Automated left ventricular segmentation in cardiac MRI

Abstract

We present an automated left ventricular (LV) myocardial boundary extraction method. Automatic localization of the LV is achieved using a motion map and an expectation maximization algorithm. The myocardial region is then segmented using an intensity-based fuzzy affinity map and the myocardial contours are extracted by cost minimization through a dynamic programming approach. The results from the automated algorithm compared against the experienced radiologists using Bland and Altman analysis were found to have consistent mean bias of 7% and limits of agreement comparable to the inter-observer variability inherent in the manual method.