Level set-based tracking of the endocardium without a shape prior from 3D ultrasound images

Abstract

A level set-based method for tracking the endocardium from 3D ultrasound images is presented. The tracking process is initialized by a manual delineation and performed automatically. The method does not use a shape prior model, removing the requirement of acquiring large sets of training data, and providing adaptivity for abnormal cases. At each image frame, the edge strength is estimated and locations with strong edges are used to compute the region-based surface deformation, which is then propagated to the rest of the image volume. The approach is evaluated with 10 sequences of canine subjects including 5 ischemic image sequences. The results show that the method performs with error values below the interobserver variability of manual segmentation, and is able to robustly follow the cardiac wall movement.