A review of fundus image analysis for the automated detection of diabetic retinopathy

Kevin Noronha, K. Prabhakar Nayak

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Diabetic related eye diseases like Diabetic retinopathy (DR), Diabetic maculopathy (DM) and Glaucoma are a major cause of blindness worldwide. The early detection of these diseases plays a very significant role in the prevention of vision loss. In the last few years medical image processing of the retinal digital fundus images has emerged as a very important research area to aid an ophthalmologist in clinical diagnosis. The detection of retinal landmarks of fundus image like the Optic disk (OD), fovea and the retinal vessels is very significant in the automated detection of Diabetic retinopathy (DR), Diabetic maculopathy (DM) and Glaucoma. This review outlines the principles, methods and algorithms used in the automated detection of diabetic retinopathy. The recent methods used to detect the retinal landmarks and pathologies like hemorrhages, micro aneurysms (HMA), cotton wool spots and retinal exudates are discussed. We present the quantitative evaluation of various methods used for the automated detection of DR. The methodologies used by the researches in analyzing their results were also discussed.

Original languageEnglish
Pages (from-to)258-265
Number of pages8
JournalJournal of Medical Imaging and Health Informatics
Volume2
Issue number3
DOIs
Publication statusPublished - 09-2012

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Diabetic Retinopathy
Glaucoma
Retinal Vessels
Eye Diseases
Wool
Optic Disk
Exudates and Transudates
Blindness
Research
Aneurysm
Early Diagnosis
Pathology
Hemorrhage

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Health Informatics

Cite this

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A review of fundus image analysis for the automated detection of diabetic retinopathy. / Noronha, Kevin; Nayak, K. Prabhakar.

In: Journal of Medical Imaging and Health Informatics, Vol. 2, No. 3, 09.2012, p. 258-265.

Research output: Contribution to journalArticle

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