Robust Atlas-Based Segmentation of Highly Variable Anatomy: Left Atrium Segmentation.

Michal Depa, Mert R Sabuncu, Godtfred Holmvang, Reza Nezafat, Ehud J Schmidt, Polina Golland
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引用次数: 50

Abstract

Automatic segmentation of the heart's left atrium offers great benefits for planning and outcome evaluation of atrial ablation procedures. However, the high anatomical variability of the left atrium presents significant challenges for atlas-guided segmentation. In this paper, we demonstrate an automatic method for left atrium segmentation using weighted voting label fusion and a variant of the demons registration algorithm adapted to handle images with different intensity distributions. We achieve accurate automatic segmentation that is robust to the high anatomical variations in the shape of the left atrium in a clinical dataset of MRA images.

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高度可变解剖结构的稳健阿特拉斯分割:左心房分割。
心脏左心房的自动分割为心房消融手术的规划和结果评估提供了很大的好处。然而,左心房的高度解剖变异性对atlas引导的分割提出了重大挑战。在本文中,我们展示了一种使用加权投票标签融合的自动左心房分割方法和一种适合处理不同强度分布图像的恶魔配准算法的变体。我们在MRA图像的临床数据集中实现了准确的自动分割,该分割对左心房形状的高度解剖变化具有鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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