13 results about "End diastole" patented technology

The invention discloses an aortic valve function evaluation device which comprises a processor and a memory, and the memory stores programs or instructions capable of running on the processor. When the program or the instruction is executed by the processor, the following steps are realized: acquiring a first echocardiogram of a target object corresponding to a final systole and a second echocardiogram of a target object corresponding to a final diastole in a cardiac cycle, and acquiring medical record data of the target object; determining a first mask pattern corresponding to the first echocardiogram and a second mask pattern corresponding to the second echocardiogram according to the first echocardiogram, the second echocardiogram and an aortic valve segmentation model; determining an aortic valve morphological index of the target object according to the first mask pattern and the second mask pattern; determining aortic valve functional indexes of the target object according to the medical record data of the target object; and determining and outputting an aortic valve function evaluation result of the target object according to the first mask pattern, the second mask pattern, the aortic valve morphological index and the aortic valve functional index.

A system for monitoring right ventricular systolic dysfunction includes a hemodynamic sensor that produces a hemodynamic sensor signal representative of a right ventricular pressure waveform of the patient, a display, one or more processors, and computer-readable memory. The computer-readable memory is encoded with instructions that, when executed by the one or more processors, cause the system to receive the hemodynamic sensor signal representative of the right ventricular pressure waveform of the patient, extract right ventricular peak systolic pressure and right ventricular end diastolic pressure from the right ventricular pressure waveform of the patient, determine a ratio of right ventricular peak systolic pressure over right ventricular end diastolic pressure, and output the ratio of right ventricular peak systolic pressure over right ventricular end diastolic pressure to the display for monitoring the presence of right ventricular systolic dysfunction based on the ratio of peak systolic pressure over end diastolic pressure.

The present application relates to a kind of cardiac magnetic resonance longitudinal relaxation time measurement method, medium and equipment.The measurement method includes the following steps: S1 uses MOLLI sequence respectively before and after scanning contrast;Specifically, in the before and after scanning contrast, by setting different initial inversion time TI, setting 3 groups of LL experiment LL1, LL2, LL3 triggered by continuous ECG, enough relaxation curve sampling points are obtained after fusion;And data is collected at the end of diastole of cardiac cycle, and 1 image is obtained per heartbeat;S2 image processing.This measurement method can realize single-pixel high-resolution T1 mapping under the breath holding of selection data acquisition and multi-LL experiment data fusion, give consideration to high accuracy, high resolution and high efficiency, and have good compatibility and practicality, provide new scheme for early diagnosis of heart disease, lesion quantification and prognosis evaluation, have wide clinical application prospect.

The invention provides a method for measuring the left ventricular ejection fraction of a dynamic echocardiography. The method comprises the following steps: inputting a to-be-identified echocardiogram sequence into a neural network segmentation model based on multi-frame feature aggregation, then performing spatial feature coding on each frame of image of the to-be-identified echocardiogram sequence through a spatial feature encoder structure to obtain a spatial feature map corresponding to each frame of image, and finally, identifying the to-be-identified echocardiogram sequence according to the spatial feature map. Performing cross-frame and cross-section spatio-temporal feature aggregation on the spatial feature pattern through a spatio-temporal feature aggregation structure to obtain global spatio-temporal features including time sequence information of a heart apex two-cavity section and a heart apex four-cavity section; the left ventricular ejection fraction determining method comprises the steps of generating a left ventricular membrane segmentation mask of a terminal diastole frame and a terminal systole frame on the basis of global spatial-temporal characteristics and spatial shallow layer characteristics corresponding to the terminal diastole frame and the terminal systole frame, and finally determining the left ventricular ejection fraction on the basis of the left ventricular membrane segmentation mask of the terminal diastole frame and the terminal systole frame.

