Blood vessel function evaluation method and system based on blood vessel image

Abstract

The invention discloses a blood vessel function evaluation method and system based on a blood vessel image, and relates to the technical field of blood vessel function evaluation, and the method comprises the steps: S1, obtaining a blood vessel image, and enabling the blood vessel image to generate a blood vessel image sequence according to a time sequence; s2, based on the blood vessel image sequence, dividing the blood vessel image into a plurality of blood vessel nodes, and identifying blood vessel parameters corresponding to the blood vessel nodes; the blood vessel parameters comprise blood vessel diameter, blood vessel area and blood flow velocity; s3, based on the blood vessel parameters of the blood vessel nodes, identifying the change trend of the blood vessel nodes, and according to the change trend of the blood vessel nodes, obtaining blood vessel evaluation coefficients of the blood vessel nodes about the blood vessel parameters; s4, acquiring a collection cycle of the blood vessel parameters, identifying cycle influence coefficients corresponding to the blood vessel parameters in different collection cycles, and acquiring an influence evaluation set corresponding to the blood vessel parameters based on the cycle influence coefficients; the accuracy and efficiency of blood vessel assessment can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vascular function evaluation, and in particular to a vascular function evaluation method and system based on vascular images. Background Art

[0002] Vascular diseases have become the number one killer endangering the health of the Chinese people. Since the evaluation of vascular function and the diagnosis of vascular diseases in clinical practice are often invasive and interventional, interventional surgery has the risk of complications, and the economic burden of invasive diagnostic methods is large, which hinders the promotion of vascular function evaluation and vascular disease diagnosis among the population, and seriously restricts the medical strategy of early detection, early diagnosis, and early treatment of vascular diseases. Therefore, non-invasive vascular function evaluation based on vascular images is an important clinical research direction.

[0003] For example, Chinese patent publication number CN117197096A discloses a method and system for evaluating vascular function based on vascular images. The method includes the following steps: S1: acquiring vascular images; S2: preprocessing vascular images; S3: performing vascular segmentation on the preprocessed images to obtain cross-sectional images of vascular walls; S4: acquiring vascular parameters based on the cross-sectional images of vascular walls; S5: calculating vascular function evaluation indicators based on vascular parameters; S6: performing comprehensive evaluation of vascular function based on vascular parameters and vascular function evaluation indicators. The method and system provided by the present invention can quickly image and easily segment vascular regions.

[0004] Existing technologies tend to directly analyze the vessel diameter, vessel area, etc. measured in the blood vessels, but ignore the periodic changes of these parameters during measurement and the corresponding relationship between the parameters, resulting in a tendency to evaluate the overall average when evaluating the blood vessels. It is impossible to identify the changing trends of the blood vessels based on the specific conditions of the blood vessels, resulting in poor adaptability of the vascular assessment and reduced accuracy of the vascular assessment. Summary of the invention

[0005] The present application solves the problem of inaccurate vascular trend identification in the prior art by providing a vascular function assessment method and system based on vascular images, thereby achieving accuracy and efficiency in vascular assessment.

[0006] The present application provides a vascular function assessment method based on vascular images, comprising: S1, acquiring vascular images, and generating a vascular image sequence according to a time series of the vascular images.

[0007] S2, based on the vascular image sequence, divides the vascular image into multiple vascular nodes, and identifies the vascular parameters corresponding to the vascular nodes; the vascular parameters include vascular diameter, vascular area and blood flow velocity.

[0008] S3, based on the vascular parameters of the vascular nodes, identifying the change trend of the vascular nodes, and obtaining the vascular evaluation coefficient of the vascular nodes with respect to the vascular parameters according to the change trend of the vascular nodes.

[0009] S4, obtaining an acquisition cycle of the vascular parameters, identifying the cycle influence coefficients corresponding to the vascular parameters under different acquisition cycles, and obtaining an influence evaluation set corresponding to the vascular parameters based on the cycle influence coefficients.

[0010] S5, analyzing the impact assessment set, identifying the influence degree coefficient of the main functional indicators of the blood vessels on the impact assessment set, and comprehensively analyzing the influence degree coefficient and the blood vessel assessment coefficient to obtain the final blood vessel assessment index.

[0011] A vascular function evaluation system based on vascular images includes: an image acquisition module: used for acquiring vascular images and preprocessing the vascular images to obtain vascular image sequences.

[0012] Vascular parameter identification module: used to divide the vascular image into multiple vascular nodes and identify the vascular parameters of each node.

[0013] Trend identification module: used to identify the changing trend of vascular parameters based on the vascular parameters of vascular nodes and calculate the vascular evaluation coefficient.

