A survey on segmentation of exudates and microaneurysms for early detection of diabetic retinopathy

被引：9
|
作者：
Devaraj, Deepashree [1 ]
Suma, R. [1 ]
Kumar, S. C. Prasanna [1 ]
机构：
[1] RV Coll Engn, Dept Elect & Instrumentat Engn, Mysuru Rd, Bengaluru 560059, India
来源：
MATERIALS TODAY-PROCEEDINGS | 2018年 / 5卷 / 04期
关键词：
Diabetic retinopathy; Exudates; Microaneurysms; Fuzzy C Means clustering; Support vector machine; Naive Bayes classifier; CLASSIFICATION;
D O I：
10.1016/j.matpr.2017.12.372
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Early detection of the retinal diseases like diabetic retinopathy is fundamental to the avoidance of visual misfortune. An automated Diabetic Retinopathy screening will enable the detection of lesions accurately, thus helping the ophthalmologists. The analysis of retinal abnormalities, for example, exudates, microaneurysms and haemorrhages are essential to detect Non-Proliferative Diabetic Retinopathy and Proliferative Diabetic Retinopathy. The survey includes various methodologies for segmentation of exudates and microaneurysms from retinal fundus images using different image processing techniques. By doing so, the permanent vision loss can be prevented. (c) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码：10845 / 10850
页数：6
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