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Joint Segmentation of 3D Femoral Lumen and Outer Wall Surfaces from MR Images

机译:从MR图像联合分割3D股骨腔和外壁表面

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We propose a novel algorithm to jointly delineate the femoral artery lumen and outer wall surfaces from 3D black-blood MR images, while enforcing the spatial consistency of the reoriented MR slices along the medial axis of the femoral artery. We demonstrate that the resulting optimization problem of the proposed segmentation can be solved globally and exactly by means of convex relaxation, for which we introduce a novel coupled continuous max-flow (CCMF) model based on an Ishikawa-type flow configuration and show its duality to the studied convex relaxed optimization problem. Using the proposed CCMF model, the exactness and globalness of its dual convex relaxation problem is proven. Experiment results demonstrate that the proposed method yielded high accuracy (i.e. Dice similarity coefficient > 85%) for both the lumen and outer wall and high reproducibility (intra-class correlation coefficient of 0.95) for generating vessel wall area. The proposed method outperformed the previous method, in terms of computation time, by a factor of ~ 20.
机译:我们提出了一种新颖的算法,可以从3D黑血MR图像中共同描绘出股动脉的内腔和外壁表面,同时加强沿着股动脉的中轴重新定向的MR切片的空间一致性。我们证明了所提出的分割方法所产生的最优化问题可以通过凸松弛来全局地和精确地解决,为此,我们引入了一种基于石川型流动配置的新型耦合连续最大流量(CCMF)模型,并显示了其对偶性到研究的凸松弛优化问题。利用所提出的CCMF模型,证明了其双凸松弛问题的正确性和全局性。实验结果表明,该方法对管腔和外壁都具有很高的精度(即骰子相似系数> 85%),并且在生成血管壁面积方面具有很高的可重复性(类内相关系数为0.95)。在计算时间方面,所提出的方法比以前的方法要好20倍。

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