The proposed segmentation approach demonstrated superior performance over other methods. Specifically, the comparative results on the publicly available MICCAI 2009 Cardiac MR Left Ventricle Segmentation database documented superior performance of the proposed approach over published methods. Additionally, the high accuracy of our segmentation approach leads to accurate estimation of the global performance indexes, as evidenced by the Bland-Altman analyses of the end-systolic volume (ESV), end-diastolic volume (EDV), and the ejection fraction (EF) ratio.
A novel approach for assessing the myocardial function using 4D cine cardiac magnetic resonance imaging (CMRI) is proposed. The myocardial function is assessed by estimating the left ventricle (LV) wall thickening based on a novel 4D tracking approach that tracks the LV wall during the cardiac cycle. Initially, the proposed 4D approach tracks the surface points on the LV wall by solving a 3D Laplace equation between each two subsequent LV surfaces. In order to remove inconsistencies and preserve the anatomy of the heart wall during the tracking process, the initial locations of the tracked LV surface points are iteratively adjusted through an energy minimization cost function using a generalized Gauss-Markov random field (GGMRF) image model. Using the iteratively adjusted solution of the 3D Laplace equation, the myocardial wall thickening is estimated by co-allocation of the corresponding points, or matches between the endocardium and epicardium surfaces of the LV wall. Experimental results on in vivo data demonstrate that our approach outperforms 2D wall thickening estimation approaches.
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