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Evolving the structure of hidden Markov models for micro aneurysms detection

Goh, J, Tang, L and Al Turk, L (2010) Evolving the structure of hidden Markov models for micro aneurysms detection Proceedings of UK Workshop on Computational Intelligence. 1 - 6.

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Abstract

Micro aneurysms are one of the first visible clinical signs of diabetic retinopathy and their detection can help diagnose the progression of the disease. In this paper, a novel technique based on Genetic Algorithms is used to evolve the structure of the Hidden Markov Models to obtain an optimised model that indicates the presence of micro aneurysms located in a sub-region. This technique not only identifies the optimal number of states, but also determines the topology of the Hidden Markov Model, along with the initial model parameters.

Item Type: Article
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Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Divisions: Faculty of Engineering and Physical Sciences > Computing Science
Depositing User: Symplectic Elements
Date Deposited: 08 Feb 2012 09:30
Last Modified: 23 Sep 2013 18:49
URI: http://epubs.surrey.ac.uk/id/eprint/7631

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