[0014] Cycle impact module: used to identify cycle impact coefficients under different cycles according to the acquisition cycle of vascular parameters, and to construct an impact evaluation set.

[0015] Impact assessment module: used to analyze the impact assessment set, calculate the impact degree coefficient, and conduct a comprehensive analysis with the vascular assessment coefficient to obtain the final vascular assessment index.

[0016] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0017] By acquiring vascular images and generating vascular image sequences in time series, a continuous and dynamic data foundation is provided for subsequent vascular parameter identification and trend analysis. By dividing vascular images into multiple vascular nodes and identifying the vascular parameters corresponding to each node, the fine division of vascular structure and accurate measurement of key parameters are achieved, providing an important basis for vascular function evaluation. By identifying the vascular parameters based on vascular nodes, the change trend is identified and the vascular evaluation coefficient is obtained; the changes of blood vessels over time can be captured, and the degree of change can be quantified through the evaluation coefficient, providing a reliable basis for the judgment of vascular health status. By obtaining the acquisition cycle of vascular parameters, the cycle influence coefficients under different cycles are identified, and an impact evaluation set is constructed; the changes of vascular parameters under different acquisition cycles are considered, which improves the accuracy and comprehensiveness of the evaluation. By analyzing the impact evaluation set, the influence degree coefficients of the main vascular function indicators are identified, and a comprehensive analysis is performed with the vascular evaluation coefficient to obtain the final vascular evaluation index; the impact of multiple factors on vascular function is comprehensively considered, and a comprehensive and accurate vascular health evaluation result is obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The figure is a flow chart of a method for evaluating vascular function based on vascular images according to the present invention.

[0019] Figure 2 The figure is a flow chart of step S3 of a method for evaluating vascular function based on vascular images of the present invention.

[0020] Figure 3 The figure is a flow chart of step S4 of a method for evaluating vascular function based on vascular images of the present invention.

[0021] Figure 4 FIG. 4 is a flow chart of step S5 of a method for evaluating vascular function based on vascular images of the present invention.

[0022] Figure 5 This is a system framework diagram of a vascular function assessment system based on vascular images of the present invention. DETAILED DESCRIPTION

[0023] To facilitate the understanding of the present invention, the present application will be described more comprehensively below with reference to the relevant drawings; the drawings show preferred embodiments of the present invention, but the present invention can be implemented in many different forms and is not limited to the embodiments described herein; on the contrary, the purpose of providing these embodiments is to enable a more thorough and comprehensive understanding of the disclosed content of the present invention.

[0024] It should be noted that the terms “vertical”, “horizontal”, “up”, “down”, “left”, “right” and similar expressions used in this document are only for illustrative purposes and do not represent the only implementation method.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which the present invention belongs; the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the term "and / or" used herein includes any and all combinations of one or more related listed items.

[0026] like Figure 1 As shown, a vascular function assessment method based on vascular images comprises:

[0027] S1, acquiring a blood vessel image, and generating a blood vessel image sequence according to a time series.

[0028] S2, based on the vascular image sequence, divides the vascular image into multiple vascular nodes, and identifies the vascular parameters corresponding to the vascular nodes; the vascular parameters include vascular diameter, vascular area and blood flow velocity.

[0029] S3, based on the vascular parameters of the vascular nodes, identifying the change trend of the vascular nodes, and obtaining the vascular evaluation coefficient of the vascular nodes with respect to the vascular parameters according to the change trend of the vascular nodes.

[0030] S4, obtaining an acquisition cycle of the vascular parameters, identifying the cycle influence coefficients corresponding to the vascular parameters under different acquisition cycles, and obtaining an influence evaluation set corresponding to the vascular parameters based on the cycle influence coefficients.

[0031] S5, analyzing the impact assessment set, identifying the influence degree coefficient of the main functional indicators of the blood vessels on the impact assessment set, and comprehensively analyzing the influence degree coefficient and the blood vessel assessment coefficient to obtain the final blood vessel assessment index.

[0032] In the present invention, medical imaging equipment (such as ultrasound, MRI, CT, etc.) is used to obtain blood vessel images; the blood vessel images are preprocessed, including denoising, contrast enhancement, edge detection, etc., to improve the accuracy of blood vessel recognition.

[0033] After these identified vascular images are identified, the identified vascular parameters include vascular diameter, vascular area and blood flow velocity. The vascular area represents the area of ​​vascular expansion and dilation, which is used to identify the specific changes in blood vessels when performing vascular assessment on the human body.

