Two-dimensional spot tracking and tissue Doppler combined OSAS cardiac mechanical analysis system

Abstract

The invention belongs to the technical field of medical image analysis, and particularly relates to a two-dimensional spot tracking and tissue Doppler combined OSAS cardiac mechanical analysis system, which realizes high-precision time axis alignment of a two-dimensional ultrasonic gray-scale image sequence and a myocardial tissue Doppler velocity spectrum through a two-channel synchronous acquisition module. The parallel computing engine generates longitudinal strain of the endocardium layer, circumferential strain of the middle layer and speed peak parameters. And the dynamic association module adopts a dynamic time warping algorithm to quantify the phase deviation of the stratified strain curve and the speed curve, and outputs low, middle and high risk grades in combination with a risk index model of the risk early warning module. A visual interface dynamically displays a cardiac muscle movement asynchronous area through a thermodynamic diagram, a velocity vector arrow and an abnormal flicker mark, and a hardware integrated assembly and a standardized analysis process significantly improve the detection sensitivity and diagnosis efficiency. According to the invention, the problems of multi-modal data splitting and early warning lagging are solved.

Description

Technical Field

[0001] The invention relates to the technical field of medical image analysis, and in particular to an OSAS cardiac mechanics analysis system combining two-dimensional speckle tracking with tissue Doppler. Background Art

[0002] Obstructive sleep apnea syndrome (OSAS) is a common disease characterized by nocturnal apnea and hypoxia, which can easily lead to compensatory damage to cardiac function if it is suffered for a long time. In clinical diagnosis, doctors usually rely on ultrasound imaging technology to evaluate the mechanical characteristics of the patient's left ventricular myocardium; however, most existing ultrasound analysis methods only focus on a single modal parameter, making it difficult to fully capture the dynamic correlation between strain and velocity during myocardial contraction.

[0003] The existing methods for evaluating the mechanical characteristics of the patient's left ventricular myocardium are traditional methods. The speckle tracking and myocardial tissue Doppler velocity spectrum are separated and analyzed. The time axis is not accurately aligned, which requires doctors to manually compare reports and the phase deviation calculation error is large. The lack of joint modeling of layered strain and velocity parameters makes it difficult to detect myocardial compensation abnormalities in a timely manner. At the same time, the results are presented in static values, which cannot intuitively locate high-risk areas.

[0004] Aiming at the above problems, an innovative design was carried out based on the original OSAS cardiac mechanics analysis system. Summary of the invention

[0005] The purpose of the present invention is to provide an OSAS cardiac mechanics analysis system combining two-dimensional speckle tracking and tissue Doppler, which aims to solve the problems of multimodal data fragmentation, insufficient time synchronization, delayed warning of abnormal myocardial compensation and lack of visual interaction in the prior art.

[0006] To this end, the technical solution adopted in the present invention is as follows: A two-dimensional speckle tracking combined with tissue Doppler OSAS cardiac mechanics analysis system, including the following modules: M1, dual-channel data acquisition module, which is configured as an ultrasound probe to synchronously acquire a left ventricular two-dimensional ultrasound grayscale image sequence and a myocardial tissue Doppler velocity spectrum, and to achieve time axis alignment of the two types of data; M2, parallel computing engine module, which is connected to the dual-channel data acquisition module, and includes a first processing module and a second processing module: The first processing module receives a two-dimensional ultrasound grayscale image sequence and generates longitudinal strain and circumferential strain parameters of the endocardial layer, the middle myocardial layer and the epicardial layer by a speckle tracking algorithm; The second processing module receives the Doppler velocity spectrum of myocardial tissue and calculates the peak value of myocardial motion velocity by time domain integration. And acceleration parameters ; M3, a dynamic association module, which is connected to the parallel computing engine module, and which performs time series fusion of the longitudinal strain of the endocardial layer, the circumferential strain of the middle myocardial layer, and the circumferential strain of the epicardial layer of the first processing module with the velocity peak value and the acceleration parameter of the second processing module to generate a strain and velocity joint feature map; M4, OSAS risk warning module, which is connected to the dynamic association module, generates the left ventricular systolic function compensation state classification and OSAS risk index based on the phase deviation and parameter change trend in the joint characteristic spectrum, and outputs them to the visual interactive interface.

