Mitral valve prolapse detection using landmark extraction from echocardiography sequences.

The mitral valve is one of the four valves of the heart, whose function is to keep the blood flow in the physiological direction when the heart contracts. There is no satisfactory method allowing an automated assessment for Mitral Valve Prolapse (MVP) detection. In this paper an algorithm is proposed for detecting MVPs automatically from an echocardiography sequence. Our algorithm has two steps; first landmarks are extracted from the echocardiography sequence. Then landmarks are tracked in the whole frames of a sequence. In order to detect MVP and isolate it from a normal mitral motion, we extracted some features (such as maximum deviation of valve angle and spectral power ratio) from the motion pattern of a mitral valve and we gave these features to a SVM classifier. The results show that the mitral motion trajectory may have good discriminative features for detecting MVP (87% specificity and 84% sensitivity).