A method, apparatus and device for determining a phase profile of a cardiopulmonary region signal

Abstract

The present disclosure relates to a method, device and equipment for determining the phase distribution of a cardiopulmonary region signal, the method comprising: collecting a target electrical impedance tomography signal synchronized with the mechanical movement of the heart of a subject from the electrical impedance tomography signals of the chest of the subject at multiple detection times; determining an electrical impedance static image of the chest of the subject according to the target electrical impedance tomography signal; determining a heart region of interest and a lung region of interest of the subject in the electrical impedance static image respectively; determining a peak pixel point image according to the electrical impedance time variation curve corresponding to the target pixel point in the lung region of interest; calculating the sum of the pixel points in the heart region of interest and the lung region of interest, multiplying the sum of the pixel points with each peak pixel point in the peak pixel point image one by one to obtain a phase distribution map of the cardiopulmonary region signal of the subject. The voltage signal synchronized with the mechanical movement of the heart can be corresponded with the spatial position, thereby accurately reflecting the phase distribution of the blood flow signal of the cardiopulmonary region of the subject.

Description

Technical Field

[0001] This disclosure relates to the field of computer information processing technology, and in particular to a method, apparatus and device for determining the phase distribution of signals in the cardiopulmonary region. Background Technology

[0002] Currently, pulmonary blood flow can be measured using radionuclide perfusion scanning. However, radionuclide perfusion scanning uses the radioactive isotope technetium, which is expensive to obtain and difficult to measure in real time, and even more difficult to measure the phase distribution of pulmonary perfusion.

[0003] The existing electrical impedance tomography technique for measuring the phase of blood flow in the heart or lungs uses the following method: first, extract the voltage signal that is synchronized with the mechanical motion of the heart from the original measured voltage signal, and then calculate the average of the channel dimensions. The average curve of the resulting time signal is considered to be the curve that conforms to the phase characteristics of the cardiac signal.

[0004] The main drawbacks of the above method can be: on the one hand, the voltage signal synchronized with the mechanical movement of the heart is affected by the blood circulation of the heart and lungs at the same time. Therefore, the average curve calculated from the voltage signal does not have a definite physical meaning and is difficult to correspond to the time nodes of heart contraction or relaxation. On the other hand, the voltage signal synchronized with the mechanical movement of the heart is difficult to correspond to spatial location, and therefore it is difficult to reflect the phase distribution of blood flow signals in the cardiopulmonary region. Summary of the Invention

[0005] This disclosure provides a method, apparatus, and device for determining the phase distribution of signals in the cardiopulmonary region, in order to solve the problem in the prior art that voltage signals synchronized with the mechanical movement of the heart are difficult to correspond to spatial positions, and therefore cannot reflect the phase distribution of blood flow signals in the heart region.

[0006] In a first aspect, this disclosure provides a method for determining the phase distribution of signals in the cardiopulmonary region, including:

[0007] Among the electrical impedance tomography signals of the subject's chest collected at multiple detection times, the target electrical impedance tomography signal synchronized with the subject's cardiac mechanical motion is selected.

[0008] Based on the target electrical impedance tomography signal at each detection time, determine the static electrical impedance image of the subject's chest;

[0009] The regions of interest for the heart and lungs of the subject were determined in the static electrical impedance image, respectively.

[0010] The peak pixel image is determined based on the electrical impedance time change curve corresponding to the target pixel in the region of interest of the lung.

[0011] The sum of pixels in the heart region of interest and the lung region of interest is calculated, and the sum of pixels is multiplied by each peak pixel in the peak pixel image to obtain the phase distribution map of the cardiopulmonary region signal of the subject.

[0012] In some embodiments, among the electrical impedance tomography signals of the subject's chest acquired at multiple detection times, the target electrical impedance tomography signal synchronized with the subject's cardiac mechanical motion includes:

[0013] By applying an excitation current or voltage to the body of the subject through electrodes placed around the chest cavity, data measurements are taken at multiple measurement moments on the remaining electrodes to obtain electrical signals; the electrical signals include current signals or voltage signals.

[0014] Based on the mechanical movement frequency of the subject's heart, the electrical signal is processed to extract the target electrical signal that is synchronized with the mechanical movement of the subject's heart.

[0015] In some embodiments, determining a static electrical impedance tomography image of the subject's chest based on the target electrical impedance tomography signal at each detection time includes:

[0016] Based on the target electrical impedance tomography signal at each detection time, an electrical impedance image sequence of the subject's chest is constructed;

[0017] Based on the electrical impedance image sequence, the static electrical impedance images of the subject's chest are integrated.

[0018] In some embodiments, a sequence of electrical impedance tomography images of the subject's chest is constructed based on the target electrical impedance tomography signal at each detection time, including:

[0019] Calculate the difference between the measured target electrical signals at every two adjacent detection times across all detection times;

[0020] Calculate the difference reconstruction function of the difference to obtain the change in electrical conductivity in the thoracic cavity of the subject at every two adjacent detection times;

[0021] The electrical impedance change in the subject's thoracic cavity at each two adjacent detection times is determined based on the change in conductivity.

[0022] Based on the changes in electrical impedance, a sequence of electrical impedance images of the subject's chest is constructed.

