Detecting endocardial boundary in echocardiogram by anisotropic filtering and entropy-weighted features

Reading echocardiograms is important to evaluate cardiac function. Due to influence of speckle, shadow and artifacts, analyzing echocardiograms requires more effort and energy than other medical imaging. A computerized method is proposed by this study to automatize the detection of endocardial boundaries based on B-mode echocardiograms in shortaxis view. Local entropy, anisotropic filtering, and cost image technique are used to pre-process the images to enhance the difference of blood region from the segments of myocardium and fix missing edge components. Above 80% of true positive can be achieved by the method when comparing to boundaries identified manually.