Pulse wave conduction velocity measurement and correction method and system based on curved surface array

Abstract

The invention provides a pulse wave conduction velocity measurement correction method and system based on a curved surface array. The method comprises the steps that an ultrasonic image is obtained, point coordinates in a polar coordinate system are converted into coordinates in a rectangular coordinate system, abnormal points are replaced through linear fitting, and coordinates after the abnormal value points are replaced are obtained; performing cross-correlation calculation on the transformed coordinates to obtain a three-dimensional structure; replacing a target coordinate point in the coordinates after the abnormal value point, and extracting a corresponding coordinate point from the three-dimensional structure to obtain a cross-correlation spectrum; searching an extreme value in the cross-correlation spectrum, and calculating a physical length sum and a time difference of each group of points; and calculating segmented ultrasonic pulse wave conduction velocity measurement according to the time difference, and averaging each segment of ultrasonic pulse wave conduction velocity measurement to obtain a corrected curved surface array ultrasonic pulse wave conduction velocity measurement value. The system comprises a coordinate replacement module, a three-dimensional construction module and a numerical calculation module. According to the invention, quantitative analysis on the movement of the blood vessel wall and the blood flow velocity is facilitated.

Description

Technical Field

[0001] The invention relates to the technical field of ultrasonic pulse wave imaging, and in particular to a pulse wave conduction velocity measurement and correction method and system based on a curved array. Background Art

[0002] Ultrasonic pulse wave velocity (PWV) is a non-invasive measurement method used to assess the degree of arteriosclerosis and cardiovascular health; it measures the propagation velocity of the pulse wave in the blood vessels to assess the elasticity and hardness of the blood vessel wall. Traditional ultrasound pulse wave imaging mainly uses a focused scanning method, but this method has some defects: one of the problems is that the line density limits the frame rate of imaging. A lower frame rate will result in insufficient temporal resolution, thereby reducing the correlation between signals and may cause errors in the estimation of pulse wave velocity. In order to increase the frame rate, the number of scanned beams can be reduced, but this will reduce the quality of ultrasound images and raw data, and reduce the accuracy of pulse wave velocity estimation. At present, a new type of ultrasound ultrafast scanning method has emerged, which uses plane wave scanning to measure the pulse wave transmission rate. This method has high requirements for the parallel position of the probe relative to the scanning surface. A measuring surface with horizontal errors will increase the error of the output pulse wave transmission velocity. Therefore, this method is mostly used for scanning with linear array probes. The existing method of measuring pulse wave transmission velocity by ultrafast plane wave scanning of ultrasound basically uses the ultrafast plane wave compound technology in ultrasound to achieve high frame rate and calculate the pulse wave conduction velocity in segments. The key technologies include vascular wall tracking, tissue filtering, pulse wave imaging calculation, and segmented pulse wave conduction velocity calculation; by processing and analyzing the ultrasonic signal, accurate imaging of the pulse wave conduction velocity is achieved. Under the curved array, there is a challenge in the method of measuring pulse wave transmission velocity by plane wave scanning: because the vascular wall is not horizontal to the surface of the ultrasonic probe, the geometric shape of the ultrasonic wave propagation path changes, affecting the accurate calculation of the pulse wave transmission velocity. In order to solve this problem, the measurement results need to be corrected.

[0003] The existing technology currently has the problem that the coordinates of the target area under the non-planar probe are not easy to keep horizontal with the probe surface. Therefore, the present invention provides a pulse wave velocity measurement correction method and system based on a curved array, which makes the output pulse wave velocity value more accurate by correcting the measurement target that is not horizontal and the probe surface; by correcting the blood vessel wall path and the physical position of the probe relative to the target area, the pulse wave measurement result is corrected by piecewise fitting. The key technical methods include blood vessel wall tracking, target point coordinate transformation, outlier screening and pulse wave calculation correction. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a pulse wave velocity measurement and correction method based on a curved array, comprising the following steps:

[0005] Acquire an ultrasound image, convert the point coordinates in the polar coordinate system into coordinates in the rectangular coordinate system, replace the abnormal points in the rectangular coordinate system of the blood vessel wall position by linear fitting, and obtain the coordinates after the abnormal value points are replaced;

[0006] The transformed coordinates are cross-correlated and the three-dimensional structure is obtained. The target coordinate points in the coordinates after replacing the outlier points are extracted from the three-dimensional structure and the cross-correlation spectrum is obtained by expansion.

[0007] Find the extreme value in the cross-correlation spectrum, and calculate the total physical length and time difference of each group of points; calculate the segmented ultrasonic pulse wave conduction velocity measurement according to the time difference, take the average value of the ultrasonic pulse wave conduction velocity measurement of each segment, and obtain the corrected curved array ultrasonic pulse wave conduction velocity measurement value.

[0008] Optionally, the process of obtaining the coordinates after replacing the outlier points includes the following steps:

[0009] Acquire an ultrasound image containing the position information of the blood vessel wall, and perform rectangular coordinate system conversion for each polar coordinate point of the blood vessel wall position;

[0010] The mean square error is calculated for each segment of the longitudinal coordinates in the rectangular coordinate system, and compared with the value under the mean square error, so as to detect and replace the outlier points in the point coordinates in the rectangular coordinate system; the point coordinates in the rectangular coordinate system after replacing the outlier points are linearly fitted using the least squares method to obtain the parameters of the fitting line;

[0011] The coordinates of the replaced outlier point are calculated and replaced to obtain the coordinates of the replaced outlier point in the rectangular coordinate system.

[0012] Optionally, the process of normalizing the rectangular coordinate system includes the following steps:

[0013] Obtain the size of the current ultrasound image, calculate the axial point spacing of the current image, calculate the lateral point spacing based on the axial point spacing, and then calculate the upsampling multiple of the lateral coordinate;

[0014] Upsample each transverse coordinate, traverse each column of the current ultrasound image, from left to right; for each column, calculate the index of the current transverse coordinate;

[0015] Use linear interpolation to interpolate on the current column according to the index to get the upsampled horizontal coordinates.

[0016] Optionally, the process of obtaining the parameters of the fitted line includes the following steps:

[0017] The vascular wall position in polar coordinates was converted to a rectangular coordinate system, the longitudinal coordinates were divided into multiple groups, and the mean square error was calculated for each group of points; values ​​greater than three times the mean square error were considered as outliers and eliminated;

[0018] Perform the least square linear fit on the removed points with the left and right points to calculate the coordinates of the originally removed points;

[0019] Repeat the mean square error calculation and least squares linear fitting until all points are calculated and all outliers are eliminated.

[0020] Optionally, the process of obtaining the cross-correlation spectrum includes the following steps:

[0021] The acquired data are subjected to coordinate transformation, and the position of the blood vessel wall in polar coordinates is converted into the position in rectangular coordinates; cross-correlation calculation is performed on each time step, and each time step is regarded as an independent data frame, and cross-correlation calculation is performed on the time frame;

[0022] By performing cross-correlation calculations, a three-dimensional structure is obtained. The three-dimensional structure represents the changes in the position of the blood vessel wall and is used to analyze the dynamic evolution and change rules of the blood vessel wall morphology.

[0023] Obtain the target coordinates in the rectangular coordinate system, and in the three-dimensional cross-correlation structure, take out the corresponding coordinate points according to the position of the target coordinates; expand the coordinate points in all time dimensions to obtain a new two-dimensional structure with a scaled cross-correlation spectrum.

[0024] Optionally, the cross-correlation operation process includes the following steps:

[0025] A reference signal is selected, and the reference signal is the blood vessel wall position data at a certain time point; a certain time point refers to a specific time point selected in a time series, which is any time point therein;

[0026] The reference signal is multiplied point by point with the blood vessel wall position data at other time points, and the sum is calculated to obtain the cross-correlation value; other time points refer to other time points except the selected reference time point, which are other time points in the same time series;

[0027] By repeating the calculation steps and performing cross-correlation calculation on all time points, a cross-correlation sequence can be obtained, which indicates the degree of correlation between the reference signal and the blood vessel wall position data at other time points.

