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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
Authors :
NameEmailORCID
Goh, JUNSPECIFIEDUNSPECIFIED
Tang, LUNSPECIFIEDUNSPECIFIED
Al Turk, LUNSPECIFIEDUNSPECIFIED
Vrikki, CUNSPECIFIEDUNSPECIFIED
Saleh, GUNSPECIFIEDUNSPECIFIED
Date : 2010
Contributors :
ContributionNameEmailORCID
http://www.loc.gov/loc.terms/relators/PBLINSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATI, UNSPECIFIEDUNSPECIFIED
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 14:58
Last Modified : 31 Oct 2017 14:12
URI: http://epubs.surrey.ac.uk/id/eprint/7630

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