[0034] The blood vessel diameter can be measured directly from the blood vessel image, which represents the width of the blood vessel lumen. The blood vessel area is obtained by outlining the blood vessel lumen area, and the blood flow velocity is measured using the Doppler effect. When ultrasound encounters moving red blood cells, the frequency of the reflected sound waves will change, and this change is proportional to the blood flow velocity, thereby obtaining the blood flow velocity required at this time.

[0035] The acquired vascular image sequence is represented as data corresponding to a continuous time series, which can indicate the time when the specific changes in the blood vessel currently being evaluated occur, thereby assisting in identifying problems that occur.

[0036] For example, the implementation method of step S2 includes: based on the vascular image sequence, dividing the vascular image according to the time series, and dividing multiple vascular nodes according to the vascular cavity contour in turn, each vascular node represents a partial area of ​​the vascular image at a time point, and according to the displacement of the vascular node in the time series, calculating the vascular diameter and vascular area, using the Doppler effect to measure the blood flow velocity, and outputting the vascular diameter, vascular area and blood flow velocity as vascular parameters.

[0037] like Figure 2 As shown, the method of identifying the change trend of the blood vessel node in step S3 is:

[0038] S31, based on the vascular parameters of the vascular nodes, determining the trend change amount of each vascular node in multiple cycles and the trend difference amount between adjacent vascular nodes in a single cycle.

[0039] S32, recording the occurrence probability of the trend change amount and the trend difference amount of the blood vessel node, and the joint probability of the trend change amount and the trend difference amount, to obtain the preliminary evaluation coefficient of the blood vessel.

[0040] S33, comparing the preliminary evaluation coefficient of the blood vessel with the preset trend factor to verify whether the change of the blood vessel is consistent with the preset trend factor.

[0041] S34, verifying the correlation between the vascular parameters in a single cycle and multiple cycles, obtaining a cycle correlation coefficient, combining the cycle correlation coefficient with the preliminary evaluation coefficient, and outputting a vascular evaluation coefficient of the vascular parameters.

[0042] The cycle selected in step S31 may be a heartbeat cycle, a respiratory cycle, etc. At the same time, in order to adjust the measurement accuracy of the vascular assessment, the set cycle may also be set to regard each measurement as a cycle to determine the changes in the current vascular assessment after multiple measurements.

[0043] At this time, the trend change and trend difference are calculated through the time series analysis algorithm. The trend change indicates the difference in the corresponding measurement time for each vascular node in different cycles; the trend difference indicates the difference between adjacent vascular nodes in the same cycle; at the same time, in order to improve the accuracy of the current measurement data, it is necessary to select the data of the blood vessel currently being evaluated entering a stable period when measuring the data. For example, about twenty seconds after the test, the user's blood vessel changes will be relatively stable. The data at this time can reflect the specific cleaning of the user's blood vessels currently being measured.

[0044] The calculation method for the trend change of vascular parameters can be expressed as calculating the average value of blood flow velocity in all cycles, and calculating the change of each cycle relative to the average value at this time. This change is the trend change; at the same time, the calculation method of vascular area and vascular diameter in vascular parameters is different from that of blood flow velocity. Vascular area and vascular diameter pay more attention to the difference between a single value and the average value in historical data, that is, calculating the difference between vascular area and vascular diameter and the average value of historical data, calculating the average value of the difference, and finally calculating the change of the average value of the difference relative to the average value in historical data.

[0045] For example, consider the number of vascular nodes as i, the number of cycles as t, the vascular diameter as D, the vascular area as A, and the blood flow velocity as V. At this time, the trend change amount and trend difference amount of the vascular parameters can be expressed as shown below.

[0046] in, represents the average value of the vessel diameter of the i-th vessel node in multiple cycles, D i,t represents the value of the vessel diameter of the i-th vessel node in the t-th cycle, D represents the average value of the vessel diameter in the historical data, n represents the number of cycles, and t ranges from 1 to n.

[0047] Then the trend change of blood vessel diameter can be expressed as Where, ΔD i,t Represents the trend change of the blood vessel diameter of the i-th blood vessel node in the t-th cycle.

[0048] Where, ΔD i The trend change amount of the blood vessel diameter of the i-th blood vessel node represents the number of blood vessel nodes. The trend change amount at this time is the trend change amount mainly calculated in subsequent steps.

[0049] At this time, the calculation method of the trend change of the blood vessel area is the same as the trend change of the blood vessel diameter, which will not be described here.

[0050] The trend change amount of blood flow velocity is expressed as follows.

[0051] in, represents the average blood flow velocity of the ith vascular node in multiple cycles, V i,t Represents the value of the blood flow velocity of the i-th blood vessel node in the t-th cycle.