[0028] Optionally, the process of obtaining a corrected curved array ultrasound pulse wave velocity measurement value comprises the following steps:

[0029] Calculate the physical distance between each point and the previous point, traverse all points, and add up the physical distance between each point and the previous point to get the physical length of the target curve;

[0030] In the cross-correlation spectrum, find the extreme value along the horizontal direction to obtain the coordinates of the maximum value; sum up the physical lengths of each group of midpoints and calculate the time difference experienced;

[0031] The segmented pulse wave velocity is calculated, and overlapping sampling is added during the segmentation process to obtain the corrected curved array ultrasound pulse wave conduction velocity value.

[0032] Optionally, the physical distance calculation process includes the following steps:

[0033] According to the given coordinates, for each point, calculate the difference between its coordinates and the previous point, then calculate the sum of their squares, and perform square root operation;

[0034] Multiply the result by the pixel spacing to get the physical distance between the points;

[0035] After traversing all the points, the physical length of the target curve can be obtained.

[0036] Optionally, the process of calculating the segmented pulse wave velocity comprises the following steps:

[0037] By searching for extreme values ​​along the horizontal direction of the cross-correlation spectrum, multiple maximum value coordinates are obtained; the time difference experienced by the maximum value coordinates is calculated by the sum of the physical lengths of certain points in each group; the time difference is obtained by multiplying the horizontal axis coordinate after least squares fitting of the coordinate by the frame rate during data acquisition;

[0038] The segmented pulse wave velocity is calculated as the physical length / time difference of certain points in each group; overlapping sampling of certain points is added during the segmentation process;

[0039] The corrected curved array ultrasonic pulse wave velocity value can be obtained by taking the average value of all calculated ultrasonic pulse wave velocity values.

[0040] The present invention provides a pulse wave transmission velocity measurement and correction system based on a curved array, comprising:

[0041] The coordinate replacement module is responsible for acquiring the ultrasound image, converting the point coordinates in the polar coordinate system into the coordinates in the rectangular coordinate system, replacing the abnormal points in the rectangular coordinates of the vascular wall position by linear fitting, and obtaining the coordinates after replacing the abnormal value points;

[0042] The three-dimensional construction module is responsible for performing cross-correlation calculation on the transformed coordinates to obtain the three-dimensional structure; replacing the target coordinate points in the coordinates after the outlier points, extracting the corresponding coordinate points from the three-dimensional structure, and expanding them to obtain the cross-correlation spectrum;

[0043] The numerical calculation module is responsible for finding extreme values ​​in the cross-correlation spectrum and calculating the total physical length and time difference of each group of points; calculating the segmented ultrasonic pulse wave conduction velocity measurement according to the time difference, taking the average value of the ultrasonic pulse wave conduction velocity measurement of each segment, and obtaining the corrected curved array ultrasonic pulse wave conduction velocity measurement value.

[0044] The present invention converts the coordinates of a point in a polar coordinate system into coordinates in a rectangular coordinate system, removes outliers and performs linear fitting; by coordinate conversion and outlier removal, accurate blood vessel wall position coordinates can be obtained, which helps to improve the accuracy and reliability of measurement and eliminate the influence of outliers on subsequent calculations. The transformed coordinates are cross-correlated to obtain a three-dimensional structure; the target coordinate points are extracted and expanded to obtain a cross-correlation spectrum; by cross-correlation calculation and spectrum expansion, time series information of blood vessel wall movement can be obtained, which helps to analyze the movement characteristics of the blood vessel wall and extract information on pulse wave conduction velocity. Find the extreme value in the cross-correlation spectrum, calculate the sum of the physical lengths of the points and the time difference; calculate the ultrasonic pulse wave conduction velocity measurement based on the time difference, and take the average value to obtain the corrected measurement value; by finding the extreme value and calculating the time difference, the pulse wave conduction velocity can be quantified, which helps to accurately measure the elasticity and blood flow rate of the blood vessels and evaluate the function and health status of the cardiovascular system.

[0045] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0046] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0048] Figure 1 Flow chart of the pulse wave velocity measurement and correction method based on curved array in Example 1 of the present invention;

[0049] Figure 2 A diagram showing the process of obtaining coordinates after replacing outlier points in Embodiment 2 of the present invention;

[0050] Figure 3 This is a process diagram of normalizing a rectangular coordinate system in Embodiment 3 of the present invention;

[0051] Figure 4This is a process diagram for obtaining parameters of a fitted straight line in Example 4 of the present invention;

[0052] Figure 5 is a process diagram of obtaining a cross-correlation spectrum in Example 5 of the present invention;

[0053] Figure 6 is a process diagram of the cross-correlation operation in Embodiment 6 of the present invention;

[0054] Figure 7 This is a process diagram of obtaining the corrected curved array ultrasound pulse wave velocity measurement value in Example 7 of the present invention;

[0055] Figure 8 4 is a diagram of a calculation process of a physical distance in Embodiment 8 of the present invention;

[0056] Fig. 9 is a process diagram of calculating segmented pulse wave velocity in embodiment 9 of the present invention;

[0057] Fig.10 This is a block diagram of a pulse wave velocity measurement and correction system based on a curved array in Example 10 of the present invention. DETAILED DESCRIPTION

[0058] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0059] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms of "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0060] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0061] Example 1: Figure 1As shown, an embodiment of the present invention provides a pulse wave velocity measurement and correction method based on a curved array, comprising the following steps:

[0062] S100: Acquire an ultrasound image, convert the coordinates of a point in a polar coordinate system into coordinates in a rectangular coordinate system, replace the abnormal point in the rectangular coordinate system of the blood vessel wall position by linear fitting, and obtain the coordinates after the abnormal value point is replaced;

[0063] S200: performing cross-correlation calculation on the transformed coordinates to obtain a three-dimensional structure; replacing the target coordinate points in the coordinates after the outlier points, extracting corresponding coordinate points from the three-dimensional structure, and expanding them to obtain a cross-correlation spectrum;

[0064] S300: Find extreme values ​​in the cross-correlation spectrum, and calculate the total physical length and time difference of each group of points; calculate the segmented ultrasonic pulse wave conduction velocity measurement according to the time difference, take the average value of the ultrasonic pulse wave conduction velocity measurement of each segment, and obtain the corrected curved array ultrasonic pulse wave conduction velocity measurement value.

[0065] The working principle and beneficial effects of the above technical solution are as follows: the present embodiment first obtains an ultrasonic image, converts the point coordinates in the polar coordinate system into coordinates in the rectangular coordinate system, replaces the abnormal points in the rectangular coordinate system of the vascular wall position by linear fitting, and obtains the coordinates after replacing the abnormal value points; secondly, the transformed coordinates are cross-correlated to obtain a three-dimensional structure; the target coordinate points in the coordinates after replacing the abnormal value points are extracted from the three-dimensional structure, and the cross-correlation spectrum is obtained by expansion; finally, the extreme values ​​are found in the cross-correlation spectrum, and the sum of the physical lengths and the time difference of each group of points are calculated; the segmented ultrasonic pulse wave conduction velocity measurement is calculated according to the time difference, and the average value of each segment of the ultrasonic pulse wave conduction velocity measurement is taken to obtain the corrected curved array ultrasonic pulse wave conduction velocity measurement value. Step S100 of the above solution converts the point coordinates in the polar coordinate system into coordinates in the rectangular coordinate system, removes the abnormal values ​​and performs linear fitting; through coordinate conversion and outlier removal, accurate vascular wall position coordinates can be obtained, which helps to improve the accuracy and reliability of measurement and eliminate the influence of abnormal values ​​on subsequent calculations. Step S200 performs cross-correlation calculation on the transformed coordinates to obtain a three-dimensional structure; extracts the target coordinate point and expands it to obtain a cross-correlation spectrum; through cross-correlation calculation and spectrum expansion, the time series information of the vascular wall movement can be obtained, which is helpful for analyzing the movement characteristics of the vascular wall and extracting the information of the pulse wave conduction velocity. Step S300 searches for the extreme value in the cross-correlation spectrum, calculates the sum of the physical lengths of the points and the time difference; calculates the ultrasonic pulse wave conduction velocity measurement based on the time difference, and takes the average value to obtain the corrected measurement value; by searching for extreme values ​​and calculating the time difference, the pulse wave conduction velocity can be quantified, which is helpful for accurately measuring the elasticity and blood flow rate of the blood vessels and evaluating the function and health of the cardiovascular system.