[0023] In some embodiments, based on the electrical impedance image sequence, integrating the static electrical impedance images of the subject's chest includes:

[0024] Obtain the impedance element matrix corresponding to the impedance image sequence, where each row of the impedance element matrix is ​​the impedance of the target pixel in the impedance image sequence at a detection time;

[0025] Calculate the average electrical impedance of all elements in the electrical impedance element matrix;

[0026] Based on the impedance of each pixel in the impedance image sequence at each detection time and the average impedance, the slope and intercept of each pixel in the impedance image sequence are determined.

[0027] The slopes of each pixel in the electrical impedance image sequence are combined to obtain a static electrical impedance image of the subject's chest.

[0028] In some embodiments, determining the region of interest in the lungs of the subject in the static electrical impedance image includes:

[0029] The value of each pixel in the static impedance image is determined based on the slope of each pixel and a first preset threshold.

[0030] The region of interest in the lungs of the subject is determined based on the value of each pixel.

[0031] If the slope of the target pixel in the impedance static image is greater than the first preset threshold, the target pixel is set to 1; otherwise, the target pixel is set to 0. The region composed of the pixels with a value of 1 is determined as the region of interest of the lungs of the subject.

[0032] In some embodiments, determining the region of interest in the heart of the subject in the static electrical impedance image includes:

[0033] The value of each pixel in the static impedance image is determined based on the slope of each pixel in the static impedance image and a second preset threshold.

[0034] The region of interest in the heart of the subject is determined based on the value of each pixel.

[0035] If the slope of the target pixel in the static impedance image is less than the second preset threshold, the target pixel is set to 1; otherwise, the target pixel is set to 0. The region composed of the pixels with a value of 1 is determined as the region of interest of the subject's heart.

[0036] In some embodiments, determining the peak pixel image based on the electrical impedance time-varying curve corresponding to the target pixel in the region of interest of the lung includes:

[0037] In the lung region of interest in the static impedance image, the pixel with the highest brightness value is selected as the target pixel, and the impedance time change curve corresponding to the target pixel is plotted.

[0038] In the impedance time variation curve, select a section of the curve that contains at least one peak point and one trough point as the cardiac cycle;

[0039] The peak point detection process is performed on the impedance time change curve corresponding to each pixel in the impedance image sequence within the cardiac cycle to determine the peak pixel corresponding to each pixel in the impedance image sequence.

[0040] The peak pixels are combined to obtain a peak pixel image.

[0041] Secondly, this disclosure also provides an apparatus for determining the phase distribution of signals in the cardiopulmonary region, comprising:

[0042] The acquisition module is used to acquire the target electrical impedance tomography signal that is synchronized with the mechanical motion of the heart of the subject from the electrical impedance tomography signals of the chest of the subject at multiple detection times.

[0043] The first determining module is used to determine the static electrical impedance tomography image of the subject's chest based on the target electrical impedance tomography signal at each detection time.

[0044] The second determining module is used to determine the region of interest in the heart and the region of interest in the lungs of the subject in the static electrical impedance image, respectively.

[0045] The third determining module is used to determine the peak pixel image based on the electrical impedance time change curve corresponding to the target pixel in the region of interest of the lung.

[0046] The calculation module is used to calculate the sum of pixels in the heart region of interest and the lung region of interest, and multiply the sum of pixels by each peak pixel in the peak pixel image to obtain the phase distribution map of the cardiopulmonary region signal of the subject.

[0047] Thirdly, this disclosure also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described method.

[0048] Fourthly, this disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0049] Fifthly, this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0050] This disclosure provides a method, apparatus, and device for determining the phase distribution of signals in the cardiopulmonary region. The method involves acquiring target electrical impedance tomography (EIT) signals synchronized with the mechanical movement of the subject's heart from the EIT signals of the chest at multiple detection times. Based on the target EIT signals at each detection time, a static EIT image of the subject's chest is determined. Within the static EIT image, regions of interest (ROIs) for the heart and lungs are identified. Peak pixel images are determined based on the time-varying impedance curves corresponding to target pixels in the lung ROI. The sum of pixels in the heart and lung ROIs is calculated, and this sum is multiplied by each peak pixel in the peak pixel image to obtain the phase distribution map of the subject's cardiopulmonary region signals. This method correlates the voltage signals synchronized with the mechanical movement of the heart with spatial location, thereby accurately reflecting the phase distribution of blood flow signals in the subject's cardiopulmonary region. Attached Figure Description

[0051] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0052] Figure 1 A flowchart illustrating a method for determining the phase distribution of signals in the cardiopulmonary region, provided in an embodiment of this disclosure;

[0053] Figure 2 This embodiment of the present disclosure provides a voltage signal measured in a healthy subject under breath-holding conditions at the end of inspiration.

[0054] Figure 3 Electrical impedance image a is the electrical impedance image in the electrical impedance image sequence provided in this embodiment of the present disclosure;

[0055] Figure 4 Electrical impedance image b is the electrical impedance image in the electrical impedance image sequence provided in this embodiment of the disclosure;

[0056] Figure 5 Electrical impedance image c is the electrical impedance image in the electrical impedance image sequence provided in this embodiment of the disclosure;

[0057] Figure 6 The impedance image d in the impedance image sequence provided in the embodiments of this disclosure;

[0058] Figure 7 Static images of electrical impedance provided for embodiments of this disclosure;

[0059] Figure 8Images of regions of interest in the heart and lungs provided for embodiments of this disclosure;

[0060] Figure 9 A schematic diagram illustrating the selection of target pixels in a lung region of interest in a static electrical impedance image, as provided in an embodiment of this disclosure.