[0052] Then the trend change of blood vessel diameter can be expressed as Where, ΔV i,tIt represents the trend change of blood flow velocity of the i-th vascular node in the t-th cycle; Wherein, is represented as the trend change of the blood flow velocity of the i-th vascular node.

[0053] When calculating the trend difference amount, the average value of the difference between the vascular parameters of adjacent vascular nodes is calculated as the trend difference amount of the vascular node at this time.

[0054] When calculating the preliminary evaluation coefficient based on the trend difference and the trend change, the occurrence probabilities of the trend change and the trend difference are identified respectively. At this time, the occurrence probability can be expressed as the ratio of the number of values ​​of the trend change and the trend difference to the number of all values. At the same time, it is necessary to identify the joint probability in order to identify the currently set preliminary evaluation coefficient.

[0055] The joint probability of the trend change amount and the trend difference amount can be expressed as shown below.

[0056]

[0057] Among them, γ represents the joint probability of trend change and trend difference, P1 represents the probability of occurrence of trend change, P2 represents the probability of occurrence of trend difference, exp represents an exponential function with an exponential base of e, α1 represents the weight coefficient of trend change, and α2 represents the weight coefficient of trend difference.

[0058] Since the trend difference and trend change at this time correspond to the blood flow velocity, blood vessel diameter and blood vessel area respectively, the weight coefficients set at this time are 0.3, 0.15 and 0.15 respectively for the trend change amount set in the order of blood vessel diameter, blood vessel area and blood flow velocity, and the weight coefficients set in the order of blood vessel diameter, blood vessel area and blood flow velocity are 0.2, 0.1 and 0.1 respectively for the trend difference amount set in the order of blood vessel diameter, blood vessel area and blood flow velocity.

[0059] At this time, the preliminary evaluation coefficient is expressed as: Based on the joint probability of the trend change amount and the trend difference amount, the preliminary evaluation coefficient is calculated:

[0060]

[0061] Among them, δ represents the preliminary evaluation coefficient, J represents the number of vascular parameters, and the value of j ranges from 1 to J. j represents the joint probability of the trend change and trend difference of the j-th vascular parameter, It represents the average value of the joint probability of the trend change amount and the trend difference amount. When calculating the vascular parameters at this time, the values ​​corresponding to the vascular diameter, vascular area and blood flow velocity in the vascular node are input in sequence, so that the preliminary evaluation coefficient corresponding to the vascular parameters can be obtained.

[0062] In step S33, the preliminary evaluation coefficient is compared with the preset trend factor to identify whether the preliminary evaluation coefficient calculated at this time is consistent with the preset trend factor set in the database. When they are consistent, the preliminary evaluation coefficient at this time is directly output; when they are inconsistent, the preliminary evaluation coefficient of the previous cycle is obtained, and the average value of the preliminary evaluation coefficient of the previous cycle and the preliminary evaluation coefficient of the current cycle is output. The output preliminary evaluation coefficient is combined with the cycle correlation coefficient to calculate the vascular evaluation coefficient.

[0063] For the calculation method of the periodic correlation coefficient in step S34, the trend change amount and trend difference amount of the vascular parameters are taken as input, and the first correlation coefficient related to the trend change amount and trend difference amount of the vascular diameter, the second correlation coefficient related to the trend change amount and trend difference amount of the vascular area, and the third correlation coefficient related to the trend change amount and trend difference amount of the blood flow velocity are calculated in sequence, and the weighted average of the first correlation coefficient, the second correlation coefficient, and the third correlation coefficient is taken as the periodic correlation coefficient.

[0064] The first correlation coefficient uses the trend change and trend difference of the vascular diameter as input, and takes the average value of the trend change and trend difference of the vascular diameter in the historical data as the comparison content. The Pearson correlation coefficient is used to calculate the first correlation coefficient at this time. The comparison method for the second correlation coefficient and the third correlation coefficient is the same, both of which use the corresponding average values ​​in the historical data for comparison. The Pearson correlation coefficient is used to identify the correlation between multiple cycles at this time to identify the consistency of vascular parameters and ensure the effectiveness of the current vascular assessment.

[0065] After obtaining the period correlation coefficient, the realization method of the vascular evaluation coefficient is expressed as:

[0066]

[0067] Wherein, PI represents the vascular assessment coefficient, e represents the exponential constant, δ represents the preliminary assessment coefficient, δ0 represents the standard value of the preliminary assessment coefficient, and the standard value adopts the average value of the preliminary assessment coefficient in the historical data; R represents the cycle correlation coefficient, R0 represents the standard value of the cycle correlation coefficient, and the standard value of the cycle correlation coefficient adopts the average value of the historical data.

