Algorithms for the automated detection of diabetic retinopathy using digital fundus images: a review.

Abstract:

:Diabetes is a chronic end organ disease that occurs when the pancreas does not secrete enough insulin or the body is unable to process it properly. Over time, diabetes affects the circulatory system, including that of the retina. Diabetic retinopathy is a medical condition where the retina is damaged because fluid leaks from blood vessels into the retina. Ophthalmologists recognize diabetic retinopathy based on features, such as blood vessel area, exudes, hemorrhages, microaneurysms and texture. In this paper we review algorithms used for the extraction of these features from digital fundus images. Furthermore, we discuss systems that use these features to classify individual fundus images. The classifications efficiency of different DR systems is discussed. Most of the reported systems are highly optimized with respect to the analyzed fundus images, therefore a generalization of individual results is difficult. However, this review shows that the classification results improved has improved recently, and it is getting closer to the classification capabilities of human ophthalmologists.

journal_name

J Med Syst

authors

Faust O,Acharya U R,Ng EY,Ng KH,Suri JS

doi

10.1007/s10916-010-9454-7

subject

Has Abstract

pub_date

2012-02-01 00:00:00

pages

145-57

issue

1

eissn

0148-5598

issn

1573-689X

journal_volume

36

pub_type

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