Abnormalities in Mitral Valve of Heart Detection and Analysis Using Echocardiography Images

Abstract

Mitral valve is the second most important chamber in the heart which often faces mitral valves stenosis, mitral valves regurgitation and mitral valve prolapsed. This leads to a sudden heart attack where the blood flow in the ventricles pushes back through the backward direction indicating sudden rise and fall in the function of heart. Thus it is threated to be a serious issue which needs to be treated at the earliest, by using an echocardiography method which uses the ultra sound waves bypassing through the muscles and creates an image of the heart muscles. The image captured is analysed with respect to the position of the mitral valve and the blood pressure directions in order to detect the occurrence of heart attack and track the direction of blood at the earlier stage. This paper presents a detailed survey on the different techniques available for the mitral valve stenosis, regurgitation and valve prolapse. Even though the methods like, computer assisted visual feedback, magnetic tracking system, robotically-actuated delivery sheath, parameterized real operations, probabilistic, hierarchical and discriminant, proximal flow convergence method, image acquisition and contour delineation, 3D planimetry technique, support vector machines, Saint Venant-Kirchhoff elasticity model, zero d models, remodelling phenotype, k means clustering 3D tee methods, boosting learning, optical flow algorithm and proximal flow convergence methods are used. Probabilistic hierarchical and discriminant framework and learning recognition model produces more than 90% accuracy. But optical flow algorithm and proximal flow convergence method produces 100% accuracy.