[0066] In summary, through the above steps, this embodiment can use a curved array to perform correction on ultrasonic pulse wave velocity measurement. Accurate coordinates of the blood vessel wall position are obtained through coordinate transformation, outlier elimination and linear fitting. Information on pulse wave velocity is extracted through cross-correlation calculation and spectrum expansion. The pulse wave velocity is accurately measured by finding extreme values ​​and calculating time differences; this helps to improve the accuracy and reliability of the measurement and evaluate the function and health of the cardiovascular system. Through the above steps, the blood vessel wall position in the polar coordinate system can be converted into coordinates in the rectangular coordinate system, and cross-correlation calculation and analysis can be performed to obtain the PWV value of the curved array, which helps to quantitatively analyze the movement of the blood vessel wall and the blood flow velocity, and provides an assessment of cardiac function and vascular health.

[0067] Example 2: Figure 2 As shown, based on Example 1, the process of obtaining the coordinates after replacing the outlier point provided in the embodiment of the present invention includes the following steps:

[0068] S101: Acquire an ultrasound image containing position information of a blood vessel wall, and perform a rectangular coordinate system conversion for each polar coordinate point of the blood vessel wall position;

[0069] The polar coordinate point (r, θ) at each blood vessel wall position uses trigonometric functions to calculate the cosine and sine values ​​of the polar angle θ (the angle between the polar coordinate point and the polar axis): cos(θ) and sin(θ); the polar diameter r (the distance from the polar coordinate point to the pole) is multiplied by cos(θ) to obtain the horizontal coordinate x in the rectangular coordinate system; the polar diameter r is multiplied by sin(θ) to obtain the vertical coordinate y in the rectangular coordinate system, and the coordinates of the point in the converted rectangular coordinate system (x, y) are obtained;

[0070] The trigonometric function relationship is used to convert the coordinates (r, θ) of the polar coordinate point into the coordinates (x, y) in the rectangular coordinate system. The specific conversion formula is as follows:

[0071] x=r*cos(θ)

[0072] y=r*sin(θ)

[0073] Among them, cos(θ) represents the cosine value of the polar angle θ, and sin(θ) represents the sine value of the polar angle θ. Get x, y in the rectangular coordinate system;

[0074] S102: calculating the mean square error of the longitudinal coordinates in the rectangular coordinate system in sections, comparing it with the value under the mean square error, detecting and replacing the outlier points in the point coordinates in the rectangular coordinate system; performing linear fitting on the point coordinates in the rectangular coordinate system after replacing the outlier points using the least squares method to obtain the parameters of the fitting line;

[0075] S103: Calculate and obtain the coordinates of the replaced abnormal value point and replace it, so as to obtain the coordinates of the replaced abnormal value point in the rectangular coordinate system.

[0076] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first obtains an ultrasonic image containing the position information of the blood vessel wall, and performs a rectangular coordinate system conversion for the polar coordinate point of each blood vessel wall position; wherein, the polar coordinate point (r, θ) of each blood vessel wall position uses trigonometric functions to calculate the cosine value and sine value of the polar angle θ (the angle between the polar coordinate point and the polar axis): cos(θ) and sin(θ); multiply the polar diameter r (the distance from the polar coordinate point to the pole) by cos(θ) to obtain the horizontal coordinate x in the rectangular coordinate system; multiply the polar diameter r by sin(θ) (θ), obtain the ordinate y in the rectangular coordinate system, and obtain the point coordinates (x, y) in the converted rectangular coordinate system; secondly, calculate the mean square of the longitudinal coordinates in the rectangular coordinate system in sections, compare it with the value under the variance, detect and replace the outlier points in the point coordinates in the rectangular coordinate system; use the least squares method to perform linear fitting on the point coordinates in the rectangular coordinate system after replacing the outlier points, and obtain the parameters of the fitting line; finally, calculate the coordinates of the replaced outlier points and replace them to obtain the coordinates in the rectangular coordinate system after replacing the outlier points. Step S101 of the above scheme converts the data from the polar coordinate system to the rectangular coordinate system, which is convenient for subsequent processing and analysis of the data; the coordinates in the converted rectangular coordinate system can provide more accurate and convenient data representation. Step S102 detects and eliminates possible outliers to reduce the interference of outliers on data analysis; the discreteness of the data can be quantified by calculating the mean square error, and values ​​exceeding the threshold are regarded as outliers and eliminated. Step S103 estimates the coordinates of the removed outliers by linear fitting and replaces them with estimated values, which can maintain the integrity and continuity of the data and reduce the impact of outliers on data analysis.

[0077] In summary, this embodiment improves the accuracy and reliability of data, and the removal of outliers can reduce the interference of noise and abnormal points on data analysis, while linear fitting can fill the removed outliers to make the data more complete and continuous. Through these processes, the position of the vascular wall can be better analyzed and studied, useful information and features can be extracted, and support can be provided for subsequent medical diagnosis and treatment. Through the above steps, the coordinates of the points in the polar coordinate system can be converted to the coordinates in the rectangular coordinate system; the conversion helps to perform subsequent outlier removal and linear fitting in the rectangular coordinate system; the converted coordinates can provide a more convenient and accurate data representation for further analysis and processing.

[0078] Example 3: Figure 3 As shown, based on Example 2, the process of normalizing the rectangular coordinate system provided by the embodiment of the present invention includes the following steps:

[0079] S1011: Obtain the size of the current ultrasound image, calculate the axial point spacing of the current image, calculate the lateral point spacing based on the axial point spacing, and then calculate the upsampling multiple of the lateral coordinate;

[0080] S1012: Upsampling each transverse coordinate, traversing each column (transverse) of the current ultrasound image from left to right; for each column, calculating the index of the current transverse coordinate;

[0081] S1013: Use linear interpolation to interpolate on the current column according to the index to obtain the upsampled horizontal coordinate.

[0082] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first obtains the size of the current ultrasound image, calculates the axial point spacing of the current image, calculates the lateral point spacing based on the axial point spacing, and then calculates the upsampling multiple of the lateral coordinate; secondly, upsamples each lateral coordinate, traverses each column (lateral) of the current ultrasound image, from left to right; for each column, calculates the index of the current lateral coordinate; finally, linear interpolation is used to interpolate on the current column according to the index to obtain the upsampled lateral coordinate. Step S1011 of the above solution can obtain the basic units of the axial and lateral directions by obtaining the image size and calculating the point spacing, providing accurate parameters for subsequent normalization processing; by calculating the point spacing and the upsampling multiple, the axial and lateral directions of the image can be unified into the same basic units, which is convenient for unified processing and analysis of the data; the normalization process can maintain the consistency and comparability of the data, which is convenient for the application of subsequent algorithms and models. Step S1012 can determine the position of each horizontal coordinate in the normalized coordinate system by traversing each column and calculating the index; by traversing each column and calculating the index, the horizontal coordinate can be upsampled so that the axial and lateral point spacings are equal, which can maintain the consistency of the data and facilitate subsequent analysis and processing. Step S1013 can obtain the upsampled horizontal coordinates by linear interpolation on the current column according to the index; through interpolation, the horizontal coordinates can be supplemented and refined in the upsampled coordinate system, which can make the data more continuous and complete, and improve the accuracy of subsequent processing and analysis. This embodiment uses the axial distance before normalization as the basic unit, and upsamples the horizontal coordinates so that the axial and lateral point spacings are equal; the consistency of the axial and lateral coordinates can be maintained, which is convenient for subsequent analysis and processing.

