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Optic disc detection in color fundus images using ant colony optimization

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Abstract

Diabetic retinopathy has been revealed as the most common cause of blindness among people of working age in developed countries. However, loss of vision could be prevented by an early detection of the disease and, therefore, by a regular screening program to detect retinopathy. Due to its characteristics, the digital color fundus photographs have been the easiest way to analyze the eye fundus. An important prerequisite for automation is the segmentation of the main anatomical features in the image, particularly the optic disc. Currently, there are many works reported in the literature with the purpose of detecting and segmenting this anatomical structure. Though, none of them performs as needed, especially when dealing with images presenting pathologies and a great variability. Ant colony optimization (ACO) is an optimization algorithm inspired by the foraging behavior of some ant species that has been applied in image processing with different purposes. In this paper, this algorithm preceded by anisotropic diffusion is used for optic disc detection in color fundus images. Experimental results demonstrate the good performance of the proposed approach as the optic disc was detected in most of all the images used, even in the images with great variability.

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Acknowledgments

C. P. thanks the Fundação para a Ciência e Tecnologia (FCT), Portugal for the Ph.D. Grant SFRH/BD/61829/2009. The authors also would like to thank to the reviewers for their valuable comments for this article improvement.

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Authors and Affiliations

  1. Industrial Electronics, University of Minho, Guimarães, Portugal

    Carla Pereira & Manuel Ferreira

  2. Ophthalmology Service, Centro Hospitalar do Alto Ave, Guimarães, Portugal

    Luís Gonçalves

Authors
  1. Carla Pereira
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  2. Luís Gonçalves
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  3. Manuel Ferreira
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Correspondence to Carla Pereira.

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Pereira, C., Gonçalves, L. & Ferreira, M. Optic disc detection in color fundus images using ant colony optimization. Med Biol Eng Comput 51, 295–303 (2013). https://doi.org/10.1007/s11517-012-0994-5

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  • DOI: https://doi.org/10.1007/s11517-012-0994-5

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