FoCA: A new framework of coupled geometric active contours for segmentation of 3D cardiac magnetic resonance images

Abstract

In this paper, a new framework of coupled active contours (FoCA) is proposed for segmentation of the left ventricle myocardium, in cardiac magnetic resonance (CMR) images, without primary learning and user-driven segmentation. Primarily, we suggest a pair of coupled geometric active contours (GACs) for segmentation of the endo- and epicardial boundaries of the left ventricle in every CMR slice. The energy functional of each active contour includes the edge and shape terms of the STACS energy functional, regulator term of the local binary fitting (LBF), and new region and coupling terms. Two new patch-based region terms, inspired by LBF and piecewise model, are proposed to effectively handle intensity inhomogeneity of CMR images. Furthermore, a coupling energy term is added to the epicardial energy functional to avoid intersection with the endocardial curve. For 3D implementation, every 2D active contour in each slice is effectively jointed to the corresponding curves in the previous and next slices (of the same volume) by using a new coupling energy term, obtained by extending the 2D length-shortening regulator. Also, the initial contour and algorithm parameters are automatically regulated. Finally, 3D+t implementation is performed by using the sequential initialization method. Experimental results demonstrated that the proposed method provided superior solution quality compared to a large number of counterpart algorithms by using two well-known frequently-used databases.