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Automatic Detection of Diabetic Retinopathy- A Technological Breakthrough

Published on August 2015 by Chinar, Deepti Malhotra, and Alpana Agarwal
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International Conference on Advancements in Engineering and Technology
Foundation of Computer Science USA
ICAET2015 - Number 6
August 2015
Authors: Chinar, Deepti Malhotra, and Alpana Agarwal
b869e0f1-4b65-436c-87ed-21e1d9cc9f7b

Chinar, Deepti Malhotra, and Alpana Agarwal . Automatic Detection of Diabetic Retinopathy- A Technological Breakthrough. International Conference on Advancements in Engineering and Technology. ICAET2015, 6 (August 2015), 22-25.

@article{
author = { Chinar, Deepti Malhotra, and Alpana Agarwal },
title = { Automatic Detection of Diabetic Retinopathy- A Technological Breakthrough },
journal = { International Conference on Advancements in Engineering and Technology },
issue_date = { August 2015 },
volume = { ICAET2015 },
number = { 6 },
month = { August },
year = { 2015 },
issn = 0975-8887,
pages = { 22-25 },
numpages = 4,
url = { /proceedings/icaet2015/number6/22246-4081/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advancements in Engineering and Technology
%A Chinar
%A Deepti Malhotra
%A and Alpana Agarwal
%T Automatic Detection of Diabetic Retinopathy- A Technological Breakthrough
%J International Conference on Advancements in Engineering and Technology
%@ 0975-8887
%V ICAET2015
%N 6
%P 22-25
%D 2015
%I International Journal of Computer Applications
Abstract

Diabetic Retinopathy is a dangerous eye disease and the most common cause of blindness for worldwide population. Digital color fundus images are becoming very important as they help in diagnosing Diabetic Retinopathy. With this fact new image processing techniques can be applied to improve automatic detection of diabetic retinopathy. Segmentation, feature extraction, enhancement, image classification, pattern matching are the major image processing elements in detecting eye diseases . Microaneurysms are the primary sign of DR, therefore necessary preprocessing step for a correct diagnosis to automatically detect the microaneurysms in fundus image is an algorithm. For detecting the microaneurysms in retina images this review paper aims to develop and test a new method.

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Keywords

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