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Post-processing for retinal vessel detection

机译:视网膜血管检测的后处理

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Retinal vessel extraction plays a vital role in the computer-aided analysis of ophthalmology diseases. In this paper, we propose a new post-processing method to enhance retinal vessel classification performance. This proposed method automatically connects the discontinuous thin vessel fragments and smooth the thick vessel edges by the combination of two mathematical morphological operations, skeleton and erosion. Moreover, the proposed method removes the pathological regions by comparing the geometric structures of vessels and pathological regions. Experimental results demonstrate that the proposed method performs well for retinal vessel classification enhancement, i.e. maintain the integrity of vessel trees and reduce the false detection of pathological regions, making the vessel classification results better than those presented by the state-of-the-art approaches in comparison.
机译:视网膜血管提取在眼科疾病的计算机辅助分析中起着至关重要的作用。在本文中,我们提出了一种新的后处理方法,以增强视网膜血管分类性能。该方法通过将两个数学形态学运算(骨架和侵蚀)结合起来,自动连接不连续的细血管碎片并平滑厚血管边缘。此外,所提出的方法通过比较血管和病理区域的几何结构来去除病理区域。实验结果表明,所提出的方法在增强视网膜血管分类方面表现良好,即保持血管树的完整性并减少对病理区域的错误检测,从而使血管分类结果优于最新方法相比下。

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