[0068] In step S4, the periodic influence coefficient includes obtaining a periodic correction value and a periodic reminder value, so as to obtain corresponding influence coefficients under different periods.

[0069] like Figure 3 As shown, step S4 can be implemented in the following manner:

[0070] S41, based on the variation trend of the vascular parameters, obtaining a stenosis coefficient related to the vascular parameters and the vascular stenosis.

[0071] S42, based on the variation trend of the vascular parameters, obtaining a patency coefficient related to the vascular parameters and the vascular patency.

[0072] S43, based on the stenosis coefficient and the unobstructedness coefficient, the cycle range value of the current vascular node in the corresponding cycle is calculated in sequence, the maximum value of the cycle range value is used as the cycle reminder value, and the median value of the cycle range value is used as the cycle correction value.

[0073] S44, outputting a cycle impact value based on the cycle reminder value and the cycle correction value.

[0074] At this time, the stenosis coefficient is expressed as the ratio of the time when the blood vessel diameter, blood vessel area and blood flow velocity are measured within the normal range to the total time; the unobstructedness coefficient is expressed as the ratio of the time when the blood vessel velocity is within the normal range to the total time; the data used to calculate the stenosis coefficient and the unobstructedness coefficient are the data currently measured in the corresponding cycle, which reflects whether the blood vessel parameters are normal in the current cycle and quantifies the corresponding status of each blood vessel node.

[0075] The cycle range value is expressed as: Range = w1×N+w2×(1-S); wherein Range represents the cycle range value, N represents the stenosis coefficient, w1 represents the weight coefficient of the stenosis coefficient, S represents the unobstructedness coefficient, and w2 represents the weight coefficient of the unobstructedness coefficient. The cycle range values ​​calculated for multiple cycles and a single cycle are combined. At this time, the maximum value in the cycle range value is the cycle reminder value, and the median value in the cycle range value is the cycle correction value; the weight coefficients for the stenosis coefficient and the unobstructedness coefficient are expressed as 0.6 and 0.4 respectively.

[0076] The calculation method of the cycle impact value is expressed as, Among them, RE represents the cycle impact value, Pr represents the cycle reminder value, Pc represents the cycle correction value, w3 represents the weight coefficient of the cycle reminder value, w4 represents the weight coefficient of the cycle correction value, and the weight coefficients of the cycle reminder value and the cycle correction value are set to 0.55 and 0.45 respectively. Combined with the cycle reminder value and the cycle correction value at this time, the output cycle impact value can timely detect the user's vascular changes, so as to timely identify the state of the blood vessels corresponding to the current user and make timely evaluation.

[0077] After obtaining the cycle influence coefficient, the corresponding data is output to obtain the influence data set. The influence data set contains the corresponding calculation results under the current step. The influence data set includes the cycle influence coefficient, cycle range value, cycle reminder value, cycle correction value, stenosis coefficient and patency coefficient, etc. The data contained in the influence data set is compared with the historical data. When it is greater than the threshold set by the historical data, the influence data set is output as an impact evaluation set. The data output by the impact evaluation set needs to be further identified, and attention is paid to the quantitative value of the health condition represented by the blood vessels when the current vascular health condition undergoes major changes.

[0078] In step S5, by identifying the functional indicators of vascular function and calculating the probability values ​​of deviation of these indicators, the content of the current impact assessment set can be quantified to obtain the overall impact of each main functional indicator under the impact assessment set.

[0079] The functional indicators used at this time include the stenosis change rate, the patency change rate and the blood flow velocity change rate. The stenosis change rate can be calculated based on the stenosis coefficient, the patency change rate can be calculated based on the patency coefficient, and the blood flow velocity change rate can be calculated based on the blood flow velocity corresponding to the stenosis coefficient at this time; then the indicator coefficient is calculated for the functional indicator, and the indicator coefficient is combined with the degree of deviation of the functional indicator to calculate the influence degree coefficient.

[0080] like Figure 4 As shown, the implementation of step S5 includes:

[0081] S51, based on the impact assessment set, obtaining index coefficients corresponding to the functional indicators in sequence, the index coefficients including a stenosis change rate coefficient, a patency change rate coefficient and a blood flow velocity change rate coefficient.

[0082] S52, obtaining the deviation degree of the index coefficient under the corresponding index coefficient value, the deviation degree includes the deviation degree of stenosis, the deviation degree of patency, and the deviation degree of blood flow velocity.

[0083] S53, combining the index coefficient and the deviation degree to calculate the influence degree coefficient corresponding to the functional index.

[0084] The stenosis change rate coefficient can be expressed as, K N =1+α N ×ΔN t ; Among them, K N represents the coefficient of change of stenosis, ΔN t represents the rate of change of stenosis, α N The weight coefficient representing the degree of stenosis.

