利用快速模糊C均值聚类方法检测视网膜眼底图像中的青光眼

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI:10.1109/ICCCIS48478.2019.8974539

Law Kumar Singh, Pooja, H. Garg

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引用次数: 7

摘要

青光眼是当今世界视力丧失的主要原因之一。青光眼是一种眼液压力升高的疾病;如果不及时治疗，患者可能会失去视力。青光眼可以通过检查眼底图像中光学杯和光学盘的边界来诊断。该方法通过对眼底图像的处理，自动检测光学杯和光学盘的边界。本文探讨了快速模糊c均值分割眼底图像视盘和视杯的新方法。快速模糊C均值法比模糊C均值法评价结果的速度更快。在DRIONS、DRIVE和STARE等公开的视网膜眼底图像数据库上进行测试时，该方法的报出率分别为97.75%、92.50%和95.00%。

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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Detection of Glaucoma in Retinal Fundus Images Using Fast Fuzzy C means clustering approach

Glaucoma is one of the major causes of vision loss in today’s world. Glaucoma is the disease where fluid pressure in the eye increases; if it is not timely cured, the patient may lose their vision. Glaucoma can be detected by examining boundary of optics cup and optics disc acquired from retinal fundus images. The proposed method suggests automatic detection the boundary of optics cup and optics disc with processing of fundus images. This paper explores the new approach of fast fuzzy C-mean technique for segmenting the optic disc and optic cup in fundus images. Results evaluated by fast fuzzy C mean a technique is faster than fuzzy C-mean method. The proposed method reported results to 97.75% 92.50% and 95.00% when tested on DRIONS, DRIVE and STARE on publicly available databases of retinal fundus images.

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2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)

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