[0083] This embodiment specifically includes the following steps:

[0084] Get the size of the current image as [m, n], where m represents the axial (longitudinal) size of the image and n represents the horizontal size of the image;

[0085] Calculate the axial point spacing ΔAxis of the current image, which is calculated using the following formula:

[0086] ΔAxis = image axial span / (m-1)

[0087] According to ΔAxis, calculate the horizontal point spacing ΔHorizontal, which is calculated by the following formula:

[0088] ΔHorizontal=ΔAxis*(n-1)

[0089] Calculate the upsampling multiple ratio of the horizontal coordinates, which is calculated using the following formula:

[0090] ratio=ΔHorizontal / ΔPixel

[0091] The axial distance ΔPixel before normalization is used as the basic unit;

[0092] Upsample each horizontal coordinate. The specific steps are as follows:

[0093] Traverse each column (horizontally) of the current image, from left to right;

[0094] For each column, calculate the index of the current horizontal coordinate, which can be calculated by the following formula:

[0095] index = current column index * ratio

[0096] Use an interpolation method (such as linear interpolation) to interpolate on the current column according to index to obtain the upsampled horizontal coordinates.

[0097] Example 4: Figure 4 As shown, based on Example 2, the process of obtaining the parameters of the fitting straight line provided in the embodiment of the present invention includes the following steps:

[0098] S1021: converting the vascular wall position in polar coordinates to a rectangular coordinate system, dividing the longitudinal coordinates into multiple groups, and calculating the mean square error for each group of points; values ​​greater than three times the mean square error are considered as abnormal values ​​and are removed;

[0099] S1022: performing least square linear fitting on the removed point with the left and right points to calculate the coordinates of the originally removed point;

[0100] S1023: Repeat S1021-S1022 until all points are calculated and all outliers are eliminated.

[0101] The working principle and beneficial effects of the above technical solution are as follows: This embodiment first converts the vascular wall position under polar coordinates to a rectangular coordinate system, divides the longitudinal coordinates into multiple groups, and calculates the mean square error for each group of points; values ​​greater than three times the mean square error are regarded as outliers and eliminated; secondly, the eliminated points are fitted with the left and right points by least square linear fitting to calculate the coordinates of the originally eliminated points; finally, S1021-S1022 are repeated until all points are calculated and the outliers are eliminated. Step S1021 of the above solution can identify and eliminate outliers by converting the vascular wall position under polar coordinates to a rectangular coordinate system and calculating the mean square error for the longitudinal coordinate groups; eliminating outliers can improve the accuracy and reliability of the data and ensure the accuracy of subsequent processing and analysis; by calculating the mean square error, the threshold of outliers can be determined to further filter out data that may have problems. Step S1022 estimates the coordinates of the removed points based on the left and right points of the removed points by least squares linear fitting; the removed outliers can be corrected and filled to a certain extent by least squares linear fitting, making the data more complete and continuous, maintaining the consistency of the data, and improving the accuracy of subsequent processing and analysis. Step S1023 ensures that all outliers are properly processed and corrected by repeatedly executing S1021 and S1022 until all points are calculated; more accurate and reliable blood vessel wall position data can be obtained by eliminating and correcting outliers, which can improve the reliability of subsequent processing and analysis and provide more accurate information for blood vessel wall morphology analysis and disease diagnosis.

[0102] In summary, this embodiment transforms the vascular wall position in polar coordinates in a rectangular coordinate system through the above process and removes abnormal values; thus, new vascular wall position coordinates after processing can be obtained, thereby ensuring the accuracy and reliability of the data.

[0103] In this embodiment, the position of the blood vessel wall in the input polar coordinates is transformed into a rectangular coordinate system, where the longitudinal coordinates of the k points are [n1, n2, n 3, ....,n k ], the axial coordinates are [m,m2,m 3, ....,m k ] Calculate the mean square error for each group of p n points in the longitudinal coordinates, and take the value (m abnor ,n abnor ) are considered as outliers and removed. The removed points are fitted with the least squares linear method with d points on the left and right (d≥2), and then the coordinates of the original removed points are calculated and replaced to obtain the new (mm abnornew ,n abnornew ); Repeat this step until all k points have been calculated, and we can get [N1, N2, N3, ...., Nk ] and [M1,M2,M3,....,M k ].

[0104] Example 5: Figure 5 As shown, based on Example 1, the process of obtaining the cross-correlation spectrum provided in the embodiment of the present invention includes the following steps:

[0105] S201: performing coordinate transformation on the acquired data, converting the position of the blood vessel wall in polar coordinates into the position in a rectangular coordinate system; performing cross-correlation calculation on each time step, treating each time step as an independent data frame, and performing cross-correlation calculation on the time frame;

[0106] S202: obtaining a three-dimensional structure by performing cross-correlation calculation, wherein the three-dimensional structure represents the change in the position of the blood vessel wall and is used to analyze the dynamic evolution and change law of the blood vessel wall morphology;

[0107] S203: Obtain the target coordinates in a rectangular coordinate system, and in the three-dimensional cross-correlation structure, extract the corresponding coordinate points according to the positions of the target coordinates; expand the coordinate points in all time dimensions to obtain a new two-dimensional structure with a scaled cross-correlation spectrum;

[0108] In the two-dimensional structure, the horizontal axis represents time and the vertical axis represents physical distance. The changes of the target coordinate point at different time points can be observed and associated with the physical distance. By analyzing the cross-correlation spectrum, the dynamic change characteristics of the blood vessel wall can be studied and understood, which is of great significance for blood vessel wall morphology analysis and disease diagnosis.

[0109] The working principle and beneficial effects of the above technical solution are as follows: the present embodiment first transforms the collected data into coordinates, converts the position of the vascular wall in polar coordinates into the position in rectangular coordinates; performs cross-correlation calculation on each time step, takes each time step as an independent data frame, and performs cross-correlation calculation on the time frame; secondly, a three-dimensional structure is obtained by performing cross-correlation calculation, and the three-dimensional structure represents the change of the position of the vascular wall, which is used to analyze the dynamic evolution and change law of the vascular wall morphology; finally, the target coordinates in the rectangular coordinate system are obtained, and in the three-dimensional cross-correlation structure, the corresponding coordinate points are taken out according to the position of the target coordinates; the coordinate points are expanded in all time dimensions to obtain a new two-dimensional structure with a scaled cross-correlation spectrum. Step S201 of the above solution converts the data from the polar coordinate system into the rectangular coordinate system and performs cross-correlation calculation; through such processing, the dynamic information of the position of the vascular wall can be extracted, including the change and dynamic evolution of the morphology, which is helpful for further analysis and research on the characteristics and change law of the vascular wall. Step S202 can obtain the three-dimensional structure of the position of the vascular wall through cross-correlation calculation. This structure can be used to observe and analyze the dynamic change characteristics of the vascular wall, which is helpful to understand the morphological evolution, change law and dynamic characteristics of the vascular wall, and provide an important basis for subsequent morphological analysis and disease diagnosis. Step S203 can obtain a cross-correlation spectrum with scale by extracting the corresponding coordinate points according to the target coordinate position in the three-dimensional cross-correlation structure and expanding it into a two-dimensional structure. The cross-correlation spectrum can show the change law of the target coordinate point in time and associate it with the physical distance, which is helpful to analyze and study the dynamic change characteristics of the vascular wall, and provide important information and guidance for vascular wall morphological analysis, disease diagnosis and treatment.

[0110] In this embodiment, the acquired data is subjected to coordinate transformation in step S100 and then cross-correlation calculation is performed between e frames, so that a three-dimensional structure with a scale of [m, n, q] can be obtained, where q is the time length after cross-correlation calculation of all ultrafast acquisition frames; the obtained target coordinates [N1, N2, N3, ...., N k ] and [M1,M2,M3,....,M k ] Taking out the coordinate points in the [m,n,q] cross-correlation three-dimensional structure and expanding all the lengths q can obtain a cross-correlation spectrum with a scale of [k,q], where the horizontal axis represents time and the vertical axis represents physical distance.

[0111] Example 6: Figure 6 As shown, based on Example 5, the process of cross-correlation calculation provided by the embodiment of the present invention includes the following steps:

[0112] S2011: Select a reference signal, where the reference signal is the blood vessel wall position data at a certain time point; the certain time point refers to a specific time point selected in a time series, which can be any time point therein.