[0085] The coefficient of change rate of permeability can be expressed as, KS =1+α S ×ΔS t ; Among them, K S Indicates the coefficient of change rate of permeability, ΔS t represents the rate of change of permeability, α S Indicates the weight coefficient of the degree of openness.

[0086] The blood flow velocity change rate coefficient can be expressed as, K V =1+α V ×ΔV t ; Among them, K V Represents the blood flow velocity change rate coefficient, ΔV t represents the blood flow velocity change rate, α V Represents the weight coefficient of blood flow velocity.

[0087] The weight coefficients set above are set to 0.3, 0.4, and 0.3 in the order of the stenosis change rate coefficient, the patency change rate coefficient, and the blood flow velocity change rate coefficient.

[0088] The degree of deviation of stenosis can be expressed as Among them, d N Indicates the degree of deviation of stenosis, ΔN t represents the rate of change of stenosis, μ N represents the average value of stenosis, σ N Indicates the standard deviation of stenosis; at this time, the mean value and standard deviation of stenosis can be calculated based on the stenosis coefficient.

[0089] The degree of deviation of the dredge can be expressed as, Among them, d S Indicates the degree of deviation of the dredge, ΔS t Indicates the rate of change of permeability, μ S represents the average value of the permeability, σ S Indicates the standard deviation of the flow rate.

[0090] The degree of deviation of blood flow velocity can be expressed as, Among them, d V Indicates the degree of deviation of blood flow velocity, ΔV t Indicates the blood flow velocity change rate, μ V represents the average blood flow velocity, σ V Represents the standard deviation of blood flow velocity.

[0091] At this time, the way to obtain the influence degree coefficient is to obtain the stenosis change rate coefficient, the patency change rate coefficient, the blood flow velocity change rate coefficient, the stenosis deviation degree, the patency deviation degree, the blood flow velocity deviation degree, and calculate the influence degree coefficient.

[0092]

[0093] Among them, PD is expressed as the influence degree coefficient. By quantifying the deviation degree and the index coefficient in the form of a power function, it is possible to compare and reflect the subtle changes in the deviation degree and the index coefficient when the values ​​are small, and more accurately reflect the overall corresponding impact results when there are subtle changes in the vascular health status; when the deviation degree and the index coefficient are calculated at the same time, the stenosis is expressed as the stenosis coefficient in the influence assessment set, the patency is expressed as the patency coefficient in the influence assessment set, the blood flow velocity is obtained based on the blood flow velocity in the influence assessment set, and the difference between the current blood flow velocity and the historical blood flow velocity average is obtained, and the ratio of the difference to the historical blood flow velocity average is used as the blood flow velocity change rate used at this time.

[0094] After obtaining the influence coefficient, the final evaluation index of the blood vessel can be expressed as:

[0095] PF=PI×log2(1-PD)+(1-PI)×log2(PD);

[0096] Among them, PF represents the final evaluation index of blood vessels, PI represents the blood vessel evaluation coefficient, and PD represents the influence degree coefficient.

[0097] The final vascular evaluation index can reduce misdiagnosis caused by fluctuations in a single index and improve the accuracy of diagnosis. At the same time, based on this comprehensive index, potential problems in the blood vessels can be discovered earlier, and timely intervention and treatment of the blood vessels can be performed to improve the treatment effect of the blood vessels.

[0098] The present invention mainly identifies that if relative expansion and contraction occur during blood vessel detection, the shape of the currently identified blood vessel is verified, and whether there are nodes at the currently identified blood vessel where the contraction and expansion are larger than those of the surrounding blood vessels, as well as points where the expansion is smaller than that of the surrounding blood vessels, or even smaller than expected. The blood vessel image when the blood vessel flow is expanded is verified to identify whether there are stenosis and blockages. The incidence of stenosis of the blood vessel and the position of the blood vessel in the human body's torso are verified, and the possible stenosis opening rate and contraction-swelling ratio at this time are identified. It is verified whether the blood vessel evaluation value corresponding to each node meets expectations, and whether there is a correlation between the difference in blood vessel contraction and the difference in stenosis and the trend of the same corresponding distribution;

[0099] When evaluating blood vessels, the acquired blood vessel images are divided into multiple segments, each segment is recorded as a blood vessel node, and the trend change amount of each blood vessel node in multiple cycles and the trend difference amount between adjacent blood vessel nodes in a single cycle are determined.

[0100] The distribution probability and joint distribution probability of the trend change amount and trend difference amount of each vascular node are recorded to determine the changes in the corresponding diameter, area and blood flow velocity of the current blood vessel.

