Detection of micro aneurysms using multiple classifiers and hidden Markov models

Goh, J, Tang, L, Al Turk, L, Vrikki, C and Saleh, G (2010) Detection of micro aneurysms using multiple classifiers and hidden Markov models Proceedings of the Third International Conference on Health Informatics. pp. 269-274.

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Abstract

Diabetic retinopathy is a complication of diabetes and early detection is essential for effective treatment. In this paper, a novel technique for the detection of micro aneurysms is presented. Various features are extracted using image processing techniques and then fed through multiple classifiers for initial classification of candidate micro aneurysms. Hidden Markov models are then used to perform contextual analysis to recognise true micro aneurysms.

Item Type:	Article
Divisions :	Surrey research (other units)
Authors :	Goh, J, Tang, L, Al Turk, L, Vrikki, C and Saleh, G
Date :	2010
Contributors :	Contribution Name Email ORCID http://www.loc.gov/loc.terms/relators/PBL INSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATI,
Depositing User :	Symplectic Elements
Date Deposited :	28 Mar 2017 14:58
Last Modified :	24 Jan 2020 11:17
URI:	http://epubs.surrey.ac.uk/id/eprint/7630

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