[0007] Furthermore, the dynamic correlation module calculates the phase deviation between the layered strain curve S(t) and the velocity curve V(t) by a dynamic time warping algorithm, specifically including:

[0008] in is the dimensionless phase deviation metric; π is the optimal alignment path of two time series; is the path with the minimum cumulative distance among the alignment paths π; For time point The layered strain value, in %, includes the longitudinal strain of the endocardial layer and the circumferential strain of the middle myocardial layer; Time The myocardial velocity value, in cm / s, including the peak velocity ; Before calculating the phase deviation, the delamination strain value and speed value Perform standardization and convert into dimensionless parameters; when >τ, a myocardial compensation abnormality warning is triggered, where τ is a dimensionless threshold.

[0009] Furthermore, the OSAS risk warning module calculates the risk index by the following formula:

[0010] in is the OSAS risk index, the index range is 0-1; α and β are weight coefficients, α + β = 1; is the change in the longitudinal strain of the endocardial layer within the time window Δt, and its unit is %; is the change in the peak velocity within the time window Δt, in cm / s; Δt is the length of the analysis time window, in seconds.

[0011] Furthermore, the dual-channel data acquisition module also includes a preprocessing submodule, which is as follows: The preprocessing submodule automatically segments the myocardial contour of the two-dimensional ultrasound grayscale image sequence to divide the endocardial layer, middle layer and epicardial layer regions; The preprocessing submodule performs respiratory motion artifact filtering on the Doppler velocity spectrum of the myocardial tissue to retain velocity signals related to the cardiac systolic period.

[0012] Furthermore, the visual interactive interface of the OSAS risk warning module includes displaying a layered strain thermal map, superimposed tissue Doppler velocity vector arrows, and abnormal area highlighting prompts: The layered strain thermogram is displayed based on the layered strain parameters generated by the first processing module, and maps the strain distribution of each segment of the left ventricle with a color gradient; Red area: longitudinal strain of endocardial layer <-20%; Yellow area: -20%≤endocardial layer longitudinal strain≤-15%; Green area: longitudinal strain of endocardial layer > -15%; The superimposed tissue Doppler velocity vector arrow is based on the velocity parameter generated by the second processing module , the direction of the arrow indicates the direction of myocardial movement, the length of the arrow is proportional to the velocity amplitude, and the velocity amplitude is defined as the absolute value of the myocardial movement velocity vector, that is, the velocity magnitude, and its unit is cm / s; The abnormal area highlight prompt satisfies both >τ and Myocardial segments >0.7 were flash-labeled.

[0013] The present invention also discloses an OSAS cardiac mechanics analysis system combining two-dimensional speckle tracking with tissue Doppler, and also includes a hardware integration component, wherein the hardware integration component is composed of an ultrasonic probe with a built-in inertial sensor and an edge computing device: The ultrasonic probe has a built-in inertial sensor to detect the displacement (Δx, Δy) of the ultrasonic probe in real time, and correct the image offset using the following formula:

[0014] in is the corrected two-dimensional image; is the original two-dimensional image; Δx, Δy are the displacements of the ultrasound probe in the X and Y directions, and the unit is pixel; The edge computing device is deployed on the ultrasound host and is used to locally calculate the layered strain parameters.

[0015] The present invention also discloses an OSAS cardiac mechanics analysis method of an OSAS cardiac mechanics analysis system using two-dimensional speckle tracking combined with tissue Doppler, and the OSAS cardiac mechanics analysis method comprises the following steps: Step S1, synchronously acquiring a two-dimensional ultrasonic grayscale image sequence and a myocardial tissue Doppler velocity spectrum through a dual-channel data acquisition module; Step S2, generating layered strain parameters and velocity parameters respectively through a parallel computing engine module; Step S3: Calculate the phase deviation through the dynamic correlation module and risk index ; Step S4: Outputting a visual report and risk level through the OSAS risk warning module, wherein the risk level includes low risk, medium risk and high risk: The low risk: ≤0.3; Medium risk: 0.3< ≤0.7; The high risk: >0.7.