[0061] Figure 10 The electrical impedance time variation curve corresponding to the target pixel provided in this embodiment of the disclosure, and a schematic diagram of the cardiac cycle selected therein;

[0062] Figure 11 The peak pixel image provided in this embodiment of the disclosure;

[0063] Figure 12 A phase distribution map of the cardiopulmonary region signal of the subject provided in an embodiment of this disclosure;

[0064] Figure 13 This is another flowchart illustrating the method for determining the phase distribution of the cardiopulmonary region signal provided in this embodiment of the present disclosure;

[0065] Figure 14 This is a schematic diagram of a device for determining the phase distribution of signals in the cardiopulmonary region, provided in an embodiment of this disclosure.

[0066] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0067] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0068] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0069] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0070] It should be noted that existing technologies extract voltage signals synchronized with cardiac mechanical motion from the original measured voltage signals, and then directly average them along the channel dimension, assuming that the resulting average curve (time signal) conforms to the phase characteristics of cardiac signals. However, the results are difficult to interpret and do not accurately reflect the true phase distribution of cardiac signals. The method for determining the phase distribution of signals in the cardiopulmonary region described in this disclosure displays and quantifies the phase distribution of cardiac signals in the cardiopulmonary region of the subject based on impedance image sequences, providing an effective means for subsequent phase-based signal processing.

[0071] Example 1

[0072] Figure 1 This is a flowchart illustrating a method for determining the phase distribution of signals in the cardiopulmonary region, provided as an embodiment of this disclosure. Figure 1 As shown, a method for determining the phase distribution of signals in the cardiopulmonary region includes:

[0073] Step 101: Collect the target electrical impedance tomography signal that is synchronized with the mechanical motion of the heart of the subject from the electrical impedance tomography signals of the chest of the subject at multiple detection times.

[0074] Step 102: Determine the static electrical impedance tomography image of the subject's chest based on the target electrical impedance tomography signal at each detection time.

[0075] Step 103: Determine the region of interest for the heart and the region of interest for the lungs of the subject in the static electrical impedance image, respectively;

[0076] Step 104: Determine the peak pixel image based on the impedance time change curve corresponding to the target pixel in the region of interest of the lung.

[0077] Step 105: Calculate the sum of pixels in the heart region of interest and the lung region of interest, and multiply the sum of pixels by each peak pixel in the peak pixel image to obtain the phase distribution map of the cardiopulmonary region signal of the subject.

[0078] In this embodiment, electrical impedance tomography (EIT) signals of the subject's chest are measured during spontaneous breathing or breath-holding. A target EIT signal synchronized with the subject's cardiac mechanical movement is extracted from this signal. Based on the target EIT signal, a static EIT image of the subject's chest is constructed. Regions of interest (ROIs) for the heart and lungs are determined within this static EIT image. Peak pixel images are determined based on the time-varying impedance curves corresponding to target pixels in the lung ROI. Multiplying the heart ROIs and lung ROIs with the peak pixel images yields a phase distribution map of the subject's cardiopulmonary region signals. This method correlates voltage signals synchronized with cardiac mechanical movement with spatial location, thereby accurately reflecting the phase distribution of blood flow signals in the subject's cardiopulmonary region.

[0079] Example 2

[0080] Based on the above embodiments, step 101 may include:

[0081] Step 1011: After applying an excitation current or excitation voltage to the body of the subject by placing some electrodes around the chest cavity of the subject, data measurements are taken at multiple measurement times on the remaining electrodes to obtain electrical signals; the electrical signals include current signals or voltage signals.

[0082] Step 1012: Based on the mechanical movement frequency of the subject's heart, perform signal extraction processing on the electrical signal to obtain the target electrical signal that is synchronized with the mechanical movement of the subject's heart.

[0083] Specifically, by placing electrodes around the chest cavity of the subject, an excitation current can be applied to the subject's body, and voltage measurements can be taken at multiple measurement moments on the remaining electrodes to obtain data such as... Figure 2 The voltage signal shown; Figure 2The voltage signal (average curve of each channel) is measured by a healthy subject under the condition of breath-holding at the end of inspiration. Then, based on the mechanical motion frequency of the subject's heart, the voltage signal is processed by signal extraction to obtain the target voltage signal that is synchronized with the mechanical motion of the subject's heart.

[0084] Alternatively, by placing electrodes around the chest cavity of the subject, an excitation voltage is applied to the subject's body, and current measurements are performed at multiple measurement times on the remaining electrodes to obtain a current signal; then, based on the mechanical movement frequency of the subject's heart, the current signal is processed to extract the target current signal that is synchronized with the mechanical movement of the subject's heart.

[0085] For example, by placing 16 electrodes around the chest cavity of the subject, an excitation current is applied to the subject's body through 8 of the electrodes, and voltage is measured on the remaining 8 electrodes to obtain a target voltage signal; as another implementation, an excitation voltage can also be applied to the subject's body through 8 of the electrodes, and current is measured on the remaining 8 electrodes to obtain a target current signal.

[0086] In this embodiment, by acquiring a target current signal or a target voltage signal that is synchronized with the mechanical movement of the subject's heart, the contraction and relaxation process of the subject's heart can be accurately reflected in the target current signal or the target voltage signal, and the abnormality of whether the subject's heart has weak contraction or restricted relaxation can be detected, thereby obtaining an accurate phase distribution of the subject's cardiopulmonary region signal.

