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首页> 外文会议>International Conference on BioMedical Engineering and Informatics >Accurate vessel segmentation with optimal combination of features
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Accurate vessel segmentation with optimal combination of features

机译：具有最佳特性组合的精确血管分割

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We describe a novel appearance model with optimal combined features to produce the accurate vessel segmentation. It starts with investigating a set of multi-scale vessel features, followed by a weighed approach to optimally combine different features. Then the optimally combined features advantage the appearance model to reveal more detailed information of vessel. The novelty of the work lies in the integration of optimal combined multi-scale features in the appearance model. The main advantage of our framework is that it detects vessel boundary in problematic regions that contain small vessels and noise. It is particularly suitable for accurate segmentation of thin and low contrast vessels. Two state-of-the-art vessel segmentation methods were used to compare with our method. Quantitative results on synthetic data indicate that our method is more accurate than these methods. Furthermore, our method performs good in clinical experiments, it is capable of detecting more detailed information of vessel. Compare with two state-of-the-art methods, our method is more accurate and robust, and more suited for automatic vessel extraction.
机译：我们描述了一种新颖的外观模型，具有最佳的组合特征来生产精确的血管分割。它从调查一组多尺度血管功能开始，然后是最佳地结合不同的特征的称重方法。然后，最佳组合的特征优势外观模型揭示了容器的更详细信息。该工作的新颖性在于在外观模型中集成了最佳组合的多尺度特征。我们框架的主要优点是它检测含有小血管和噪音的有问题区域的血管边界。它特别适用于精确的薄和低对比度容器的细分。使用两种最先进的船舶分割方法与我们的方法进行比较。合成数据的定量结果表明我们的方法比这些方法更准确。此外，我们的方法在临床实验中表现良好，它能够检测容器的更详细信息。与两种最先进的方法相比，我们的方法更准确，更坚固，更适合自动血管提取。

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