超声心动图二维序列中使用形状和运动约束水平集的多视图心肌跟踪

T. Dietenbeck, D. Barbosa, M. Alessandrini, R. Jasaityte, Valérie Robesyn, J. D’hooge, D. Friboulet, O. Bernard
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引用次数: 7

摘要

超声心动图图像的心肌分割是心脏病诊断的一项重要任务。由于超声图像固有的问题(即低对比度、斑点噪声、信号缺失、阴影的存在),这项任务很困难。在本文中,我们扩展了[1]最近提出的水平集方法,以便在超声心动图序列中跟踪整个心肌。为此,我们建立了一个新的运动优先能,它约束了隐函数的零能级,以满足光流假设。然后将该算法与专家参考文献和在四个主要超声心动图视图中获得的12个序列(超过700张图像)的数据集上的另一种方法进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiview myocardial tracking in echocardiographic 2D sequences using shape and motion constrained level-set
Segmentation of the myocardium in echocardiographic images is an important task for the diagnosis of heart disease. This task is difficult due to the inherent problems of echographic images (i.e. low contrast, speckle noise, signal dropout, presence of shadows). In this article, we extend a level-set method recently proposed in [1] in order to track the whole myocardium in echocardiographic sequences. To this end, we formulate a new motion prior energy that constrains the zero-level of the implicit function to satisfy the optical flow hypothesis. The algorithm is then compared to experts references and to another method on a dataset of 12 sequences (more than 700 images) acquired in the four main echocardiographic views.
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