[0101] The stenosis and patency of the vascular node at this time are recorded. The stenosis can be set according to the shape of the current vascular node and the blood flow rate, while the patency represents a calculation method opposite to the stenosis, which mainly obtains the time proportion and occurrence probability under the normal flow rate of the blood vessel to quantify the normal proportion of the blood vessel.

[0102] After completing the recognition of these contents, multiple data are collected and judged on the blood vessels in turn according to the contents recognized at this time, and whether the actual changes of the blood vessels at this time are consistent with the preset trend factors is obtained to verify the comprehensive situation of the blood vessels under the current identification situation, so as to complete the periodic evaluation processing of the blood vessels; at the same time, it is also necessary to verify the correlation between the blood vessels in multiple cycles and a single cycle, so as to quantify the corresponding control of the blood vessels and complete the judgment processing of the blood vessels.

[0103] Here, the cycle reminder value and cycle correction level will be set according to these data to adjust the cycle of vascular detection and evaluation, as well as the corresponding cycle identification and processing method after the blood vessel is processed.

[0104] like Figure 5 As shown, a vascular function assessment system based on vascular images comprises:

[0105] Image acquisition module: used to acquire vascular images and preprocess the vascular images to obtain vascular image sequences.

[0106] Vascular parameter identification module: used to divide the vascular image into multiple vascular nodes and identify the vascular parameters of each node.

[0107] Trend identification module: used to identify the changing trend of vascular parameters based on the vascular parameters of vascular nodes and calculate the vascular evaluation coefficient.

[0108] Cycle impact module: used to identify cycle impact coefficients under different cycles according to the acquisition cycle of vascular parameters, and to construct an impact evaluation set.

[0109] Impact assessment module: used to analyze the impact assessment set, calculate the impact degree coefficient, and conduct a comprehensive analysis with the vascular assessment coefficient to obtain the final vascular assessment index.

[0110] The system ultimately achieves a comprehensive and accurate assessment of vascular function. Through continuous vascular image acquisition, precise vascular node division and parameter identification, capture and analysis of changing trends, and comprehensive consideration of periodicity and impact, the system can provide users with reliable vascular health assessment results and provide strong support for the prevention and treatment of vascular diseases.

[0111] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for evaluating vascular function based on vascular images, characterized in that: include: S1, acquiring a vascular image, and generating a vascular image sequence according to a time series of the vascular image; S2, based on the vascular image sequence, the vascular image is divided into multiple vascular nodes, and the vascular parameters corresponding to the vascular nodes are identified; the vascular parameters include vascular diameter, vascular area and blood flow velocity; S3, based on the vascular parameters of the vascular nodes, identifying the change trend of the vascular nodes, and obtaining the vascular evaluation coefficient of the vascular nodes with respect to the vascular parameters according to the change trend of the vascular nodes; S4, obtaining an acquisition cycle of the vascular parameters, identifying the cycle influence coefficients corresponding to the vascular parameters under different acquisition cycles, and obtaining an influence evaluation set corresponding to the vascular parameters based on the cycle influence coefficients; S5, analyzing the impact assessment set, identifying the influence degree coefficient of the main functional indicators of the blood vessels on the impact assessment set, and comprehensively analyzing the influence degree coefficient and the blood vessel assessment coefficient to obtain the final blood vessel assessment index.

2. The vascular function assessment method based on vascular images according to claim 1, characterized in that: Step S3 includes: S31, determining a trend change amount of each vascular node in multiple cycles and a trend difference amount between adjacent vascular nodes in a single cycle based on the vascular parameters of the vascular nodes; S32, recording the occurrence probability of the trend change amount and the trend difference amount of the blood vessel node, and the joint probability of the trend change amount and the trend difference amount, to obtain the preliminary evaluation coefficient of the blood vessel; S33, comparing the preliminary evaluation coefficient of the blood vessel with a preset trend factor to verify whether the change of the blood vessel is consistent with the preset trend factor; S34, verifying the correlation between the vascular parameters in a single cycle and multiple cycles, obtaining a cycle correlation coefficient, combining the cycle correlation coefficient with the preliminary evaluation coefficient, and outputting a vascular evaluation coefficient of the vascular parameters.

3. The vascular function assessment method based on vascular images according to claim 2, characterized in that: The joint probability of the trend change amount and the trend difference amount is expressed as follows; Among them, γ represents the joint probability of trend change and trend difference, P1 represents the probability of occurrence of trend change, P2 represents the probability of occurrence of trend difference, exp represents an exponential function with an exponential base of e, α1 represents the weight coefficient of trend change, and α2 represents the weight coefficient of trend difference.

