Automatic active appearance model segmentation of 3D echocardiograms

A fully automated segmentation for 3D echocardiography (3DE) using 3D Active Appearance Models (AAM) was developed and evaluated on 99 patients. The method used ultrasound specific grey value normalization and two matching algorithms were tested. To our knowledge this is the first report on a fully operational 3D AAM employed in 3DE on a large scale. The 3D AAM detected the endocardial contours accurately, even in the presence of large variations in left ventricular appearance and shape. Matching was successful in 91% of patients and resulted in a median point-to-surface error of 2.69 mm (av±sd: 2.91±1.03mm). Results indicate that fully automated AAM analysis of 3DE is practically feasible in datasets of mixed origin and quality.