Assessment of right ventricular (RV) function is known to be of diagnostic value in patients with RV dysfunction. Because of its complex anatomic shape, automated determination of the RV volume is difficult and strong reliance on geometric assumptions is not desired. A method for automated RV assessment was developed using three-dimensional (3-D) echocardiography without relying on a priori knowledge of the cardiac anatomy. A 3-D adaptive filtering technique that optimizes the discrimination between blood and myocardium was applied to facilitate endocardial border detection. Filtered image data were incorporated in a segmentation model to automatically detect the endocardial RV border. End-systolic and end-diastolic RV volumes, as well as ejection fraction, were computed from the automatically segmented endocardial surfaces and compared against reference volumes manually delineated by two expert cardiologists. The results reported good performance in terms of correlation and agreement with the results from the reference volumes.