[0087] Example 3

[0088] Figures 3 to 6 The impedance images a to d in the impedance image sequence provided in this embodiment of the present disclosure are, Figure 7 Static images of electrical impedance provided for embodiments of this disclosure, such as Figures 3 to 7 As shown, based on the above embodiments, step 102 may include:

[0089] Step 1021: Construct a sequence of electrical impedance tomography images of the subject's chest based on the target electrical impedance tomography signal at each detection time.

[0090] Step 1022: Based on the electrical impedance image sequence, integrate the static electrical impedance image of the subject's chest.

[0091] The impedance image sequence is a set of impedance images generated by impedance imaging and arranged in order of a detection time. Each impedance image contains multiple current data or voltage data.

[0092] The static impedance image is an image obtained by integrating the impedance image sequence.

[0093] In this embodiment, by constructing the electrical impedance image sequence, the changes in electrical impedance of the subject's chest over a detection period can be determined; by integrating the static electrical impedance images, data processing can be simplified, and the static electrical impedance images are more suitable for static feature extraction, which improves image stability and facilitates the analysis and interpretation of electrical impedance data.

[0094] Example 4

[0095] Figures 3 to 6 For example, impedance images a to d in the impedance image sequence provided in the embodiments of this disclosure Figures 3 to 6 As shown, based on the above embodiments, step 1021 may include:

[0096] Step 10211: Calculate the difference between the measured target electrical signals at every two adjacent detection times across all detection times; the target electrical signals include: target voltage signals or target current signals;

[0097] Step 10212: Calculate the differential reconstruction function of the difference to obtain the change in electrical conductivity in the chest cavity of the subject at every two adjacent detection times;

[0098] Step 10213: Determine the change in electrical impedance within the subject's thoracic cavity at every two adjacent detection times based on the change in conductivity;

[0099] Step 10214: Construct a sequence of electrical impedance images of the subject's chest based on the electrical impedance changes.

[0100] It should be noted that the impedance image sequence can be determined based on various feasible algorithms. Specifically, the change in electrical impedance within the subject's chest cavity between two adjacent detection times can be determined by calculating the voltage difference between the two detection times. The formula for calculating the change in electrical impedance is as follows:

[0101]

[0102] Wherein, ΔZ is the change in electrical impedance in the chest cavity of the subject between the two detection times, and Δσ is the change in electrical conductivity in the chest cavity of the subject between two adjacent times;

[0103] Δσ=F(Δd)

[0104] Where Δd is the voltage difference in the chest cavity of the subject at two adjacent detection times, Δσ is the change in conductivity in the chest cavity of the subject at the two adjacent detection times, and F is a function.

[0105] In this embodiment, by constructing the electrical impedance image sequence, it is possible to determine the changes in the electrical impedance of the subject's chest over a detection period, thereby determining the changes in the subject's body.

[0106] Example 5

[0107] Figure 7 Static images of electrical impedance provided for embodiments of this disclosure, such as Figure 7 As shown, based on the above embodiments, step 1022 may include:

[0108] Step 10221: Obtain the impedance element matrix corresponding to the impedance image sequence, where each row of the impedance element matrix is ​​the impedance of the target pixel in the impedance image sequence at a detection time;

[0109] Step 10222: Calculate the average electrical impedance of all elements in the electrical impedance element matrix;

[0110] Step 10223: Determine the slope and intercept of each pixel in the impedance image sequence based on the impedance of each pixel at each detection time and the average impedance.

[0111] Step 10224: Combine the slopes of each pixel in the electrical impedance image sequence to obtain a static electrical impedance image of the subject's chest.

[0112] It should be noted that the static impedance image can be obtained based on various feasible algorithms. Specifically, the impedance image sequence can be represented as an impedance element matrix A, where each column of the impedance element matrix A is a static impedance image at a detection time, and each row is the impedance of the target pixel in the impedance image sequence at a detection time, denoted as a. i = (i = 1, 2, ..., M), where M is the total number of rows in the resistivity element matrix A;

[0113] The formula for calculating the average electrical reactance of all elements in the electrical reactance element matrix A is:

[0114]

[0115] in, Let a be the average electrical impedance of all elements in the electrical impedance element matrix A. iLet M be the impedance value of the i-th pixel at the first detection time, and M be the total number of all detection times.

[0116] The formulas for calculating the slope and intercept of each pixel in the impedance image sequence are as follows:

[0117]

[0118] in, for and a i Linear regression, Let a be the average electrical impedance of all elements in the electrical impedance element matrix A. i Let s be the impedance value of the i-th pixel at the first detection time. i b is the slope of each pixel in the impedance image sequence. i It is the intercept of each pixel in the impedance image sequence.

[0119] The slopes of each pixel in the impedance image sequence are combined to obtain a static impedance image of the subject's chest, i.e.: I static = (s1, s2, ..., s N ) T ;

[0120] Among them, I static The image represents a static electrical impedance image of the subject's chest, where s1 is the slope of the first pixel in the electrical impedance image sequence, s2 is the slope of the second pixel in the electrical impedance image sequence, and s... N The slope of the Nth pixel in the impedance image sequence is given by T, where N is the total number of pixels in the impedance image sequence, and T represents the transpose.

[0121] In this embodiment, by integrating the static impedance image, data processing can be simplified, and the static impedance image is more suitable for static feature extraction. This improves image stability and facilitates the analysis and interpretation of impedance data.

[0122] Example 6

[0123] Figure 8 Images of regions of interest in the heart and lungs provided for embodiments of this disclosure, such as Figure 8 As shown, based on the above embodiments, step 103 may include:

[0124] Step 1031: Determine the value of each pixel in the static impedance image based on the slope of each pixel in the static impedance image and the first preset threshold.

