance waveform graph after the first target point to determine the second target point, the second target point being the point corresponding to the minimum impedance value in the impedance waveform graph after the first target point.

[0158] In one embodiment, in generating a blood perfusion impedance image according to the impedance change between the first target point and the second target point, the generating unit 303 is further used to: process the impedance change between the first target point and the second target point according to a preset imaging algorithm to obtain an impedance change image of the blood flow; obtain a set of peak positions in the impedance change image of the blood flow, the peak position set including at least one peak position to determine whether the peak positions in the peak position set are located in a preset heart prior position range; if not, determine that the impedance change image of the blood flow is a blood perfusion impedance image; or, if yes, perform cardiac artifact removal processing on the impedance change image of the blood flow to obtain a blood perfusion impedance image.

[0159] In one embodiment, in the blood flow impedance change image subjected to cardiac artifact removal processing to obtain a blood flow perfusion impedance image, the generating unit 303 is further used to: perform partial differential processing on each pixel point in the blood flow impedance change image to obtain a first partial differential and a second partial differential corresponding to each pixel point; perform gradient calculation on the first partial differential and the second partial differential corresponding to each pixel point to obtain an impedance gradient of each pixel point and a gradient direction corresponding to the impedance gradient; traverse the area corresponding to each peak position in the peak position set to obtain at least one pixel point to be confirmed, and the gradient direction corresponding to the pixel point to be confirmed is the same as the peak position. The angle between the peak directions corresponding to the positions is greater than a preset angle; among the at least one pixel point to be confirmed, the pixel point to be confirmed that is shortest to the peak position in the peak position set is selected as the target pixel point, with the distance between the target pixel point and the peak position in the peak position set as the radius, and the peak position in the peak position set as the center of the circle, to obtain the heart area to be processed, and the heart area to be processed is located in the impedance change image of the blood flow; the impedance change amount of all pixels in the heart area to be processed is set to 0, to obtain a blood perfusion impedance image, and the blood perfusion impedance image is the impedance change image of the blood flow after the heart area to be processed is removed.

[0160] It should be noted that the above-mentioned blood perfusion imaging device based on the EIT device can execute the blood perfusion imaging method based on the EIT device provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in the embodiment of the blood perfusion imaging device based on the EIT device, please refer to the blood perfusion imaging method based on the EIT device provided in the embodiment of the present application.

[0161] See also Figure 4 , Figure 4 4 is a schematic diagram of a computer device provided in an embodiment of the present application. The computer device includes one or more processors 41 and a memory 42. The memory 42 is connected to the one or more processors 41, for example, connected to the processor 41 via a bus.

[0162] The processor 41 is configured to support the computer device to perform the corresponding functions in the method in the above method embodiment. The processor 41 can be a central processing unit (CPU), a network processor (NP), a hardware chip or any combination thereof. The above hardware chip can be an application specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The above PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0163] The memory 42 is used to store program codes, etc. The memory 42 may include a volatile memory (VM), such as a random access memory (RAM); the memory 42 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD); the memory 42 may also include a combination of the above-mentioned types of memories.

[0164] The memory 42 may be used to store non-volatile software programs, non-volatile computer executable programs and modules, such as program instructions / modules corresponding to the blood perfusion imaging method based on the EIT device in the embodiment of the present application. The processor 41 executes the various functional applications and data processing of the blood perfusion imaging method based on the EIT device and the blood perfusion imaging device based on the EIT device by running the non-volatile software programs, instructions and modules stored in the memory 42, that is, to realize the functions of the various modules or units of the blood perfusion imaging method based on the EIT device and the blood perfusion imaging device based on the EIT device provided in the above method embodiment.

[0165] The memory 42 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required by at least one function. The data storage area may store data created according to the use of the blood perfusion imaging device based on the EIT device, etc. In some embodiments, the memory 42 may optionally include a memory 42 remotely arranged relative to the processor 41, and these remote memories 42 may be connected to the blood perfusion imaging device based on the EIT device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0166] The one or more modules are stored in the memory 42, and when executed by the one or more processors 41, the blood perfusion imaging method based on the EIT device in any of the above method embodiments is executed, for example, the method steps described in the above method embodiments are executed to realize the functions of the modules described in the above device embodiments.

[0167] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method described in the above embodiment.