[0016] Compared with the prior art, the advantages of the present invention are: (1) High-precision synchronization of multimodal data. Through the dual-channel synchronous acquisition module and preprocessing submodule, high-precision time axis alignment of the two-dimensional ultrasound grayscale image sequence and the Doppler velocity spectrum of myocardial tissue is achieved, which significantly reduces the phase deviation error caused by data splitting in traditional methods and provides a reliable basis for dynamic correlation analysis.

[0017] (2) Sensitive detection of myocardial compensation abnormalities. The dynamic time warping algorithm is used to quantify the phase deviation of the layered strain and velocity curves, combined with the preset threshold to trigger the warning, which significantly improves the sensitivity of myocardial movement asynchrony detection. By integrating the joint model of the layered strain change rate and the velocity attenuation rate, an intelligent graded warning of OSAS-related cardiac damage is achieved, improving the accuracy of early abnormality identification.

[0018] (3) Intelligent interaction and real-time diagnosis. The visual interface displays dynamic heat maps, velocity vector arrows, and abnormal segment markers to help doctors quickly locate high-risk areas and greatly improve diagnostic efficiency. The hardware integrated components ensure the immediate output of analysis results through displacement correction and localized real-time calculation, meeting clinical real-time requirements.

[0019] (4) Clinical applicability is enhanced. The standardized process integrates multimodal data acquisition, parameter calculation, risk modeling and visual output to achieve rapid screening and analysis, and the verification results are highly consistent with traditional diagnostic methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 is a flow chart of the system architecture of the present invention; Figure 2 Schematic diagram of the DTW algorithm and risk assessment of the present invention; Figure 3 It is a schematic diagram of the visualization interface of the present invention; Figure 4 FIG. 2 is a diagram of the hardware integration components of the present invention. DETAILED DESCRIPTION

[0022] To achieve the above objectives, the present invention is implemented through the following technical solutions: the present invention provides an OSAS cardiac mechanics analysis system combining two-dimensional speckle tracking and tissue Doppler, Figures 1 to 4 The system comprises: M1, dual-channel data acquisition module, this module is configured as an ultrasound probe to synchronously acquire a left ventricular two-dimensional ultrasound grayscale image sequence and a myocardial tissue Doppler velocity spectrum, and to achieve time axis alignment for the two types of data.

[0023] M2, parallel computing engine module, which is connected to the dual-channel data acquisition module, and includes a first processing module and a second processing module: The first processing module receives a two-dimensional ultrasound grayscale image sequence and generates longitudinal strain and circumferential strain parameters of the endocardial layer, the middle myocardial layer and the epicardial layer through a speckle tracking algorithm; The second processing module receives the Doppler velocity spectrum of myocardial tissue and calculates the peak value of myocardial motion velocity by time domain integration And acceleration parameters ; The dual-channel data acquisition module also includes a preprocessing submodule, as follows: The preprocessing submodule automatically segments the myocardial contours of the two-dimensional ultrasound grayscale image sequence and divides the endocardial layer, middle layer and epicardial layer areas; The preprocessing submodule filters the respiratory motion artifacts on the Doppler velocity spectrum of myocardial tissue and retains the velocity signals related to the cardiac systolic period; Through automatic segmentation of myocardial contours and respiratory artifact filtering, image segmentation errors and motion noise interference are eliminated, the extraction accuracy of layered strain parameters and velocity parameters is ensured, and data quality is improved.