[0113] S2012: multiplying the reference signal by the blood vessel wall position data at other time points point by point, and summing the results to obtain a cross-correlation value; the other time points refer to other time points except the selected reference time point, which are also other time points in the same time series;

[0114] Assume that the reference signal is x(t) and the blood vessel wall position data at other time points is y(t);

[0115] Multiply x(t) and y(t) point by point to obtain the product signal z(t)=x(t)*y(t);

[0116] Time-shift the product signal z(t) to obtain the shifted signal z′(t);

[0117] The shifted signal z′(t) is summed to obtain a cross-correlation value C(t)=∑z′(t);

[0118] S2013: Repeat the calculation steps and perform cross-correlation calculation on all time points to obtain a cross-correlation sequence C(t), which represents the correlation between the reference signal and the blood vessel wall position data at other time points.

[0119] The working principle and beneficial effects of the above technical solution are as follows: the present embodiment first selects a reference signal, which is the blood vessel wall position data at a certain time point; secondly, the reference signal is point-by-point multiplied with the blood vessel wall position data at other time points, and the cross-correlation value is obtained by summing up; assuming that the reference signal is x(t), and the blood vessel wall position data at other time points is y(t); x(t) and y(t) are point-by-point multiplied to obtain a product signal z(t)=x(t)*y(t); the product signal z(t) is time-shifted to obtain a shifted signal z′(t); the shifted signal z′(t) is summed to obtain a cross-correlation value C(t)=∑z′(t); finally, the calculation steps are repeated to perform cross-correlation calculations on all time points, and a cross-correlation sequence C(t) can be obtained, which indicates the degree of correlation between the reference signal and the blood vessel wall position data at other time points. Step S2011 of the above solution selects a reference signal as a reference point, which can be used to compare the blood vessel wall position data at other time points, so as to analyze the dynamic change characteristics of the blood vessel wall position. Step S2012 can calculate the cross-correlation value between the reference signal and the vascular wall position data at other time points through point-by-point multiplication and summation operations. The cross-correlation value can reflect the degree of correlation between the vascular wall positions, and thus can be used to analyze the similarity and correlation of the vascular wall position data. Step S2013 can obtain a cross-correlation sequence C(t) by performing cross-correlation calculations on all time points, which is used to describe the degree of correlation between the reference signal and the vascular wall position data at other time points; by analyzing this cross-correlation sequence, the dynamic change characteristics of the vascular wall position data, including similarity, correlation and change rules, can be understood; it is of great significance for vascular wall morphology analysis and disease diagnosis, and can provide relevant information and guidance on vascular wall morphology and function.

[0120] Example 7: Figure 7 As shown, based on Example 1, the process of obtaining the corrected curved array ultrasound pulse wave velocity measurement value provided by the embodiment of the present invention includes the following steps:

[0121] S301: Calculate the physical distance between each point and the previous point, traverse all points, and accumulate the physical distance between each point and the previous point to obtain the physical length of the target curve;

[0122] S302: In the cross-correlation spectrum, find the extreme value along the horizontal direction to obtain the coordinates of the maximum value; sum up the physical lengths of each group of midpoints to calculate the time difference experienced;

[0123] S303: Calculate the segmented pulse wave velocity. In the segmentation process, overlapping sampling is added to obtain the corrected curved array ultrasound pulse wave conduction velocity value.

[0124] The working principle and beneficial effects of the above technical solution are as follows: the present embodiment first calculates the physical distance between each point and the previous point, traverses all points, and accumulates the physical distance between each point and the previous point to obtain the physical length of the target curve; secondly, in the cross-correlation spectrum, the extreme value is found along the horizontal direction to obtain the maximum value coordinate; the physical length of each group of midpoints is summed up to calculate the time difference experienced; finally, the segmented pulse wave velocity is calculated, and in the segmentation process, overlapping sampling is added to obtain the corrected curved array ultrasonic pulse wave conduction velocity value. Step S301 of the above solution can obtain the real arc length of the target curve by calculating and accumulating the physical distance between points, which helps to understand the morphological characteristics and length information of the curve and provides a basis for subsequent ultrasonic pulse wave conduction velocity measurement. Step S302 can determine the specific point on the target curve by finding the extreme value coordinates in the cross-correlation spectrum, and can obtain the segmented ultrasonic pulse wave velocity (PWV) by calculating the sum of the physical lengths of each group of midpoints and the time difference experienced; the elasticity of the vascular wall and the pulse wave velocity can be analyzed to evaluate the vascular function and health status. Step S303 can obtain the local elasticity of the vascular wall and the pulse wave velocity information by calculating the segmented pulse wave velocity; adding overlapping sampling in the segmentation process can improve the measurement accuracy and noise resistance; finally, all the calculated ultrasonic pulse wave velocity values ​​are averaged to obtain the corrected curved array ultrasonic pulse wave velocity value, which is used to evaluate vascular function and disease diagnosis.

[0125] In summary, through these steps, this embodiment can measure and analyze the curved array ultrasound pulse wave velocity, providing accurate and reliable information for vascular wall morphology analysis, vascular function assessment and disease diagnosis.

[0126] Example 8: Figure 8 As shown, based on Example 7, the calculation process of the physical distance provided in this embodiment of the present invention includes the following steps:

[0127] S3011: According to the given coordinates, for each point, the coordinate difference between it and the previous point is calculated, and then the sum of the squares is calculated, and a square root operation is performed;

[0128] S3012: Multiply the result by the pixel spacing to obtain the physical distance between the points;

[0129] S3013: After traversing all the points, the physical length of the target curve can be obtained.

[0130] The working principle and beneficial effects of the above technical solution are as follows: First, according to the given coordinates, for each point, the coordinate difference between the point and the previous point is calculated, and then the sum of the squares is calculated and the square root operation is performed; secondly, the result is multiplied by the pixel spacing to obtain the physical distance between the points; finally, after traversing all the points, the physical length of the target curve can be obtained. Step S3011 of the above solution can obtain the Euclidean distance between the points by calculating the square root of the sum of the squares of the coordinate differences between the points; this distance can be used to measure the physical distance between the two points and used for subsequent physical length calculations. Step S3012 can convert the distance from the pixel unit to the actual physical distance unit by multiplying the Euclidean distance between the points by the pixel spacing, which helps to convert the coordinate data into the length information in the real world, so as to perform further analysis and application. Step S3013 can obtain the total physical length of the target curve by traversing all the points and accumulating the physical distance between them and the previous point. This length information can be used to measure the morphological characteristics and size of the curve, providing a basic basis for subsequent data analysis, vascular function assessment and disease diagnosis.

[0131] In summary, through these steps, this embodiment can calculate the physical distance between points and obtain the physical length of the target curve. This length information can be used for vascular wall morphology analysis, vascular function assessment and disease diagnosis, providing accurate and reliable data support for clinical applications.

[0132] In this embodiment, the coordinates [N1, N2, N3, ...., N k ] and [M1,M2,M3,....,M k ] The method of calculating the actual arc length and the physical distance ΔL between points using the axial point spacing ΔPixel length is as follows:

[0133]

[0134] After traversing k points, the physical length of the target curve can be obtained.

[0135] Example 9: Fig. 9 As shown, based on Example 7, the process of calculating the segmented pulse wave velocity provided by the embodiment of the present invention includes the following steps:

[0136] S3031: by searching for extreme values ​​along the horizontal direction of the cross-correlation spectrum, a plurality of maximum value coordinates are obtained; the time difference experienced by the maximum value coordinates is calculated by the sum of the physical lengths of certain points in each group; the time difference is obtained by multiplying the horizontal axis coordinate after least squares fitting of the coordinate by the frame rate during data acquisition;

[0137] S3032: The segmented pulse wave velocity is calculated as the physical length / time difference of certain points in each group; overlapping sampling of certain points is added during the segmentation process;

[0138] S3033: Taking the average value of all calculated ultrasonic pulse wave velocity values, a corrected curved array ultrasonic pulse wave velocity value can be obtained.

