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Hessian-based vessel enhancement combined with directional filter banks and vessel similarity

机译:基于Hessian的船舶增强结合定向滤波器组和血管相似度

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摘要

Vessel enhancement in angiogram is an important preprocessing procedure for clinical diagnosis and further processing. Hessian-based methods have been widely used due to its elegant geometrical interpretations. But classical Hessian-based methods suffer the drawbacks of blurred vessel edges and intensity inhomogeneity, especially in vessel junction regions. In this paper, a new vessel enhancement method is proposed to address these problems. The input angiogram is first decomposed into several directional images and each of them is enhanced by traditional Hessian-based method. Then the enhanced direction images are recombined to generate final result. To improve contrast at vessel edges and intensity homogeneity in vessels, a vessel similarity measurement is proposed and used as weight coefficients in the recombination of enhanced directional images. It is calculated based on the intensity and curvature analysis of directional images. Qualitative and quantitative experiments performed on typical angiograms and retinal images in DRIVE database show that the proposed method has better performance than other two Hessian-based enhancement methods.
机译:血管造影中的血管增强是临床诊断和进一步加工的重要预处理程序。由于其优雅的几何解释,基于Hessian的方法已被广泛使用。但基于古典的Hessian的方法遭受模糊的血管边缘和强度不均匀性的缺点,特别是在血管连接区域。在本文中,提出了一种新的血管增强方法来解决这些问题。输入血管造影图首先将其分解成几个方向图像,并且通过传统的基于Hessian的方法增强了它们中的每一个。然后,增强的方向图像被重新组合以产生最终结果。为了在容器中提高血管边缘和强度均匀性的对比度,提出了血管相似度测量并用作增强定向图像的重组中的重量系数。它基于定向图像的强度和曲率分析来计算。在驱动数据库中对典型血管造影和视网膜图像进行的定性和定量实验表明,所提出的方法具有比其他两个基于Hessian的增强方法的性能更好。

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