This application provides an ultrasound cardiac dynamic monitoring system and method, relating to the field of ultrasound cardiac function dynamic monitoring technology. The system includes: a patch-type ultrasound probe, a hydrogel patch, a wearable hardware module, and a cardiac function analysis module. The cardiac function analysis module is configured to: receive the ultrasound image; determine a target sampling line in the ultrasound image based on a reinforcement learning model; control the wearable hardware module to acquire M-mode images along the target sampling line; input the M-mode images into a deep learning model to output the key point positions of the left ventricular septum and the left ventricular posterior wall at end-diastole and end-systole based on the deep learning model; calculate the left ventricular ejection fraction (LVEF) based on the LVEF and the key point positions; the LVEF represents the dynamic monitoring and detection results of cardiac function. This system can improve the effectiveness and accuracy of dynamic cardiac monitoring.

The invention provides a coronary angiography image-based end-diastolic recognition method and related equipment, and the method comprises the steps: collecting a plurality of frames of coronary angiography images to construct a coronary angiography sequence which at least comprises coronary angiography images of two cardiac cycles; the coronary angiography sequence is input into a trained recognition model for probability prediction of the end diastole to obtain a probability sequence, and the recognition model is used for extracting spatial features and time sequence features of each frame of image, calculating attention between frames and outputting a probability value of each frame of coronary angiography image belonging to the end diastole, the end-diastole image is an image with most dispersed blood vessels in the cardiac cycle, and the probability value of the end-diastole image is maximum; and extracting a wave crest from the probability sequence output by the recognition model by adopting a wave crest extraction algorithm, wherein the coronary angiography image corresponding to the wave crest is the end-diastole image. According to the method, the end-diastole prediction can be carried out on the coronary angiography sequence image, the accuracy is high, the generalization ability is high, and the robustness is good.

The application discloses a method, system, device, medium and product for evaluating right ventricular function, and relates to the technical field of medical image processing and ultrasonic diagnosis. The method comprises the following steps: acquiring a sequence of multiple two-dimensional ultrasonic images of a right ventricle of a heart and spatial pose information of the sequence, and generating point cloud data; identifying an end-diastolic frame, an end-systolic frame and an anatomical structure point, and acquiring sparse point cloud data of the anatomical structure point; constructing a three-dimensional grid model of the end-diastolic frame and the end-systolic frame; determining multiple tracking points of a tricuspid annulus and acquiring a three-dimensional coordinate trajectory; calculating longitudinal displacement, area change rate and peak time dispersion based on the trajectory, and completing function evaluation. The application overcomes the limitations of angle dependence and point substitution of traditional TAPSE technology, realizes comprehensive evaluation of right ventricular function from three dimensions of longitudinal displacement, area change rate and systolic synchrony, and improves the accuracy and clinical value of evaluation.

The invention discloses a method, a system, equipment, a medium and a product for evaluating a right ventricular function, and relates to the technical field of medical image processing and ultrasonic diagnosis. The method comprises the following steps: acquiring a multi-frame two-dimensional ultrasonic image sequence of a right ventricle of a heart and spatial pose information of the multi-frame two-dimensional ultrasonic image sequence, and generating point cloud data; identifying the last diastole frame, the last systole frame and the anatomical structure point, and obtaining sparse point cloud data of the anatomical structure point; constructing a three-dimensional grid model of the last diastole frame and the last systole frame; determining a plurality of tracking points of the tricuspid valve ring and acquiring a three-dimensional coordinate trajectory; and calculating the longitudinal displacement, the area change rate and the peak arrival time dispersion based on the trajectory to complete the function evaluation. According to the method, the limitation that a traditional TAPSE technology depends on a point instead of a surface is overcome, comprehensive evaluation of the right ventricular function from the three dimensions of longitudinal displacement, the area change rate and contraction synchronism is achieved, and the accuracy and clinical value of evaluation are improved.