[0168] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0169] The above disclosure is only the preferred embodiment of the present application, which certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A blood perfusion imaging method based on EIT equipment, characterized in that: include: Acquiring ventilation data within a monitoring period and a total impedance waveform graph corresponding to the ventilation data; Selecting a first time period in the total impedance waveform diagram, the first time period being a time period of normal ventilation in the monitoring cycle; Acquire a first impedance waveform graph corresponding to the first time period and first total impedance waveform data corresponding to the first impedance waveform graph; generating a ventilation image according to the first total impedance waveform data; generating a blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform graph; Blood flow analysis data is obtained according to the ventilation image and the blood perfusion impedance image.

2. The method according to claim 1, characterized in that: Generating a ventilation image according to the first total impedance waveform data includes: Acquire all total impedance values ​​in the first total impedance waveform data to obtain a first total impedance value, where the first total impedance value is the sum of all the total impedance values; Calculating the mean of the first total impedance value to obtain a target mean; Performing filtering on the first impedance waveform to obtain a filtered second impedance waveform; According to the target mean, performing data analysis on the second impedance waveform to obtain a first wave peak set corresponding to the end of inspiration and a first wave trough set corresponding to the end of expiration; A ventilation image is generated according to the first wave peak set and the first wave trough set.

3. The method according to claim 2, characterized in that The step of performing data analysis on the second impedance waveform diagram according to the target mean value to obtain a first wave peak set corresponding to the end of inspiration and a first wave trough set corresponding to the end of expiration includes: According to the first judgment rule, each second total impedance value in the second impedance waveform is traversed to obtain a first wave peak set corresponding to the end of inspiration, wherein the first wave peak set includes at least one third total impedance value, wherein the first judgment rule includes selecting a total impedance value that is continuously greater than the first five second total impedance values ​​and the last five second total impedance values ​​as the third total impedance value to be determined, and when the third total impedance value to be determined is greater than the target mean value and the previous peak-to-valley value is a trough, determining the third total impedance value to be determined to be the third total impedance value; According to the second judgment rule, each second total impedance value in the second impedance waveform diagram is traversed to obtain a first trough set corresponding to the end of exhalation, wherein the first trough set corresponding to the end of exhalation includes at least one fourth total impedance value, wherein the second judgment rule includes selecting a total impedance value that is continuously smaller than the first five second total impedance values ​​and the last five second total impedance values ​​as the fourth total impedance value to be determined, and when the fourth total impedance value to be determined is smaller than the target mean value and the previous peak-to-trough value is the peak, determining the fourth total impedance value to be determined as the fourth total impedance value.

4. The method according to claim 2, characterized in that: Generating a ventilation image according to the first wave peak set and the first wave trough set includes: Acquire first ventilation data corresponding to each peak in the first peak set and second ventilation data corresponding to each trough in the first trough set; Calculate the mean of the first ventilation total data corresponding to all the peaks to obtain the end-inspiratory mean, wherein the first ventilation total data is the total value of the first ventilation data corresponding to all the peaks; Calculate the mean of the second ventilation total data corresponding to all the troughs to obtain the end-expiratory mean, wherein the second ventilation total data is the total value of the second ventilation data corresponding to all the troughs; Taking the end-expiratory mean as a reference benchmark, calculating the impedance change between the first ventilation data corresponding to each peak in the first peak set and the end-expiratory mean; According to a preset imaging algorithm, the impedance change is imaged to generate a ventilation image.

5. The method according to claim 1, characterized in that Generating a blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform graph includes: Acquire a third impedance waveform graph, wherein the third impedance waveform graph is an impedance waveform graph other than the first impedance waveform graph in the total impedance waveform graph; Performing filtering on the third impedance waveform to obtain a filtered fourth impedance waveform; According to the first judgment rule and the second judgment rule, traverse each fifth total impedance value in the fourth impedance waveform diagram to obtain a second wave peak set corresponding to the end of inspiration and a second wave trough set corresponding to the end of expiration, wherein the first judgment rule is used to obtain the second wave peak set, and the second judgment rule is used to obtain the second wave trough set; Determine a first target point and a second target point according to the first total impedance waveform data, the second peak set and the second trough set, wherein the first target point represents a point after breath holding and before the second target point, and the second target point is a point corresponding to the minimum impedance value in the fourth impedance waveform diagram; A blood perfusion impedance image is generated according to the impedance change between the first target point and the second target point.