[0024] M3, a dynamic association module, which is connected to the parallel computing engine module, and combines the longitudinal strain of the endocardial layer, the circumferential strain of the middle myocardial layer and the circumferential strain of the epicardial layer of the first processing module with the velocity peak and acceleration parameters of the second processing module in a time series to generate a strain and velocity joint feature map; The dynamic correlation module calculates the phase deviation between the layered strain curve S(t) and the velocity curve V(t) through the dynamic time warping algorithm, specifically including:

[0025] in is the dimensionless phase deviation metric; π is the optimal alignment path of two time series; is the path with the minimum cumulative distance among the alignment paths π; For time point The layered strain value, in %, includes the longitudinal strain of the endocardial layer and the circumferential strain of the middle myocardial layer; Time The myocardial velocity value, in cm / s, including the peak velocity ; Before calculating the phase deviation, the delamination strain value and speed value Perform standardization and convert into dimensionless parameters; when >τ, triggering myocardial compensation abnormality warning, where τ is a dimensionless threshold; The layered strain curve and velocity curve are aligned through the dynamic time warping algorithm, and the phase deviation between the two is quantified, which solves the problem of misjudgment caused by time axis asynchrony in traditional methods and significantly improves the accuracy of myocardial motion asynchrony detection.

[0026] M4, OSAS risk warning module, which is connected with the dynamic association module, generates the left ventricular systolic function compensation state classification and OSAS risk index based on the phase deviation and parameter change trend in the joint characteristic spectrum, and outputs them to the visual interactive interface; The OSAS risk warning module calculates the risk index using the following formula:

[0027] in is the OSAS risk index, the index range is 0-1; α and β are weight coefficients, α + β = 1; is the change in the longitudinal strain of the endocardial layer within the time window Δt, and its unit is %; is the change in the velocity peak value within the time window Δt, in cm / s; Δt is the length of the analysis time window, in seconds; A risk index was constructed based on the hierarchical strain change rate and velocity attenuation rate to achieve a three-level risk classification of OSAS-related cardiac injury and enhance the clinical practicality of dynamic risk assessment.

[0028] The visual interactive interface of the OSAS risk warning module includes display of layered strain thermal maps, superimposed tissue Doppler velocity vector arrows, and abnormal area highlighting prompts: Displaying a layered strain heat map based on the layered strain parameters generated by the first processing module, mapping the strain distribution of each segment of the left ventricle with a color gradient; Red area: longitudinal strain of endocardial layer <-20%; Yellow area: -20%≤endocardial layer longitudinal strain≤-15%; Green area: longitudinal strain of endocardial layer > -15%; The superimposed tissue Doppler velocity vector arrow is based on the velocity parameters generated by the second processing module , the direction of the arrow indicates the direction of myocardial movement, the length of the arrow is proportional to the velocity amplitude, and the velocity amplitude is defined as the absolute value of the myocardial movement velocity vector, that is, the velocity magnitude, and its unit is cm / s; The abnormal area highlight prompt satisfies both >τ and Myocardial segments >0.7 were flash-labeled; Through the dynamic overlay display of heat maps, velocity vector arrows and abnormal markers, the areas of abnormal myocardial mechanics are intuitively presented, helping doctors to quickly locate high-risk segments and improve diagnostic efficiency.

[0029] The OSAS cardiac mechanics analysis system of two-dimensional speckle tracking combined with tissue Doppler also includes hardware integration components, which are composed of built-in inertial sensors and edge computing devices in ultrasound probes: The ultrasonic probe has a built-in inertial sensor that detects the ultrasonic probe displacement (Δx, Δy) in real time and corrects the image offset using the following formula:

[0030] in is the corrected two-dimensional image; is the original two-dimensional image; Δx, Δy are the displacements of the ultrasound probe in the X and Y directions, and the unit is pixel; The edge computing device is deployed on the ultrasound host to locally calculate the layered strain parameters; The ultrasound probe has a built-in inertial sensor to correct image displacement, and the edge computing device implements localized real-time calculation, eliminating probe movement artifacts and reducing analysis delays, ensuring the immediacy and reliability of the result output.