Embodiments of the present invention provide a system for automatically deriving parameters of a human heart from ultrasound results. The first neural network is arranged to receive a plurality of echocardiography images and to classify the images as one of at least a two-lumen tangent plane and a four-lumen tangent plane. The second neural network is arranged to receive echocardiography images comprising two or four-lumen tangent planes and to identify endocardial boundaries of a left ventricle (LV) for each tangent plane. End systolic and end diastolic images are then identified and parameters such as LV volume, ejection fraction, overall longitudinal strain, and regional longitudinal strain are calculated.

The present application belongs to the field of medical devices and physiological signal detection technology, and relates to a pulse wave analysis method and system based on piezoelectric dynamics characteristics. The present application compensates for the attenuation of the subcutaneous tissue on the pulse wave through active acoustic detection, emits high-frequency mechanical vibration waves at the end of diastole using multi-frequency voltage pulses, and receives reflected echoes to construct an equivalent acoustic impedance transfer function and an acoustic inverse compensation filter. The present application restores the true arterial vessel wall dynamics by performing frequency domain deconvolution operation on the original pulse wave signal, locates key physiological event points, estimates the local pulse wave propagation speed using a single-point piezoelectric sensor without the need for multi-point measurement. In combination with the fluid mechanics equation, the present application separates the forward incident wave and the backward reflected wave, calculates the absolute amplitude ratio to evaluate the vascular compliance, effectively eliminates the interference of subcutaneous fat and muscle tissue, improves the accuracy and reliability of the evaluation, and provides a new tool for cardiovascular function evaluation.

Disclosed are a method and a system for synthesizing echocardiogram video segments with myocardium motion modeling using a combination of diffusion model and neural ordinary differential equations. The method includes the steps of: synthesizing the video echocardiography video that conditions the segmentation map of the first frame of the cardiac cycle (end-diastole) using a video diffusion model; estimating the motion, or a diffeomorphic registration between a given frame from generated video and the first frame of the cardiac cycle using a neural ordinary differential equation (ODE) model; and obtaining an annotated echocardiogram video by propagating the segmentation map of the first frame of the cardiac cycle through the generated video using the estimated motion.

The invention relates to a mitral valve function evaluation device which comprises a processor and a memory, and the memory stores programs or instructions capable of being executed on the processor. When the program or the instruction is executed by the processor, the following steps are realized: acquiring a first echocardiogram of a target object corresponding to a final systole, a second echocardiogram of a target object corresponding to a final diastole and a blood flow velocity time sequence; determining a first mask pattern corresponding to the first echocardiogram and a second mask pattern corresponding to the second echocardiogram according to the first echocardiogram, the second echocardiogram and a mitral valve segmentation model; according to the first mask pattern and the second mask pattern, mitral valve structural features are determined; determining mitral valve calcification features according to a calcification region of interest in the first echocardiogram; according to the blood flow velocity time sequence, mitral valve blood flow characteristics are determined; and determining a mitral valve function evaluation result of the target object according to the first mask pattern, the second mask pattern, the mitral valve structural features, the mitral valve blood flow features and the mitral valve calcification features.

The invention discloses an aortic valve function evaluation device which comprises a processor and a memory, and the memory stores programs or instructions capable of running on the processor. When the program or the instruction is executed by the processor, the following steps are realized: acquiring a first cardiovascular three-dimensional diagram corresponding to the end systole and a second cardiovascular three-dimensional diagram corresponding to the end diastole of a target object in a cardiac cycle, and medical record data of the target object; according to the first cardiovascular three-dimensional diagram, the second cardiovascular three-dimensional diagram and an aortic valve segmentation model, determining a first three-dimensional mask diagram corresponding to the first cardiovascular three-dimensional diagram and a second three-dimensional mask diagram corresponding to the second cardiovascular three-dimensional diagram; according to the medical record data, determining aortic valve hemodynamic indexes of the target object; and inputting the first three-dimensional mask map, the second three-dimensional mask map and the aortic valve hemodynamic indexes into an aortic valve function evaluation model to obtain and output an aortic valve function evaluation result of the target object.