Optimized clinical segmentation of retinal blood vessels by using combination of adaptive filtering, fuzzy entropy and skeletonization

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• 作者：Khosro Rezaee^a ; ^b ; Javad Haddadnia^a ; ^b ; ^{Haddadnia@hsu.ac.ir} ; Ashkan Tashk^c (Graduate Student Member)
• 关键词：Retinas vessels ; Image processing ; Wiener filter ; Adaptive filter ; Fuzzy entropy and skeleton method
• 刊名：Applied Soft Computing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：52
• 期：Complete
• 页码：937-951
• 全文大小：4134 K
• 卷排序：52

文摘

Occasionally certain areas in the retina can be questionable for physicians which can lead to wrong interpretations for patients. A method is proposed that introduces a higher ability of segmentation by employing Skeletonization and a threshold selection based on Fuzzy Entropy. By extracting indices of the human retina properly, physicians will be able to estimate pathological injuries with a higher confidence. The proposed approach is fast and outperforms over other previously competitive techniques. The proposed approach consists of two stages. First of all, the retinal vessels was preprocessed by the HSV space and Wiener Filter. Then, the segmentation level is implemented by using Adaptive Filter that employs optimum threshold based on Fuzzy Entropy and Skeleton algorithm.