Segmenting the papillary muscles and the trabeculae from high resolution cardiac CT through restoration of topological handles.
Segmenting the papillary muscles and the trabeculae from high resolution cardiac CT through restoration of topological handles.
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DOI：
10.1007/978-3-642-38868-2_16
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发表时间：
2013-01-01
期刊：
影响因子：
--
通讯作者：
Axel, Leon
中科院分区：
文献类型：
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作者：
Gao, Mingchen;Chen, Chao;Axel, Leon
我们介绍了一种新的算法分割的高分辨率CT图像的左心室（LV），特别是乳头肌和小梁。这些结构的高质量分割是必要的，以便更好地理解LV的解剖功能和几何特性。然而，由于这些精细结构在几何形状和拓扑结构上的微妙和复杂性质，捕获这些精细结构极具挑战性。我们的算法计算一个给定的初始分割的潜在丢失的拓扑结构。使用计算拓扑学的技术，例如持久同源性，我们的算法找到可能是真实信号的拓扑句柄。为了进一步提高准确性，这些建议是通过训练分类器的显着性和置信度来衡量的。在最后的分割中恢复具有高分数的手柄，导致复杂结构的高质量分割结果。
We introduce a novel algorithm for segmenting the high resolution CT images of the left ventricle (LV), particularly the papillary muscles and the trabeculae. High quality segmentations of these structures are necessary in order to better understand the anatomical function and geometrical properties of LV. These fine structures, however, are extremely challenging to capture due to their delicate and complex nature in both geometry and topology. Our algorithm computes the potential missing topological structures of a given initial segmentation. Using techniques from computational topology, e.g. persistent homology, our algorithm find topological handles which are likely to be the true signal. To further increase accuracy, these proposals are measured by the saliency and confidence from a trained classifier. Handles with high scores are restored in the final segmentation, leading to high quality segmentation results of the complex structures.