6. The method according to claim 5, characterized in that The determining of the first target point and the second target point according to the first total impedance waveform data, the second wave peak set and the second wave valley set comprises: Acquire a first wave peak set and a first wave trough set obtained from the first total impedance waveform data, wherein the first wave peak set includes a plurality of wave peaks, each wave peak represents the end moment of inspiration, and the first wave trough set includes a plurality of wave troughs, each wave trough represents the end moment of expiration; Performing data processing on the first wave peak set and the first wave trough set to obtain a first breathing parameter for each breath, wherein the first breathing parameter includes a first breathing frequency and a first breathing amplitude; Performing data processing on the second wave peak set and the second wave trough set to obtain a second respiratory parameter for each breath, wherein the second respiratory parameter includes a second respiratory frequency and a second respiratory amplitude; Comparing the second breathing parameter of each breath with the first breathing parameter to obtain a first target breathing point that complies with a breath-holding rule, wherein the breath-holding rule is that a frequency difference between any of the second breathing frequencies and the first breathing frequency is lower than a preset frequency threshold, and an impedance amplitude between any of the second breathing amplitudes and the first breathing amplitude is lower than a preset impedance amplitude threshold; Performing data processing on the fourth impedance waveform diagram to obtain a second target breathing point; A first target point and a second target point are obtained according to the first target breathing point and the second target breathing point.

7. The method according to claim 6, characterized in that The obtaining of a first target point and a second target point according to the first target breathing point and the second target breathing point includes: Select any one of the first target breathing point and the second target breathing point to obtain a first target point; In the fourth impedance waveform diagram, the impedance waveform diagram after the first target point is traversed to determine a second target point, where the second target point is a point corresponding to the minimum impedance value in the impedance waveform diagram after the first target point.

8. The method according to claim 5, characterized in that Generating a blood perfusion impedance image according to the impedance change between the first target point and the second target point includes: According to a preset imaging algorithm, the impedance change between the first target point and the second target point is processed to obtain an impedance change image of the blood flow; Acquire a peak position set in the impedance change image of the blood flow, wherein the peak position set includes at least one peak position; Determining whether the peak position in the peak position set is within a preset heart priori position range; If not, then determining the blood flow impedance change image as a blood flow perfusion impedance image; or, If it is located, the blood flow impedance change image is processed to remove cardiac artifacts to obtain a blood flow perfusion impedance image.

9. The method according to claim 8, characterized in that The step of removing cardiac artifacts from the blood flow impedance change image to obtain a blood flow perfusion impedance image includes: Performing partial differential processing on each pixel point in the blood flow impedance change image to obtain a first partial differential and a second partial differential corresponding to each pixel point; Performing gradient calculation on the first partial differential and the second partial differential corresponding to each pixel point to obtain an impedance gradient of each pixel point and a gradient direction corresponding to the impedance gradient; Traversing the area corresponding to each peak position in the peak position set to obtain at least one pixel point to be confirmed, wherein the angle between the gradient direction corresponding to the pixel point to be confirmed and the peak direction corresponding to the peak position is greater than a preset angle; Among the at least one pixel point to be confirmed, selecting the pixel point to be confirmed that has the shortest distance from the peak position in the peak position set as the target pixel point; Taking the distance between the target pixel point and the peak position in the peak position set as the radius and the peak position in the peak position set as the center of the circle, a heart region to be processed is obtained, wherein the heart region to be processed is located in the impedance change image of the blood flow; The impedance changes of all pixels in the to-be-processed heart region are set to 0 to obtain a blood perfusion impedance image, which is an impedance change image of the blood flow after the to-be-processed heart region is removed.

10. A blood perfusion imaging device based on an EIT device, the device comprising: An acquisition unit, used to acquire ventilation data within a monitoring period and a total impedance waveform graph corresponding to the ventilation data; A selection unit, configured to select a first time period from the total impedance waveform diagram, wherein the first time period is a time period of normal ventilation in the monitoring cycle; The acquisition unit is further used to acquire a first impedance waveform graph corresponding to the first time period and first total impedance waveform data corresponding to the first impedance waveform graph; A generating unit, configured to generate a ventilation image according to the first total impedance waveform data; The generating unit is further configured to generate a blood perfusion impedance image according to the first total impedance waveform data and the total impedance waveform diagram; The generating unit is further used to obtain blood flow analysis data according to the ventilation image and the blood perfusion impedance image.

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