Endocardium segmentation in 3D Transesophageal Echocardiography

Saurabh Vyas, Ryan Mukherjee, Federico Sosa, Philippe Burlina

Abstract: Segmentation of endocardial walls from 3D Transesophageal Echocardiography (3D TEE) is a critical step in helping characterize the pathophysiology of heart disease. The goal of this paper is (a) to present a new level set method based on the use of a novel inhibition function and (b) to asses its performance and that of other best of breed segmentation algorithms such as graph cuts and random walker as applied to 3D TEE segmentation. The method is tested on 14 sequences collected from 8 patients; it shows good agreement with the ground truth developed by physicians, and demonstrates similar (if not better) performance than current segmentation methods.