[0031] The OSAS cardiac mechanics analysis method of the OSAS cardiac mechanics analysis system of two-dimensional speckle tracking combined with tissue Doppler includes the following steps: Step S1, synchronously acquiring a two-dimensional ultrasonic grayscale image sequence and a myocardial tissue Doppler velocity spectrum through a dual-channel data acquisition module; Step S2, generating layered strain parameters and velocity parameters respectively through a parallel computing engine module; Step S3: Calculate the phase deviation through the dynamic correlation module and risk index ; Step S4: Output a visual report and risk level through the OSAS risk warning module. The risk level includes low risk, medium risk and high risk: Low risk: ≤0.3; Medium risk: 0.3< ≤0.7; High risk: >0.7; By integrating data collection, parameter calculation and risk assessment through standardized processes, the whole process analysis can be completed quickly to meet the needs of clinical rapid screening, and the verification results are highly consistent with traditional diagnostic methods.

[0032] The working process of the system in four different scenarios is given below.

[0033] like Figure 1 , Figure 2 and Figure 4 As shown, Example 1: Real-time processing and hardware optimization First, the ultrasound probe acquires a two-dimensional ultrasound grayscale image sequence of the left ventricle at 50 frames per second, and simultaneously acquires the Doppler velocity spectrum of myocardial tissue at a sampling rate of 1 kHz. Timestamps are added to the two types of data using hardware clock synchronization technology to ensure that the time axis alignment error is less than 5 ms. The probe's built-in inertial sensor detects displacement in real time, and a displacement correction formula is used to eliminate image offset.

[0034] Next, the myocardial contour was automatically segmented, and the myocardium was divided into the endocardial layer, the middle layer, and the epicardial layer. The Doppler velocity spectrum of the myocardial tissue was high-pass filtered at 0.5 Hz to remove respiratory motion noise.

[0035] Secondly, the longitudinal strain and circumferential strain were calculated in the endocardial layer and the middle layer, and the filtered spectrum was integrated to extract the velocity peak and the maximum acceleration.

[0036] Again, a dynamic time warping algorithm is used to align the layered strain curve and velocity curve and calculate the phase deviation. When the phase deviation exceeds the preset threshold, a myocardial motion asynchrony warning is triggered.

[0037] Then, a risk index is generated based on the strain change rate and velocity attenuation rate within the sliding time window, and the three-level risk classification results of low, medium and high are output, and the thermal map, velocity vector arrows and abnormal segment flashing marks are displayed in real time.

[0038] Finally, the edge computing device runs the algorithm locally to ensure that the processing delay is less than 100ms, and the diagnosis results are transmitted to the hospital information system through standard protocols.

[0039] like Figure 2 and Figure 3 As shown, Example 2: High Sensitivity Scientific Research Analysis First, the ultrasound probe acquires a two-dimensional ultrasound grayscale image sequence at a high frame rate of 100 frames / second, samples the Doppler velocity spectrum of myocardial tissue at a high frequency of 2kHz, optimizes the time synchronization error to 3ms, and the probe displacement correction method is consistent with Example 1.

[0040] Next, the optimized automatic segmentation algorithm was used to improve the accuracy of myocardial stratification, and the filtering parameters were adjusted to retain more physiological signals.

[0041] Secondly, deformation correction technology is introduced to improve the measurement accuracy of strain parameters, expand the Doppler analysis range, and increase the calculation of acceleration parameters.

[0042] Thirdly, a constrained dynamic time warping algorithm is used to limit the curve alignment path deviation and adjust the phase deviation threshold to enhance the detection sensitivity.

[0043] Then, the risk index formula is expanded, and the acceleration parameters are integrated to improve the early warning capability. The visualization interface superimposes the acceleration curve and multi-level thermal map classification.

[0044] Finally, high-performance computing devices are used to accelerate algorithm execution and support the export of raw data for scientific research analysis.