[0125] Step 1032: Determine the region of interest in the lungs of the subject based on the values ​​of each pixel;

[0126] If the slope of the target pixel in the impedance static image is greater than the first preset threshold, the target pixel is set to 1; otherwise, the target pixel is set to 0. The region composed of the pixels with a value of 1 is determined as the region of interest of the lungs of the subject.

[0127] In practice, the region of interest in the lungs of the test subject can be determined based on the values ​​of each pixel, i.e.:

[0128] ROI lung = (l1, l2, ..., l K ) T

[0129] Among them, ROI lung The region of interest is the lung of the subject, l1 is the value of the first pixel in the electrical impedance image sequence, l2 is the value of the second pixel in the electrical impedance image sequence, and l K Let T be the value of the Kth pixel in the impedance image sequence, where K is the total number of pixels in the impedance image sequence, and T represents the transpose.

[0130] Specifically, the value of the i-th pixel in the static impedance image is determined based on the slope of the i-th pixel and a first preset threshold, i.e.:

[0131]

[0132] Wherein, li is the value of the i-th pixel in the impedance image sequence, si is the slope of the i-th pixel in the impedance image sequence, T1 is the first preset threshold, and K is the total number of pixels in the impedance image sequence.

[0133] The region consisting of all pixels with a value of 1 is defined as the region of interest (ROI) of the lungs of the subject.

[0134] The first preset threshold can be determined based on the slope of each pixel in the impedance image sequence, i.e.: T1 = 0.2 × max(s1, s2, ..., s...). N );

[0135] Where T1 is the first preset threshold, 0.2 is a constant, max is the maximum pixel value in the impedance image sequence, s1 is the slope of the first pixel in the impedance image sequence, s2 is the slope of the second pixel in the impedance image sequence, and s NLet be the slope of the Nth pixel in the impedance image sequence, where N is the total number of pixels in the impedance image sequence.

[0136] In this embodiment, by determining the region of interest (ROI) of the lungs of the test subject, the pixels within the ROI can be processed to achieve spatial correspondence and accurately locate the phase distribution of the lungs of the test subject, making the results more accurate.

[0137] Example 7

[0138] Figure 8 Images of regions of interest in the heart and lungs provided for embodiments of this disclosure, such as Figure 8 As shown, based on the above embodiments, step 103 may include:

[0139] Step 1033: Determine the value of each pixel in the static impedance image based on the slope of each pixel in the static impedance image and the second preset threshold.

[0140] Step 1034: Determine the region of interest (ROI) of the subject's heart based on the values ​​of each pixel.

[0141] If the slope of the target pixel in the static impedance image is less than the second preset threshold, the target pixel is set to 1; otherwise, the target pixel is set to 0. The region composed of the pixels with a value of 1 is determined as the region of interest of the subject's heart.

[0142] In practice, the region of interest (ROI) of the subject's heart can be determined based on the values ​​of each pixel, i.e.:

[0143] ROI heart = (l1, l2, ..., l K ) T

[0144] Among them, ROI heart The region of interest is the heart of the subject, l1 is the value of the first pixel in the impedance image sequence, l2 is the value of the second pixel in the impedance image sequence, and l K Let T be the value of the Kth pixel in the impedance image sequence, where K is the total number of pixels in the impedance image sequence, and T represents the transpose.

[0145] Specifically, the value of the i-th pixel in the static impedance image is determined based on the slope of the i-th pixel and a second preset threshold, i.e.:

[0146]

[0147] Among them, l i Let s be the value of the i-th pixel in the impedance image sequence. i T1 is the slope of the i-th pixel in the impedance image sequence, T2 is the second preset threshold, and K is the total number of pixels in the impedance image sequence.

[0148] The region consisting of all pixels with a value of 1 is defined as the region of interest (ROI) of the subject's heart.

[0149] The second preset threshold can be determined based on the slope of each pixel in the impedance image sequence, i.e.: T2 = 0.2 × min(s1, s2, ..., s...). N );

[0150] Where T2 is the second preset threshold, 0.2 is a constant, min is the minimum pixel value in the impedance image sequence, s1 is the slope of the first pixel in the impedance image sequence, s2 is the slope of the second pixel in the impedance image sequence, and s N Let be the slope of the Nth pixel in the impedance image sequence, where N is the total number of pixels in the impedance image sequence.

[0151] In this embodiment, by determining the region of interest (ROI) of the subject's heart, the pixels within the ROI can be processed to achieve spatial correspondence and accurately locate the phase distribution of the subject's heart, resulting in more accurate results.

[0152] Example 8

[0153] Figure 9 This is a schematic diagram illustrating the selection of target pixels in a region of interest of the lung in a static electrical impedance image, as provided in an embodiment of this disclosure. Figure 10 The electrical impedance time-varying curve corresponding to the target pixel provided in this embodiment of the disclosure, and a schematic diagram of the selected cardiac cycle therein, are shown below. Figure 9 and Figure 10 As shown, based on the above embodiments, step 104 may include:

[0154] Step 1041: In the lung region of interest in the static impedance image, select the pixel with the highest brightness value as the target pixel and plot the impedance time change curve corresponding to the target pixel.

[0155] Step 1042: Select a segment of the impedance time variation curve that contains at least one peak point and one trough point as the cardiac cycle.

