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A novel 4D PDE-based approach for accurate assessment of myocardium function using cine cardiac magnetic resonance images

机译:一种基于4D PDE的新颖方法,可使用电影心脏磁共振图像准确评估心肌功能

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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.
机译:提出了一种从4D电影心脏磁共振成像(CMRI)评估壁增厚的新颖框架。所提出的方法主要基于在心动周期期间使用几何特征跟踪左心室(LV)壁。 4D跟踪方法包括以下两个主要步骤:(i)首先,通过求解两个连续的LV表面之间的3D Laplace方程来跟踪LV壁上的表面点; (ii)其次,使用广义高斯-马尔可夫随机场(GGMRF)图像模型通过能量最小化成本函数迭代地调整所跟踪的LV表面点的位置,以消除不一致之处并保留心脏壁的解剖结构跟踪过程。然后,通过使用3D Laplace方程的解,通过分配相应的点或LV壁的心内膜和心外膜表面之间的匹配来估计心肌壁的增厚。体内数据的实验结果证实了我们方法的准确性和鲁棒性。此外,比较结果表明,我们的方法优于2D壁厚估计方法。

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