Edge detection in echocardiographic images based on differential tissue attenuation rates

Abstract

A basic goal in the analysis of echocardiographic images is the detection of endocardial border points. The authors have implemented a new method of edge detection which is based on the differing attenuation rates of blood and myocardial tissue. At each point in the image, the average attenuation rates in the portions of tissue radically preceding and radially following the point are estimated by least-squares regression. If one of these rates is sufficiently close to that of blood, and other is sufficiently close to that of myocardium, then the point is flagged as an edge point. This paper describes how this method is implemented in software, and presents the results of applying the method to a set of sample images.