[0139] The working principle and beneficial effects of the above technical solution are as follows: the present embodiment first obtains multiple maximum value coordinates by searching for extreme values ​​along the horizontal direction of the cross-correlation spectrum; the time difference experienced by the maximum value coordinates is calculated by the sum of the physical lengths of certain points in each group; the time difference is obtained by multiplying the horizontal axis coordinate after least squares fitting of the coordinates by the frame rate during data acquisition; secondly, the segmented pulse wave velocity is calculated as the physical length / time difference of certain points in each group; overlapping sampling of certain points is added in the segmentation process; finally, all the calculated ultrasonic pulse wave conduction velocity values ​​are averaged to obtain the corrected curved array ultrasonic pulse wave conduction velocity value. Step S3031 of the above solution can determine a specific point on the target curve by searching for extreme value coordinates in the cross-correlation spectrum; then, by calculating the sum of the physical lengths of certain points in each group and the time difference experienced, the segmented pulse wave velocity can be obtained; it is helpful to analyze the elasticity of the vascular wall and the conduction velocity of the pulse wave, and then evaluate the vascular function and health status. Step S3032: By calculating the physical length of each group of certain points divided by the time difference, the segmented pulse wave velocity can be obtained. This velocity value reflects the rate at which the pulse wave propagates in the blood vessel and is used to evaluate the elasticity of the blood vessel and the pulse wave conduction velocity. Adding overlapping sampling of certain points in the segmentation process can improve the noise resistance and accuracy of the calculated pulse wave velocity. Step S3033: By taking the average value of all calculated ultrasonic pulse wave conduction velocity values, the corrected curved array ultrasonic pulse wave conduction velocity value can be obtained. This value represents the average pulse wave conduction velocity of the entire target curve and is used to evaluate vascular function and disease diagnosis. By taking the average value, the calculation error can be reduced and the stability and reliability of the results can be improved.

[0140] In summary, through these steps, this embodiment can calculate the segmented pulse wave velocity, and improve the accuracy and reliability of the calculation result by overlapping sampling and averaging methods; the corrected curved array ultrasound pulse wave velocity value can be used for vascular wall morphology analysis, vascular function assessment and disease diagnosis, providing accurate and reliable data support for clinical applications.

[0141] In this embodiment, the cross-correlation spectrum is searched for extreme values ​​along the horizontal direction, and k maximum value coordinates [K1, K2, K3, ..., K k ], and calculate [K1,...,Kp ], the time difference is the horizontal axis coordinate after the least squares fitting of the coordinate * ΔPRF, where PRF is the frame rate during data acquisition; the segmented PWV is abs(physical length of each group of p points / time difference), where abs() is the absolute value of the result; adding overlapping sampling of p points in the segmentation process can improve the noise resistance of the calculated PWV; taking the average of the calculated PWV values ​​can get the corrected curved array PWV value.

[0142] Example 10: Fig.10 As shown, based on Embodiments 1 to 9, the pulse wave transmission velocity measurement and correction system based on the curved array provided in the embodiment of the present invention comprises:

[0143] The coordinate replacement module is responsible for acquiring the ultrasound image, converting the point coordinates in the polar coordinate system into the coordinates in the rectangular coordinate system, replacing the abnormal points in the rectangular coordinates of the vascular wall position by linear fitting, and obtaining the coordinates after replacing the abnormal value points;

[0144] The three-dimensional construction module is responsible for performing cross-correlation calculation on the transformed coordinates to obtain the three-dimensional structure; replacing the target coordinate points in the coordinates after the outlier points, extracting the corresponding coordinate points from the three-dimensional structure, and expanding them to obtain the cross-correlation spectrum;

[0145] The numerical calculation module is responsible for finding extreme values ​​in the cross-correlation spectrum and calculating the total physical length and time difference of each group of points; calculating the segmented ultrasonic pulse wave conduction velocity measurement according to the time difference, taking the average value of the ultrasonic pulse wave conduction velocity measurement of each segment, and obtaining the corrected curved array ultrasonic pulse wave conduction velocity measurement value.

[0146] The working principle and beneficial effects of the above technical solution are as follows: the coordinate replacement module of this embodiment obtains the ultrasound image, converts the point coordinates in the polar coordinate system into the coordinates in the rectangular coordinate system, replaces the abnormal points in the rectangular coordinates of the vascular wall position by linear fitting, and obtains the coordinates after replacing the abnormal value points; the three-dimensional construction module performs cross-correlation calculation on the transformed coordinates to obtain a three-dimensional structure; the target coordinate points in the coordinates after replacing the abnormal value points are extracted from the three-dimensional structure, and the cross-correlation spectrum is obtained by expansion; the numerical calculation module finds extreme values ​​in the cross-correlation spectrum, and calculates the sum of the physical lengths and time differences of each group of points; the segmented ultrasonic pulse wave conduction velocity measurement is calculated according to the time difference, and the ultrasonic pulse wave conduction velocity measurement of each segment is averaged to obtain the corrected curved array ultrasonic pulse wave conduction velocity measurement value. The coordinate replacement module of the above scheme can obtain more accurate and reliable coordinates of the vascular wall position by eliminating abnormal values ​​and performing linear fitting, and provide accurate input data for subsequent three-dimensional construction and numerical calculation. The three-dimensional construction module can convert the morphological information of the blood vessel wall into a cross-correlation spectrum through three-dimensional construction and expansion, which helps to extract the characteristics and morphology of the pulse wave and provide a basis for the subsequent ultrasonic pulse wave conduction velocity measurement. The numerical calculation module can obtain segmented ultrasonic pulse wave conduction velocity measurements by finding the extreme values ​​in the cross-correlation spectrum and calculating the sum of physical lengths and time differences; taking the average value of each segment's measurement value can obtain the corrected curved array ultrasonic pulse wave conduction velocity measurement value; this value can be used to evaluate the elasticity of the blood vessel and the conduction velocity of the pulse wave, providing an important indicator for vascular function evaluation and disease diagnosis.

[0147] In summary, through these modules, the pulse wave velocity measurement and correction system based on the curved array in this embodiment can eliminate abnormal values, construct a three-dimensional structure, and calculate the segmented ultrasonic pulse wave velocity, and finally obtain the corrected curved array ultrasonic pulse wave velocity measurement value; improve the accuracy, reliability and stability of the measurement, and provide accurate pulse wave velocity data for vascular function evaluation and disease diagnosis.

[0148] Embodiment 11: Based on Embodiment 10, the coordinate replacement module provided in the embodiment of the present invention includes:

[0149] The coordinate conversion submodule is responsible for acquiring the ultrasound image containing the position information of the blood vessel wall and performing rectangular coordinate conversion for the polar coordinate point of each blood vessel wall position;

[0150] The polar coordinate point (r, θ) at each blood vessel wall position uses trigonometric functions to calculate the cosine and sine values ​​of the polar angle θ (the angle between the polar coordinate point and the polar axis): cos(θ) and sin(θ); the polar diameter r (the distance from the polar coordinate point to the pole) is multiplied by cos(θ) to obtain the horizontal coordinate x in the rectangular coordinate system; the polar diameter r is multiplied by sin(θ) to obtain the vertical coordinate y in the rectangular coordinate system, and the coordinates of the point in the converted rectangular coordinate system (x, y) are obtained;

[0151] The trigonometric function relationship is used to convert the coordinates (r, θ) of the polar coordinate point into the coordinates (x, y) in the rectangular coordinate system. The specific conversion formula is as follows:

[0152] x=r*cos(θ)

[0153] y=r*sin(θ)

[0154] Among them, cos(θ) represents the cosine value of the polar angle θ, and sin(θ) represents the sine value of the polar angle θ. Get x, y in the rectangular coordinate system;

[0155] The parameter acquisition submodule is responsible for calculating the mean square error of the longitudinal coordinates in the rectangular coordinate system in sections, comparing it with the value under the mean square error, detecting and replacing the outlier points in the point coordinates in the rectangular coordinate system; using the least squares method to perform linear fitting on the point coordinates in the rectangular coordinate system after replacing the outlier points, and obtaining the parameters of the fitting line;

[0156] The coordinate replacement submodule is responsible for calculating the coordinates of the replaced outlier point and replacing it, so as to obtain the coordinates in the rectangular coordinate system after the outlier point is replaced.

