Fast and accurate segmentation of the LV in MR volumes using a deformable model with dynamic programming

This paper proposes a new approach for the segmentation of the endocardium of the left ventricle using short axis magnetic resonance (MR) images. The proposed method comprises two main stages. First, each image is converted to polar coordinates, and an edge map is computed from the transformed image. Then, the contour of the left ventricle (LV) is estimated by computing the optimal path along the edge map, using a dynamic programming approach. The system is evaluated on a public database comprising 660 magnetic resonance volumes and the results testify its usefulness both in terms of running time and accuracy. The proposed methodology is able to segment a whole volume in 1.5 seconds achieving an average Dice similarity coefficient of 85.9% (8.3%), which compares favorably with related state-of-the-art methods.