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A Parallel Swarm Library Based on Functional Programming Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Automatic Tool for Optic Disc and Cup Detection on Retinal Fundus Images

Authors : Miguel Angel Fernandez-Granero, Auxiliadora Sarmiento Vega, Anabel Isabel García, Daniel Sanchez-Morillo, Soledad Jiménez, Pedro Alemany, Irene Fondón

Published in: Advances in Computational Intelligence

Publisher: Springer International Publishing

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Abstract

The aging of the population is a matter of concern due to its association with various diseases in humans that limit their quality of life. Among them, glaucoma is one of the leading causes of blindness in the world. To its early diagnose, retinal fundus images are visually inspected by experts. In recent years, image-based computer aided diagnosis systems have been proposed. Automatic segmentation of Optic Disc (OD) and cup areas are their first and most difficult tasks. In this paper, a computerized technique aimed to their extraction from the original images is presented. The tool is related to human perception due to the use of an advanced color metric, CIE94 within a uniform color space, CIE L*a*b* to compute pixels’ color gradients [1]. Based on this information, a classifier assigns a probability value to each of the pixels, meaning its suitability for being part of the Optic Disc and Cup border. The tool has been tested on 200 images from different public databases achieving an accuracy value of 96.63%. This quality level makes the proposed color-based image processing system capable to assist the physicians in glaucoma screening programs.

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Metadata
Title
Automatic Tool for Optic Disc and Cup Detection on Retinal Fundus Images
Authors
Miguel Angel Fernandez-Granero
Auxiliadora Sarmiento Vega
Anabel Isabel García
Daniel Sanchez-Morillo
Soledad Jiménez
Pedro Alemany
Irene Fondón
Copyright Year
2017
Book
Advances in Computational Intelligence

Print ISBN: 978-3-319-59152-0

Electronic ISBN: 978-3-319-59153-7

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-59153-7_22

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