基于两阶段阈值和形态学图像恢复的Hessian血管分割改进

S. Mirhassani, M. Hosseini, A. Behrad
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引用次数: 7

摘要

在许多血管分割方法中,采用基于Hessian的血管增强滤波器作为有效的分割步骤。在本文中,对于血管的分割,HBVF方法是算法的第一步。然后,对滤波后的图像应用高电平阈值去除图像中的非血管。由于阈值的存在,一些弱血管被去除,利用霍夫变换和形态学运算实现血管的恢复。然后,将生成的图像与使用低电平阈值将其转换为二值图像的容器滤波图像相结合。通过图像组合,检测出了大部分的血管。在最后一步,为了减少误报,根据细颗粒的大小从结果中去除。实验结果表明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improvement of Hessian based vessel segmentation using two stage threshold and morphological image recovering
In many of vessel segmentation methods, Hessian based vessel enhancement filter as an efficient step is employed. In this paper, for segmentation of vessels, HBVF method is the first step of the algorithm. Afterward, to remove non-vessels from image, a high level threshold is applied to the filtered image. Since, as a result of threshold some of weak vessels are removed, recovering of vessels using Hough transform and morphological operations is accomplished. Then, the yielded image is combined with a version of vesselness filtered image which is converted to a binary image using a low level threshold. As a consequence of image combination, most of vessels are detected. In the final step, to reduce the false positives, fine particles are removed from the result according to their size. Experiments indicate the promising results which demonstrate the efficiency of the proposed algorithm.
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