Coronary artery segmentation in X-Ray Angiographic image by means of a shape based level set method

J. Brieva
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引用次数: 3

Abstract

This paper presents a level set technique to extract vascular structures in X-Ray Angiographic images. It makes uses of the Chan and Vese model applied to images of non-uniform illumination and uses a shape-based model to perform the segmentation. The shape model is computed using string matching techniques. Its performance, using different metrics, has been evaluated on a image sequence of 64 angiographic images by comparison with expert delineation. A sensitivity of 81% and a specificity of 94% were found in the quantitative validation analysis.
基于形状的水平集分割x射线血管造影图像中的冠状动脉
本文提出了一种水平集技术提取x射线血管造影图像中的血管结构。它将Chan和Vese模型应用于非均匀光照图像,并使用基于形状的模型进行分割。使用字符串匹配技术计算形状模型。它的性能,使用不同的指标,已经评估了图像序列的64个血管造影图像通过与专家划定的比较。定量验证分析的灵敏度为81%,特异性为94%。
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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