[0156] Step 1043: Perform peak point detection processing on the impedance time change curve corresponding to each pixel in the impedance image sequence within the cardiac cycle to determine the peak pixel corresponding to each pixel in the impedance image sequence.

[0157] Step 1044: Combine the peak pixels to obtain a peak pixel image.

[0158] It should be noted that, as Figure 9 As shown, the pixel with coordinates X, Y(38, 49) is the target pixel. Figure 10 As shown, the cardiac cycle is represented within the dashed box.

[0159] In this embodiment, based on the impedance image sequence, peak points are detected within the cardiac cycle for the impedance time change curve of each pixel i (i = 1, 2, ..., N) to obtain peak pixels. All peak pixels are then combined to obtain the peak pixel image I. peak ;

[0160] I peak = (p1, p2, ..., p L ) T

[0161] Among them, I peak This is an image of peak pixels, where p1 is the first peak pixel, p2 is the second peak pixel, and p... N Let L be the Lth peak pixel, where L is the total number of peak pixels, and T represents the transpose.

[0162] The peak pixel image has prominent features, making it easy to highlight abnormal areas, which can simplify data processing, reduce computational complexity, and accelerate algorithm operation.

[0163] Example 9

[0164] Figure 11 The peak pixel image provided in this embodiment of the disclosure, Figure 12 The phase distribution map of the cardiopulmonary region signal of the subject provided in the embodiments of this disclosure is as follows: Figure 11 and Figure 12 As shown, based on the above embodiments, step 105 may include:

[0165] Step 1051: Calculate the sum of pixels in the heart region of interest and the lung region of interest, and multiply the sum of pixels by each peak pixel in the peak pixel image to obtain the phase distribution map of the cardiopulmonary region signal of the subject.

[0166] Specifically, the sum of the pixels in the heart region of interest and the lung region of interest is multiplied by each peak pixel in the peak pixel image to obtain the phase distribution map of the cardiopulmonary region signal of the subject, i.e.:

[0167] I phase =I peak ⊙(ROI lung +ROI heart )

[0168] Among them, I phase This is a phase distribution map of the cardiopulmonary region signal of the subject, I peak For the peak pixel image, ROI lung The region of interest (ROI) is the lung of the subject. heart The region of interest is the heart of the subject, and ⊙ represents pixel-by-pixel multiplication.

[0169] In this embodiment, based on the pixels in the heart region of interest and the lung region of interest of the subject, as well as the peak pixels, the phase distribution of the signal in the cardiopulmonary region of the subject can be accurately determined, thereby accurately reflecting the function of the subject's heart and lungs and making a true and accurate assessment of the subject's cardiopulmonary function.

[0170] Example 10

[0171] Based on the above embodiments, this embodiment provides an application example.

[0172] Figure 13 This is another flowchart illustrating the method for determining the phase distribution of the cardiopulmonary region signal provided in this embodiment of the present disclosure, as shown below. Figure 13 As shown, the specific implementation process of a method for determining the phase distribution of signals in the cardiopulmonary region may include:

[0173] Step 1301: Acquire target electrical impedance tomography signals from the subject's chest;

[0174] Step 1302: Construct an impedance image sequence based on the target impedance tomography signal;

[0175] Step 1303: Integrate the static impedance image based on the impedance image sequence;

[0176] Step 1304: Generate the region of interest for the lungs and the region of interest for the heart of the subject based on the static electrical impedance image;

[0177] Step 1305: Determine the target pixel in the region of interest of the lung and locate a cardiac cycle;

[0178] Step 1306: Detect peak points pixel by pixel within the cardiac cycle to determine the peak pixel image;

[0179] Step 1307: Determine the phase distribution map of the cardiopulmonary region signal of the subject based on the pixels in the lung region of interest and the heart region of interest and the peak pixels in the peak pixel image.

[0180] In this embodiment, the method for determining the phase distribution of the cardiopulmonary region signal can correspond the voltage signal synchronized with the mechanical movement of the heart to the spatial position, thereby accurately reflecting the phase distribution of the blood flow signal in the cardiopulmonary region of the subject.

[0181] Example 11

[0182] Figure 14 This is a schematic diagram of a module for determining the phase distribution of signals in the cardiopulmonary region, provided as an embodiment of this disclosure. Figure 14 As shown, a device 140 for determining the phase distribution of signals in the cardiopulmonary region includes:

[0183] Acquisition module 141 is used to acquire target electrical impedance tomography signals that are synchronized with the mechanical motion of the heart of the subject from electrical impedance tomography signals of the chest of the subject at multiple detection times.

[0184] The first determining module 142 is used to determine the static electrical impedance tomography image of the subject's chest based on the target electrical impedance tomography signal at each detection time.

[0185] The second determining module 143 is used to determine the region of interest in the heart and the region of interest in the lungs of the subject in the static electrical impedance image, respectively.

[0186] The third determining module 144 is used to determine the peak pixel image based on the electrical impedance time change curve corresponding to the target pixel in the region of interest of the lung.

[0187] The calculation module 145 is used to calculate the sum of pixels in the heart region of interest and the lung region of interest, and multiply the sum of pixels by each peak pixel in the peak pixel image to obtain the phase distribution map of the cardiopulmonary region signal of the subject.

[0188] In some embodiments, the acquisition module 141 can be used for:

[0189] By applying an excitation current or voltage to the body of the subject through electrodes placed around the chest cavity, data measurements are taken at multiple measurement moments on the remaining electrodes to obtain electrical signals; the electrical signals include current signals or voltage signals.

