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

Omar, Mohamed, Hossain, Alamgir, Zhang, Li and Shum, Hubert P. H. (2014) An intelligent mobile-based automatic diagnostic system to identify retinal diseases using mathematical morphological operations. In: 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 18-20 December 2014, Dhaka.

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Official URL: http://dx.doi.org/10.1109/SKIMA.2014.7083563

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.

Item Type: Conference or Workshop Item (Speech)
Subjects: G400 Computer Science
G700 Artificial Intelligence
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Ay Okpokam
Date Deposited: 13 May 2015 11:04
Last Modified: 09 May 2017 16:09
URI: http://nrl.northumbria.ac.uk/id/eprint/22467

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