[0157] The working principle and beneficial effects of the above technical solution are as follows: the coordinate conversion submodule of this embodiment obtains an ultrasonic image containing the position information of the blood vessel wall, and performs a rectangular coordinate system conversion for the polar coordinate point of each blood vessel wall position; wherein, the polar coordinate point (r, θ) of each blood vessel wall position uses trigonometric functions to calculate the cosine value and sine value of the polar angle θ (the angle between the polar coordinate point and the polar axis): cos(θ) and sin(θ); the polar diameter r (the distance from the polar coordinate point to the pole) is multiplied by cos(θ) to obtain the horizontal coordinate x in the rectangular coordinate system; the polar diameter r is multiplied by sin(θ) to obtain the vertical coordinate y in the rectangular coordinate system, and the converted value is obtained. The coordinates of the point in the rectangular coordinate system (x, y); the coordinates of the polar coordinate point (r, θ) are converted into the coordinates in the rectangular coordinate system (x, y) by using the trigonometric function relationship; the parameter acquisition submodule calculates the mean square error of the longitudinal coordinates in the rectangular coordinate system in segments, compares it with the value under the mean square error, detects and replaces the outlier points in the point coordinates in the rectangular coordinate system; the point coordinates in the rectangular coordinate system after replacing the outlier points are linearly fitted using the least squares method to obtain the parameters of the fitting line; the coordinate replacement submodule calculates the coordinates of the replaced outlier point and replaces it to obtain the coordinates in the rectangular coordinate system after replacing the outlier point. The coordinate conversion submodule of the above scheme can convert the coordinate information of the vascular wall position into the form of the rectangular coordinate system by converting the point coordinates in the polar coordinate system into the coordinates in the rectangular coordinate system, providing a standardized data form for subsequent processing and analysis. The parameter acquisition submodule can detect and remove outliers in the point coordinates in the polar coordinate system by calculating the mean square error and comparing it with the threshold. After removing the outliers, the least squares method can be used for linear fitting to obtain the parameters of the fitting line for subsequent data processing and analysis. The coordinate replacement submodule can obtain the coordinates in the rectangular coordinate system after removing the outliers by calculating and replacing the coordinates of the removed points. It can obtain more accurate and reliable coordinates of the vascular wall position, providing accurate input data for subsequent processing and analysis.

[0158] In summary, in this embodiment, through these sub-modules, the coordinate replacement module can convert the point coordinates in the polar coordinate system into coordinates in the rectangular coordinate system, and obtain the coordinates after eliminating outliers through outlier elimination and linear fitting; subsequent processing and analysis can be performed based on accurate and reliable vascular wall position coordinates, thereby improving the accuracy and reliability of the measurement.

[0159] Embodiment 12: Based on Embodiment 10, the three-dimensional building module provided in the embodiment of the present invention comprises:

[0160] The cross-correlation calculation submodule is responsible for coordinate transformation of the collected data, converting the position of the blood vessel wall in polar coordinates into the position in the rectangular coordinate system; performing cross-correlation calculation on each time step, treating each time step as an independent data frame, and performing cross-correlation calculation on the time frame;

[0161] The three-dimensional structure acquisition submodule is responsible for obtaining a three-dimensional structure by performing cross-correlation calculation. The three-dimensional structure represents the change in the position of the vascular wall and is used to analyze the dynamic evolution and change law of the vascular wall morphology;

[0162] The two-dimensional structure acquisition submodule is responsible for obtaining the target coordinates in the rectangular coordinate system. In the three-dimensional cross-correlation structure, the corresponding coordinate points are taken out according to the position of the target coordinates; the coordinate points are expanded in all time dimensions to obtain a new two-dimensional structure with a scaled cross-correlation spectrum;

[0163] In the two-dimensional structure, the horizontal axis represents time and the vertical axis represents physical distance. The changes of the target coordinate point at different time points can be observed and associated with the physical distance. By analyzing the cross-correlation spectrum, the dynamic change characteristics of the blood vessel wall can be studied and understood, which is of great significance for blood vessel wall morphology analysis and disease diagnosis.

[0164] The working principle and beneficial effects of the above technical solution are as follows: the cross-correlation calculation submodule of this embodiment performs coordinate transformation on the collected data, converts the position of the vascular wall in polar coordinates into the position in the rectangular coordinate system; performs cross-correlation calculation on each time step, regards each time step as an independent data frame, and performs cross-correlation calculation on the time frame; the three-dimensional structure acquisition submodule obtains a three-dimensional structure by performing cross-correlation calculation, and the three-dimensional structure represents the change of the position of the vascular wall, which is used to analyze the dynamic evolution and change law of the vascular wall morphology; the two-dimensional structure acquisition submodule obtains the target coordinates in the rectangular coordinate system, and in the three-dimensional cross-correlation structure, according to the position of the target coordinates, the corresponding coordinate points are taken out; the coordinate points are expanded in all time dimensions to obtain a new two-dimensional structure with a cross-correlation spectrum with scale; in the two-dimensional structure, the horizontal axis represents time and the vertical axis represents physical distance, and the changes of the target coordinate points at different time points can be observed and associated with the physical distance; by analyzing the cross-correlation spectrum, the dynamic change characteristics of the vascular wall can be studied and understood, which is of great significance for vascular wall morphology analysis and disease diagnosis. The cross-correlation calculation submodule of the above scheme can convert the position of the vascular wall in polar coordinates into the position in the rectangular coordinate system through coordinate transformation and cross-correlation calculation, and obtain a series of cross-correlation calculation data frames, which provide basic data for subsequent three-dimensional structure acquisition and two-dimensional structure acquisition. The three-dimensional structure acquisition submodule can obtain the dynamic change information of the vascular wall position through three-dimensional structure acquisition, and can analyze the dynamic evolution and change law of the vascular wall morphology, providing important information for vascular function evaluation and disease diagnosis. The two-dimensional structure acquisition submodule can obtain the target coordinates in the rectangular coordinate system through two-dimensional structure acquisition, and take it out from the three-dimensional cross-correlation structure to form a cross-correlation spectrum with scale, which can observe the changes of the target coordinate points at different time points and associate them with the physical distance, so as to analyze the dynamic change characteristics of the vascular wall, and provide important indicators and basis for vascular wall morphology analysis and disease diagnosis.

[0165] In summary, through these sub-modules, the three-dimensional construction module of this embodiment can perform cross-correlation calculations, obtain three-dimensional structures and two-dimensional structures, and thus analyze the dynamic change characteristics of the vascular wall; it helps to understand the morphological evolution and change laws of the vascular wall, and provide important information and guidance for vascular function evaluation and disease diagnosis.

[0166] Embodiment 13: Based on Embodiment 10, the numerical calculation module provided in the embodiment of the present invention comprises:

[0167] The physical length acquisition submodule is responsible for calculating the physical distance between each point and the previous point, traversing all points, and accumulating the physical distance between each point and the previous point to obtain the physical length of the target curve;

[0168] The time difference calculation submodule is responsible for finding the extreme value along the horizontal direction in the cross-correlation spectrum and obtaining the coordinates of the maximum value; summing up the physical length of each group of midpoints and calculating the time difference experienced;

[0169] The velocity value calculation submodule is responsible for calculating the segmented pulse wave velocity. In the segmentation process, overlapping sampling is added to obtain the corrected curved array ultrasound pulse wave conduction velocity value.

[0170] The working principle and beneficial effects of the above technical solution are as follows: the physical length acquisition submodule of this embodiment calculates the physical distance between each point and the previous point, traverses all points, and accumulates the physical distance between each point and the previous point to obtain the physical length of the target curve; the time difference calculation submodule searches for extreme values ​​in the cross-correlation spectrum along the horizontal direction to obtain the maximum value coordinates; the physical length of each group of midpoints is summed up to calculate the time difference experienced; the velocity value calculation submodule calculates the segmented pulse wave velocity, and in the segmentation process, overlapping sampling is added to obtain the corrected curved array ultrasound pulse wave conduction velocity value. The physical length acquisition submodule of the above scheme: by calculating and accumulating the physical distance, the physical length of the target curve can be obtained. The length value reflects the distance between the points on the target curve, which is used for the subsequent time difference calculation and pulse wave velocity calculation. The time difference calculation submodule finds the extreme value coordinates in the cross-correlation spectrum and calculates the physical length of each group of midpoints and sums them up to obtain the time difference experienced. This time difference reflects the time of pulse wave propagation, which is used for the subsequent pulse wave velocity calculation. The velocity value calculation submodule calculates the segmented pulse wave velocity and adds overlap sampling to obtain the corrected curved array ultrasound pulse wave conduction velocity value, which represents the rate at which the pulse wave propagates in the blood vessel and is used to evaluate the elasticity of the blood vessel and the conduction velocity of the pulse wave. The corrected velocity value can improve the accuracy and reliability of the calculation results.