[0190] Based on the mechanical movement frequency of the subject's heart, the electrical signal is processed to extract the target electrical signal that is synchronized with the mechanical movement of the subject's heart.

[0191] In some embodiments, the first determining module 142 may be used to:

[0192] Based on the target electrical impedance tomography signal at each detection time, an electrical impedance image sequence of the subject's chest is constructed;

[0193] Based on the electrical impedance image sequence, the static electrical impedance images of the subject's chest are integrated.

[0194] In some embodiments, the first determining module 142 may further be used for:

[0195] Calculate the difference between the measured target electrical signals at every two adjacent detection times across all detection times;

[0196] Calculate the difference reconstruction function of the difference to obtain the change in electrical conductivity in the thoracic cavity of the subject at every two adjacent detection times;

[0197] The electrical impedance change in the subject's thoracic cavity at each two adjacent detection times is determined based on the change in conductivity.

[0198] Based on the changes in electrical impedance, a sequence of electrical impedance images of the subject's chest is constructed.

[0199] In some embodiments, the first determining module 142 may further be used for:

[0200] Obtain the impedance element matrix corresponding to the impedance image sequence, where each row of the impedance element matrix is ​​the impedance of the target pixel in the impedance image sequence at a detection time;

[0201] Calculate the average electrical impedance of all elements in the electrical impedance element matrix;

[0202] Based on the impedance of each pixel in the impedance image sequence at each detection time and the average impedance, the slope and intercept of each pixel in the impedance image sequence are determined.

[0203] The slopes of each pixel in the electrical impedance image sequence are combined to obtain a static electrical impedance image of the subject's chest.

[0204] In some embodiments, the second determining module 143 may be used to:

[0205] The value of each pixel in the static impedance image is determined based on the slope of each pixel and a first preset threshold.

[0206] The region of interest in the lungs of the subject is determined based on the value of each pixel.

[0207] If the slope of the target pixel in the impedance static image is greater than the first preset threshold, the target pixel is set to 1; otherwise, the target pixel is set to 0. The region composed of the pixels with a value of 1 is determined as the region of interest of the lungs of the subject.

[0208] In some embodiments, the second determining module 143 may also be used for:

[0209] The value of each pixel in the static impedance image is determined based on the slope of each pixel in the static impedance image and a second preset threshold.

[0210] The region of interest in the heart of the subject is determined based on the value of each pixel.

[0211] If the slope of the target pixel in the static impedance image is less than the second preset threshold, the target pixel is set to 1; otherwise, the target pixel is set to 0. The region composed of the pixels with a value of 1 is determined as the region of interest of the subject's heart.

[0212] In some embodiments, the third determining module 144 may be used to:

[0213] In the lung region of interest in the static impedance image, the pixel with the highest brightness value is selected as the target pixel, and the impedance time change curve corresponding to the target pixel is plotted.

[0214] In the impedance time variation curve, select a section of the curve that contains at least one peak point and one trough point as the cardiac cycle;

[0215] The peak point detection process is performed on the impedance time change curve corresponding to each pixel in the impedance image sequence within the cardiac cycle to determine the peak pixel corresponding to each pixel in the impedance image sequence.

[0216] The peak pixels are combined to obtain a peak pixel image.

[0217] In this embodiment, electrical impedance tomography (EIT) signals of the subject's chest are measured during spontaneous breathing or breath-holding. A target EIT signal synchronized with the subject's cardiac mechanical movement is extracted from this signal. Based on the target EIT signal, a static EIT image of the subject's chest is constructed. Regions of interest (ROIs) for the heart and lungs are determined within this static EIT image. Peak pixel images are determined based on the time-varying impedance curves corresponding to target pixels in the lung ROI. Multiplying the heart ROIs and lung ROIs with the peak pixel images yields a phase distribution map of the subject's cardiopulmonary region signals. This method correlates voltage signals synchronized with cardiac mechanical movement with spatial location, thereby accurately reflecting the phase distribution of blood flow signals in the subject's cardiopulmonary region.

[0218] It should be noted that the device for determining the phase distribution of the cardiopulmonary region signal is a device corresponding to the method for determining the phase distribution of the cardiopulmonary region signal described above. All implementation methods of the method for determining the phase distribution of the cardiopulmonary region signal in the device for determining the phase distribution of the cardiopulmonary region signal described above are applicable to the embodiments of the device for determining the phase distribution of the cardiopulmonary region signal and can achieve the same technical effect.

[0219] Example 12

[0220] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0221] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method described in the above embodiments.

[0222] In some embodiments of this example, a computer program product is provided, including a computer program / instructions, which, when executed by a processor, implements the steps of the method described in the above embodiments.

[0223] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods described in the above embodiments.

[0224] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, Blu-ray discs, etc.).

[0225] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0226] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0227] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0228] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0229] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0230] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0231] While the embodiments disclosed herein are as described above, the foregoing content is merely for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Any person skilled in the art to which this disclosure pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope of this disclosure; however, the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.

Claims

1. A method for determining the phase distribution of signals in the cardiopulmonary region, characterized in that, include: Among the electrical impedance tomography signals of the subject's chest collected at multiple detection times, the target electrical impedance tomography signal synchronized with the subject's cardiac mechanical motion is selected. Based on the target electrical impedance tomography signal at each detection time, determine the static electrical impedance image of the subject's chest; The regions of interest for the heart and lungs of the subject were determined in the static electrical impedance image, respectively. The peak pixel image is determined based on the electrical impedance time change curve corresponding to the target pixel in the region of interest of the lung. The sum of pixels in the heart region of interest and the lung region of interest is calculated, and the sum of pixels is multiplied by each peak pixel in the peak pixel image to obtain the phase distribution map of the cardiopulmonary region signal of the subject.

