Echocardiographic myocardial edge detection using an optimization protocol

Abstract

The definition of the ventricular myocardial shape in echocardiographic ultrasound cross-sectional images is a difficult task due to the low quality of these images and the high noise levels present. An automatic protocol has been developed for high-speed detection of cavity boundaries in sequential 2-D echocardiograms. A 1-D cyclic Markov random field is defined, where the field's random variables are radii emanating from the cavity's center of gravity. An optimization using simulated annealing is performed upon an energy function defined by these random variables. This energy function is composed of a linear combination of elements which represent optimal edge detection, cavity wall smoothness, temporal continuity, and cavity volume maximization. The improved decision rule, which results from this optimization, produced highly encouraging results.<>