[0171] In summary, in this embodiment, through these sub-modules, the calculation module can calculate the physical length, time difference and segmented pulse wave velocity of the target curve; these calculation results are very important for vascular function evaluation and disease diagnosis, and can provide accurate and reliable pulse wave conduction velocity data to help doctors evaluate and diagnose vascular health.

[0172] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A pulse wave velocity measurement and correction method based on a curved array, characterized in that: The following steps are involved: Acquire an ultrasound image, convert the point coordinates in the polar coordinate system into coordinates in the rectangular coordinate system, replace the abnormal points in the rectangular coordinate system of the blood vessel wall position by linear fitting, and obtain the coordinates after the abnormal value points are replaced; The transformed coordinates are cross-correlated and the three-dimensional structure is obtained. The target coordinate points in the coordinates after replacing the outlier points are extracted from the three-dimensional structure and the cross-correlation spectrum is obtained by expansion. Find the extreme value in the cross-correlation spectrum, and calculate the total physical length and time difference of each group of points; calculate the segmented ultrasonic pulse wave conduction velocity measurement according to the time difference, take the average value of the ultrasonic pulse wave conduction velocity measurement of each segment, and obtain the corrected curved array ultrasonic pulse wave conduction velocity measurement value.

2. The pulse wave velocity measurement and correction method based on curved array according to claim 1, characterized in that: The process of obtaining the coordinates after replacing the outlier points includes the following steps: Acquire an ultrasound image containing the position information of the blood vessel wall, and perform rectangular coordinate system conversion for each polar coordinate point of the blood vessel wall position; The mean square error is calculated for each segment of the longitudinal coordinates in the rectangular coordinate system, and compared with the value under the mean square error, so as to detect and replace the outlier points in the point coordinates in the rectangular coordinate system; the point coordinates in the rectangular coordinate system after replacing the outlier points are linearly fitted using the least squares method to obtain the parameters of the fitting line; The coordinates of the replaced outlier point are calculated and replaced to obtain the coordinates of the replaced outlier point in the rectangular coordinate system.

3. The pulse wave velocity measurement and correction method based on curved array according to claim 2, characterized in that: The process of normalizing the rectangular coordinate system includes the following steps: Obtain the size of the current ultrasound image, calculate the axial point spacing of the current image, calculate the lateral point spacing based on the axial point spacing, and then calculate the upsampling multiple of the lateral coordinate; Upsample each transverse coordinate, traverse each column of the current ultrasound image, from left to right; for each column, calculate the index of the current transverse coordinate; Use linear interpolation to interpolate on the current column according to the index to get the upsampled horizontal coordinates.

4. The pulse wave velocity measurement and correction method based on curved array according to claim 2, characterized in that: The process of obtaining the parameters of the fitted line includes the following steps: The vascular wall position in polar coordinates was converted to a rectangular coordinate system, the longitudinal coordinates were divided into multiple groups, and the mean square error was calculated for each group of points; values ​​greater than three times the mean square error were considered as outliers and eliminated; Perform the least square linear fit on the removed points with the left and right points to calculate the coordinates of the originally removed points; Repeat the mean square error calculation and least squares linear fitting until all points are calculated and all outliers are eliminated.

5. The pulse wave velocity measurement and correction method based on curved array according to claim 1, characterized in that: The process of obtaining the cross-correlation spectrum includes the following steps: The acquired data are subjected to coordinate transformation, and the position of the blood vessel wall in polar coordinates is converted into the position in rectangular coordinates; cross-correlation calculation is performed on each time step, and each time step is regarded as an independent data frame, and cross-correlation calculation is performed on the time frame; By performing cross-correlation calculations, a three-dimensional structure is obtained. The three-dimensional structure represents the changes in the position of the blood vessel wall and is used to analyze the dynamic evolution and change rules of the blood vessel wall morphology. Obtain the target coordinates in the rectangular coordinate system, and in the three-dimensional cross-correlation structure, take out the corresponding coordinate points according to the position of the target coordinates; expand the coordinate points in all time dimensions to obtain a new two-dimensional structure with a scaled cross-correlation spectrum.

6. The pulse wave velocity measurement and correction method based on curved array according to claim 5, characterized in that: The cross-correlation operation process includes the following steps: A reference signal is selected, and the reference signal is the blood vessel wall position data at a certain time point; a certain time point refers to a specific time point selected in a time series, which is any time point therein; The reference signal is multiplied point by point with the blood vessel wall position data at other time points, and the sum is calculated to obtain the cross-correlation value; other time points refer to other time points except the selected reference time point, which are other time points in the same time series; The calculation steps are repeated to perform cross-correlation calculation on all time points to obtain a cross-correlation sequence, which indicates the degree of correlation between the reference signal and the blood vessel wall position data at other time points.

7. The pulse wave velocity measurement and correction method based on curved array according to claim 1, characterized in that: The process of obtaining the corrected curved array ultrasound pulse wave velocity measurement value includes the following steps: Calculate the physical distance between each point and the previous point, traverse all points, and add up the physical distance between each point and the previous point to get the physical length of the target curve; In the cross-correlation spectrum, find the extreme value along the horizontal direction to obtain the coordinates of the maximum value; sum up the physical lengths of each group of midpoints and calculate the time difference experienced; The segmented pulse wave velocity is calculated, and overlapping sampling is added during the segmentation process to obtain the corrected curved array ultrasound pulse wave conduction velocity value.

8. The pulse wave velocity measurement and correction method based on curved array according to claim 7, characterized in that: The calculation process of physical distance includes the following steps: According to the given coordinates, for each point, calculate the difference between its coordinates and the previous point, then calculate the sum of their squares, and perform square root operation; Multiply the result by the pixel spacing to get the physical distance between the points; After traversing all the points, the physical length of the target curve is obtained.

9. The pulse wave velocity measurement and correction method based on curved array according to claim 7, characterized in that: The process of calculating the segmented pulse wave velocity includes the following steps: By searching for extreme values ​​along the horizontal direction of the cross-correlation spectrum, multiple maximum value coordinates are obtained; the time difference experienced by the maximum value coordinates is calculated by the sum of the physical lengths of certain points in each group; the time difference is obtained by multiplying the horizontal axis coordinate after least squares fitting of the coordinate by the frame rate during data acquisition; The segmented pulse wave velocity is calculated as the physical length / time difference of certain points in each group; overlapping sampling of certain points is added during the segmentation process; The corrected curved array ultrasonic pulse wave velocity value can be obtained by taking the average value of all calculated ultrasonic pulse wave velocity values.

10. A pulse wave transmission velocity measurement and correction system based on a curved array, characterized in that: Include: The coordinate replacement module is responsible for acquiring the ultrasound image, converting the point coordinates in the polar coordinate system into the coordinates in the rectangular coordinate system, replacing the abnormal points in the rectangular coordinates of the vascular wall position by linear fitting, and obtaining the coordinates after replacing the abnormal value points; The three-dimensional construction module is responsible for performing cross-correlation calculation on the transformed coordinates to obtain the three-dimensional structure; replacing the target coordinate points in the coordinates after the outlier points, extracting the corresponding coordinate points from the three-dimensional structure, and expanding them to obtain the cross-correlation spectrum; The numerical calculation module is responsible for finding extreme values ​​in the cross-correlation spectrum and calculating the total physical length and time difference of each group of points; calculating the segmented ultrasonic pulse wave conduction velocity measurement according to the time difference, taking the average value of the ultrasonic pulse wave conduction velocity measurement of each segment, and obtaining the corrected curved array ultrasonic pulse wave conduction velocity measurement value.

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