2. The method for determining the phase distribution of signals in the cardiopulmonary region according to claim 1, characterized in that, Among the electrical impedance tomography signals of the subject's chest acquired at multiple detection times, the target electrical impedance tomography signal synchronized with the subject's cardiac mechanical motion includes: By applying an excitation current or voltage to the body of the subject through electrodes placed around the chest cavity, data measurements are taken at multiple measurement moments on the remaining electrodes to obtain electrical signals; the electrical signals include current signals or voltage signals. Based on the mechanical movement frequency of the subject's heart, the electrical signal is processed to extract the target electrical signal that is synchronized with the mechanical movement of the subject's heart.

3. The method for determining the phase distribution of signals in the cardiopulmonary region according to claim 1, characterized in that, Based on the target electrical impedance tomography signal at each detection time, determine the static electrical impedance image of the subject's chest, including: Based on the target electrical impedance tomography signal at each detection time, an electrical impedance image sequence of the subject's chest is constructed; Based on the electrical impedance image sequence, the static electrical impedance images of the subject's chest are integrated.

4. The method for determining the phase distribution of signals in the cardiopulmonary region according to claim 3, characterized in that, Based on the target electrical impedance tomography signal at each detection time, a sequence of electrical impedance images of the subject's chest is constructed, including: Calculate the difference between the measured target electrical signals at every two adjacent detection times across all detection times; Calculate the difference reconstruction function of the difference to obtain the change in electrical conductivity in the thoracic cavity of the subject at every two adjacent detection times; The electrical impedance change in the subject's thoracic cavity at each two adjacent detection times is determined based on the change in conductivity. Based on the changes in electrical impedance, a sequence of electrical impedance images of the subject's chest is constructed.

5. The method for determining the phase distribution of signals in the cardiopulmonary region according to claim 3, characterized in that, Based on the electrical impedance image sequence, the static electrical impedance images of the subject's chest are integrated, including: Obtain the impedance element matrix corresponding to the impedance image sequence, where each row of the impedance element matrix is ​​the impedance of the target pixel in the impedance image sequence at a detection time; Calculate the average electrical impedance of all elements in the electrical impedance element matrix; Based on the impedance of each pixel in the impedance image sequence at each detection time and the average impedance, the slope and intercept of each pixel in the impedance image sequence are determined. The slopes of each pixel in the electrical impedance image sequence are combined to obtain a static electrical impedance image of the subject's chest.

6. The method for determining the phase distribution of signals in the cardiopulmonary region according to claim 1, characterized in that, Determining the region of interest (ROI) in the subject's lungs from the static electrical impedance image includes: The value of each pixel in the static impedance image is determined based on the slope of each pixel and a first preset threshold. The region of interest in the lungs of the subject is determined based on the value of each pixel. If the slope of the target pixel in the impedance static image is greater than the first preset threshold, the target pixel is set to 1; otherwise, the target pixel is set to 0. The region composed of the pixels with a value of 1 is determined as the region of interest of the lungs of the subject.

7. The method for determining the phase distribution of signals in the cardiopulmonary region according to claim 1, characterized in that, Determining the region of interest (ROI) of the subject's heart in the static electrical impedance image includes: The value of each pixel in the static impedance image is determined based on the slope of each pixel in the static impedance image and a second preset threshold. The region of interest in the heart of the subject is determined based on the value of each pixel. If the slope of the target pixel in the static impedance image is less than the second preset threshold, the target pixel is set to 1; otherwise, the target pixel is set to 0. The region composed of the pixels with a value of 1 is determined as the region of interest of the subject's heart.

8. The method for determining the phase distribution of signals in the cardiopulmonary region according to claim 1, characterized in that, Based on the impedance-time change curves corresponding to the target pixels in the region of interest of the lung, the peak pixel image is determined, including: In the lung region of interest in the static impedance image, the pixel with the highest brightness value is selected as the target pixel, and the impedance time change curve corresponding to the target pixel is plotted. In the impedance time variation curve, select a section of the curve that contains at least one peak point and one trough point as the cardiac cycle; The peak point detection process is performed on the time change curve of the electrical impedance corresponding to each pixel in the electrical impedance image sequence within the cardiac cycle to determine the peak pixel corresponding to each pixel in the electrical impedance image sequence. The peak pixels are combined to obtain a peak pixel image.

9. A device for determining the phase distribution of signals in a cardiopulmonary region, characterized in that, include: The acquisition module is used to acquire the target electrical impedance tomography signal that is synchronized with the mechanical motion of the heart of the subject from the electrical impedance tomography signals of the chest of the subject at multiple detection times. The first determining module is used to determine the static electrical impedance tomography image of the subject's chest based on the target electrical impedance tomography signal at each detection time. The second determining module is used to determine the region of interest in the heart and the region of interest in the lungs of the subject in the static electrical impedance image, respectively. The third determining module is used to determine the peak pixel image based on the electrical impedance time change curve corresponding to the target pixel in the region of interest of the lung. The calculation module is used to calculate the sum of pixels in the heart region of interest and the lung region of interest, and multiply the sum of pixels by each peak pixel in the peak pixel image to obtain the phase distribution map of the cardiopulmonary region signal of the subject.

10. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 8.

12. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 8.

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