[0045] like Figure 1 and Figure 4 As shown, Example 3: Portable primary care adapter First, the wireless ultrasound probe acquires a two-dimensional ultrasound grayscale image sequence at 30 frames per second and samples the myocardial tissue Doppler velocity spectrum at 500 Hz. The time synchronization error is extended to 10 ms, which meets the needs of grassroots diagnosis and simplifies the probe displacement correction function.

[0046] Next, a lightweight segmentation algorithm is used to replace the deep learning model, and the filtering algorithm runs on the terminal device to reduce resource usage.

[0047] Secondly, only the longitudinal strain and peak velocity parameters of the endocardial layer were calculated, and the analysis of the middle layer and acceleration parameters was omitted to simplify the process.

[0048] Again, the cloud server runs the dynamic time warping algorithm and returns the results, maintaining the default phase deviation threshold to ensure consistency.

[0049] Then, the risk classification is simplified into two levels: high risk and non-high risk, and the heat map only displays red and green to reduce the complexity of the interaction.

[0050] Finally, the tablet runs lightweight analysis software that supports offline data caching and batch processing.

[0051] like Figure 1-Figure 3 As shown, Example 4: Multi-center collaboration and data standardization First, standardized ultrasound probe parameters are used to collect data, and the time synchronization error is strictly controlled within 5ms.

[0052] Next, a collaborative optimization segmentation algorithm is used to improve the consistency of multi-center data, and the filtering process is consistent with Example 1.

[0053] Secondly, the strain parameters of the endocardial and middle layers were calculated, and the peak velocity and acceleration parameters were extracted.

[0054] Again, the cloud server cluster processes the dynamic time warping algorithm in parallel, maintaining the default phase deviation threshold to unify the evaluation criteria.

[0055] Then, a standardized risk index model is used to generate grading results, and the three-dimensional model on the web dynamically displays the distribution of mechanical abnormalities in each segment.

[0056] Finally, all data are packaged and stored according to medical imaging standards, and the analysis results are output in a cross-platform format to support multi-center statistics and analysis.

[0057] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A two-dimensional speckle tracking combined with tissue Doppler OSAS cardiac mechanics analysis system, characterized in that: Includes the following modules, M1, dual-channel data acquisition module, which is configured as an ultrasound probe to synchronously acquire a left ventricular two-dimensional ultrasound grayscale image sequence and a myocardial tissue Doppler velocity spectrum, and to achieve time axis alignment of the two types of data; M2, parallel computing engine module, which is connected to the dual-channel data acquisition module, and includes a first processing module and a second processing module: The first processing module receives a two-dimensional ultrasound grayscale image sequence and generates longitudinal strain and circumferential strain parameters of the endocardial layer, the middle myocardial layer and the epicardial layer by a speckle tracking algorithm; The second processing module receives the Doppler velocity spectrum of myocardial tissue and calculates the peak value of myocardial motion velocity by time domain integration. And acceleration parameters ; M3, a dynamic association module, which is connected to the parallel computing engine module, and which performs time series fusion of the longitudinal strain of the endocardial layer, the circumferential strain of the middle myocardial layer, and the circumferential strain of the epicardial layer of the first processing module with the velocity peak value and the acceleration parameter of the second processing module to generate a strain and velocity joint feature map; M4, OSAS risk warning module, which is connected to the dynamic association module, generates the left ventricular systolic function compensation state classification and OSAS risk index based on the phase deviation and parameter change trend in the joint characteristic spectrum, and outputs them to the visual interactive interface.

2. The OSAS cardiac mechanics analysis system of two-dimensional speckle tracking combined with tissue Doppler according to claim 1, characterized in that: The dynamic correlation module calculates the phase deviation between the layered strain curve S(t) and the velocity curve V(t) by a dynamic time warping algorithm, specifically including: in is the dimensionless phase deviation metric; π is the optimal alignment path of two time series; is the path with the minimum cumulative distance among the alignment paths π; For time point The layered strain value, in %, includes the longitudinal strain of the endocardial layer and the circumferential strain of the middle myocardial layer; For time point The myocardial velocity value, in cm / s, including the peak velocity ; Before calculating the phase deviation, the delamination strain value and speed value Perform standardization and convert into dimensionless parameters; when >τ, a myocardial compensation abnormality warning is triggered, where τ is a dimensionless threshold.

