An intelligent mobile-based automatic diagnostic system to identify retinal diseases using mathematical morphological operations

Mohamed Omar, Alamgir Hossain, Li Zhang, Hubert P. H. Shum

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)

Abstract

Diabetic retinopathy is considered in terms of the presence of exudates which cause vision loss in the areas affected. This study targets the development of an intelligent mobile-based automatic diagnosis integrated with a microscopic lens to identify retinal diseases at initial stage at any time or place. Exudate detection is a significant step in order obtaining an early diagnosis of diabetic retinopathy, and if they are segmented accurately, laser treatment can be applied effectively. Consequently, precise segmentation is the fundamental step in exudate extraction. This paper proposes a technique for exudate segmentation in colour retinal images using morphological operations. In this method, after pre-processing, the optic disc and blood vessels are isolated from the retinal image. Exudates are then segmented by a combination of morphological operations such as the modified regionprops function and a reconstruction technique. The proposed technique is verified against the DIARETDB1 database and achieves 85.39% sensitivity. The proposed technique achieves better exudate detection results in terms of sensitivity than other recent methods reported in the literature. In future work, our system will be deployed to a mobile platform to allow efficient and instant diagnosis.
Original languageEnglish
Title of host publicationThe 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014)
PublisherIEEE
Number of pages5
ISBN (Electronic)9781479963997
DOIs
Publication statusPublished - Dec 2014
Event8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) - Dhaka
Duration: 1 Dec 2014 → …

Publication series

NameSKIMA Proceedings
PublisherIEEE
Volume2014
ISSN (Print)2373-082X

Conference

Conference8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
Period1/12/14 → …

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