Fully automated segmentation of the left ventricle applied to cine MR images: description and results on a database of 45 subjects.

A fully automated segmentation method of the left ventricle from short-axis cardiac MR images is proposed and evaluated. The segmentation is based on morphological filtering and gradient vector flow snake for which an automatic setting of parameters has already been proposed. The present work focuses on the automatic detection of a region of interest (ROI) surrounding the left ventricle, prior to the segmentation step. The whole process was applied to the MICCAI 2009 Left Ventricle Challenge database containing 45 subjects (9 healthy subjects and 36 with pathology). The automatic detection of the ROI was judged accurate in 86% of the cases. It failed in 2% of the slices and provided an overestimation in 9% of the slices. Furthermore, the endocardial segmentation was accurate in 80% of the slices and the epicardial was judged satisfactory in 71% of the slices. This fully automated procedure can thus be used as a first step in a user controlled approach, in order to reduce the total number of interactions.