Automatic 3D Whole Heart Registration-Based Segmentation Using Mutual Information and B-Splines

Abstract

Abstract Extracting the anatomical information of whole heart to computed tomography (CT) images is important in both anatomic and functional studies of human heart. The most recent advances in image segmentation adopt an interactive approach. That approach is prone inconsistency and variability, such as, laborious, time-consuming and subjective process. To avoid this, an automatic technique for whole heart segmentation of cardiac CT volumes is highly desired. In this paper, we propose a novel three-dimensional (3D) automatic anatomy segmentation method for the whole heart, in which, process of the registration divides into two steps, coarse registration and accurate registration. The coarse registration using affine transformation is first used to localize the heart and the accurate registration uses cubic B-splines to parameterize the deformation field, and Normalized Mutual Information (NMI) as the similarity measure. The novelty of our method is that the registration procedure is automated and anatomically driven. Exploiting similarity structures of different individuals, the segmentation problem is converted to a registration problem. Test results show that our method is valid and is robust to noise by providing segmentation results on real heart CT images.