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A novel 4D PDE-based approach for tracking the left ventricle wall and estimating myocardial wall thickening outperformed 2D estimation approaches on in vivo data.
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A novel 4D PDE-based tracking approach improves the accuracy of left ventricular wall thickening assessment from cine CMRI compared to 2D methods.
A novel framework for assessing wall thickening from 4D cine cardiac magnetic resonance imaging (CMRI) is proposed. The proposed approach is primarily based on using geometrical features to track the left ventricle (LV) wall during the cardiac cycle. The 4D tracking approach consists of the following two main steps: (i) Initially, the surface points on the LV wall are tracked by solving a 3D Laplace equation between two successive LV surfaces; and (ii) Secondly, the 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 in order to remove inconsistencies and preserve the anatomy of the heart wall during the tracking process. Then 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 using the solution of the 3D Laplace equation. Experimental results on in vivo data confirm the accuracy and robustness of our method. Moreover, the comparison results demonstrate that our approach outperforms 2D wall thickening estimation approaches.
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Sliman et al. (2014) studied Myocardium function assessment. 4D PDE-based approach using geometrical features and GGMRF image model vs. 2D wall thickening estimation approaches was evaluated on Accuracy and robustness of myocardial wall thickening estimation. A novel 4D PDE-based approach for tracking the left ventricle wall and estimating myocardial wall thickening outperformed 2D estimation approaches on in vivo data.
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