利用优化方法提取视网膜血管

2020 International Conference on System, Computation, Automation and Networking (ICSCAN) Pub Date : 2020-07-03 DOI:10.1109/ICSCAN49426.2020.9262284

Kalyani A, Jasmine Chalcedony C, Sri Madhava Raja N, R. Valli

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引用次数: 0

摘要

正常的视力需要健康的视网膜，但在第一阶段很难识别视网膜疾病。几种视网膜疾病影响眼睛，如视网膜撕裂、视网膜脱离、青光眼、黄斑孔、黄斑变性等。由于这些疾病大多对眼内血管有影响，分析视网膜血管的结构和特征变化有助于识别疾病及其严重程度。本文利用Tsallis熵原理和细菌觅食算法从视网膜眼底图像中提取血管。视网膜图像是由无红眼底摄影获得的。并与DRIVE数据库的真地图像进行了性能比较和分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Extraction of Retinal Vasculature using Optimization Methods

A healthy retina is required for proper vision but it is difficult to identify the retinal diseases in the first stage. Several retinal diseases affect the eye such as retinal tear, detachment of retina, glaucoma, macular hole and macular degeneration etc. Since most of these diseases have an effect on the blood vessels within the eye, analyzing the structure and variation in feature of retinal blood vessels help in identifying the disease and its severity. In this paper, we are extracting the blood vessels from retinal fundus image using Tsallis entropy principle and bacterial foraging algorithm. The retinal images are obtained from red-free fundus photography. The performance of this algorithm is compared and analyzed with ground-truth images of DRIVE database.

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2020 International Conference on System, Computation, Automation and Networking (ICSCAN)

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