3. The OSAS cardiac mechanics analysis system of two-dimensional speckle tracking combined with tissue Doppler according to claim 1, characterized in that: The OSAS risk warning module calculates the risk index by the following formula: in is the OSAS risk index, the index range is 0-1; α and β are weight coefficients, α + β = 1; is the change in the longitudinal strain of the endocardial layer within the time window Δt, and its unit is %; is the change in the peak velocity within the time window Δt, in cm / s; Δt is the length of the analysis time window, in seconds.

4. The OSAS cardiac mechanics analysis system of two-dimensional speckle tracking combined with tissue Doppler according to claim 1, characterized in that: The dual-channel data acquisition module also includes a preprocessing submodule, which is as follows: The preprocessing submodule automatically segments the myocardial contour of the two-dimensional ultrasound grayscale image sequence to divide the endocardial layer, middle layer and epicardial layer regions; The preprocessing submodule performs respiratory motion artifact filtering on the Doppler velocity spectrum of the myocardial tissue to retain velocity signals related to the cardiac systolic period.

5. The OSAS cardiac mechanics analysis system of two-dimensional speckle tracking combined with tissue Doppler according to claim 1, characterized in that: The visual interactive interface of the OSAS risk warning module includes displaying layered strain thermal maps, superimposed tissue Doppler velocity vector arrows and abnormal area highlighting prompts: The layered strain thermogram is displayed based on the layered strain parameters generated by the first processing module, and maps the strain distribution of each segment of the left ventricle with a color gradient; Red area: longitudinal strain of endocardial layer <-20%; Yellow area: -20%≤endocardial layer longitudinal strain≤-15%; Green area: longitudinal strain of endocardial layer > -15%; The superimposed tissue Doppler velocity vector arrow is based on the velocity parameter generated by the second processing module , the direction of the arrow indicates the direction of myocardial movement, the length of the arrow is proportional to the velocity amplitude, and the velocity amplitude is defined as the absolute value of the myocardial movement velocity vector, that is, the velocity magnitude, and its unit is cm / s; The abnormal area highlight prompt satisfies both >τ and Myocardial segments >0.7 were flash-labeled.

6. The OSAS cardiac mechanics analysis system of two-dimensional speckle tracking combined with tissue Doppler according to claim 5, characterized in that: It also includes a hardware integration component, which is composed of an ultrasonic probe with a built-in inertial sensor and an edge computing device: The ultrasonic probe has a built-in inertial sensor to detect the displacement (Δx, Δy) of the ultrasonic probe in real time, and correct the image offset using the following formula: in is the corrected two-dimensional image; is the original two-dimensional image; Δx, Δy are the displacements of the ultrasound probe in the X and Y directions, and the unit is pixel; The edge computing device is deployed on the ultrasound host and is used to locally calculate the layered strain parameters.

7. The OSAS cardiac mechanics analysis method of the OSAS cardiac mechanics analysis system of two-dimensional speckle tracking combined with tissue Doppler according to claim 1, characterized in that: The OSAS cardiac mechanics analysis method comprises the following steps: Step S1, synchronously acquiring a two-dimensional ultrasonic grayscale image sequence and a myocardial tissue Doppler velocity spectrum through a dual-channel data acquisition module; Step S2, generating layered strain parameters and velocity parameters respectively through a parallel computing engine module; Step S3: Calculate the phase deviation through the dynamic correlation module and risk index ; Step S4: Outputting a visual report and risk level through the OSAS risk warning module, wherein the risk level includes low risk, medium risk and high risk: The low risk: ≤0.3; Medium risk: 0.3< ≤0.7; The high risk: >0.7.

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