4. A method for evaluating vascular function based on vascular images as claimed in claim 3, characterized in that the initial The evaluation coefficient is expressed as: Among them, δ represents the preliminary evaluation coefficient, J represents the number of vascular parameters, and the value of j ranges from 1 to J. j represents the joint probability of the trend change and trend difference of the j-th vascular parameter, Represents the average of the joint probabilities of the trend change and the trend difference.

5. The method for evaluating vascular function based on vascular images according to claim 4, characterized in that: The realization of the vascular assessment coefficient is expressed as: Wherein, PI represents the vascular assessment coefficient, e represents the exponential constant, δ represents the preliminary assessment coefficient, δ0 represents the standard value of the preliminary assessment coefficient, R represents the cycle correlation coefficient, and R0 represents the standard value of the cycle correlation coefficient.

6. The vascular function assessment method based on vascular images according to claim 1, characterized in that: Step S4 includes: S41, based on the change trend of the vascular parameters, obtaining a stenosis coefficient related to the vascular parameters and the vascular stenosis; S42, based on the change trend of the vascular parameters, obtaining a patency coefficient related to the vascular parameters and the vascular patency; S43, based on the stenosis coefficient and the unobstructedness coefficient, sequentially calculating the cycle range value of the current vascular node in the corresponding cycle, taking the maximum value of the cycle range value as the cycle reminder value, and taking the median value of the cycle range value as the cycle correction value; S44, outputting a cycle impact value based on the cycle reminder value and the cycle correction value.

7. The method for evaluating vascular function based on vascular images according to claim 6, characterized in that: The cycle range value is expressed as: Range = w1×N+w2×(1-S); wherein Range represents the cycle range value, N represents the stenosis coefficient, w1 represents the weight coefficient of the stenosis coefficient, S represents the unobstructed coefficient, and w2 represents the weight coefficient of the unobstructed coefficient; The calculation method of the cycle impact value is expressed as, Among them, RE represents the periodic impact value, Pr represents the periodic reminder value, Pc represents the periodic correction value, w3 represents the weight coefficient of the periodic reminder value, and w4 represents the weight coefficient of the periodic correction value.

8. The vascular function assessment method based on vascular images according to claim 1, characterized in that: Step S5 includes: S51, based on the impact assessment set, sequentially obtaining index coefficients corresponding to the functional indexes, the index coefficients including a stenosis change rate coefficient, a patency change rate coefficient, and a blood flow velocity change rate coefficient; S52, obtaining the deviation degree of the index coefficient under the corresponding index coefficient value, the deviation degree includes the deviation degree of stenosis, the deviation degree of patency, and the deviation degree of blood flow velocity; S53, combining the index coefficient and the deviation degree to calculate the influence degree coefficient corresponding to the functional index; The influence degree coefficient is realized by obtaining the stenosis change rate coefficient, the patency change rate coefficient, the blood flow velocity change rate coefficient, the stenosis deviation degree, the patency deviation degree, and the blood flow velocity deviation degree, and calculating the influence degree coefficient; Among them, PD is the influence coefficient, K N represents the coefficient of change of stenosis, K S Indicates the coefficient of change rate of d N Indicates the degree of deviation of stenosis, d S Indicates the degree of deviation of the dredge V Indicates the degree of deviation of blood flow velocity, α N The weight coefficient representing the stenosis, α S Represents the weight coefficient of the degree of openness, α V Represents the weight coefficient of blood flow velocity.

9. The vascular function assessment method based on vascular images according to claim 1, characterized in that: The final evaluation index of blood vessels can be expressed as: PF=PI×log2(1-PD)+(1-PI)×log2(PD); Among them, PF represents the final evaluation index of blood vessels, PI represents the blood vessel evaluation coefficient, and PD represents the influence degree coefficient.

10. A vascular function assessment system based on vascular images, using a vascular function assessment method based on vascular images as described in claims 1 to 9, characterized in that: include: Image acquisition module: used to acquire vascular images and pre-process the vascular images to obtain vascular image sequences; Vascular parameter identification module: used to divide the vascular image into multiple vascular nodes and identify the vascular parameters of each node; Trend recognition module: used to identify the change trend of vascular parameters based on vascular parameters of vascular nodes and calculate vascular evaluation coefficients; Cycle influence module: used to identify cycle influence coefficients under different cycles according to the collection cycle of vascular parameters, and construct an influence evaluation set; Impact assessment module: used to analyze the impact assessment set, calculate the impact degree coefficient, and conduct a comprehensive analysis with the vascular assessment coefficient to obtain the final vascular assessment index.

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