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Computational and Mathematical Methods in Medicine - Volume 2016 2016, Article ID 3695014, 9 pages -

Research Article

VARPA Group, Department of Computer Science, University of A Coruna, A Coruna, Spain

Artificial Vision Group, Department of Electronics and Computer Science, University of Santiago de Compostela, Santiago de Compostela, Spain

School of Optometry and Vision Sciences, Cardiff University, Wales, UK

Optometry Group, Department of Applied Physics, University of Santiago de Compostela, Santiago de Compostela, Spain

Received 22 September 2016; Accepted 1 November 2016

Academic Editor: Ezequiel López-Rubio

Copyright © 2016 María Luisa Sánchez Brea et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Conjunctival hyperemia or conjunctival redness is a symptom that can be associated with a broad group of ocular diseases. Its levels of severity are represented by standard photographic charts that are visually compared with the patient’s eye. This way, the hyperemia diagnosis becomes a nonrepeatable task that depends on the experience of the grader. To solve this problem, we have proposed a computer-aided methodology that comprises three main stages: the segmentation of the conjunctiva, the extraction of features in this region based on colour and the presence of blood vessels, and, finally, the transformation of these features into grading scale values by means of regression techniques. However, the conjunctival segmentation can be slightly inaccurate mainly due to illumination issues. In this work, we analyse the relevance of different features with respect to their location within the conjunctiva in order to delimit a reliable region of interest for the grading. The results show that the automatic procedure behaves like an expert using only a limited region of interest within the conjunctiva.





Autor: María Luisa Sánchez Brea, Noelia Barreira Rodríguez, Antonio Mosquera González, Katharine Evans, and Hugo Pena-Verdeal

Fuente: https://www.hindawi.com/



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