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Optic disc detection in color fundus images using ant colony optimization.

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 characteri...

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Published in:Medical & Biological Engineering & Computing Vol. 51; no. 3; pp. 295 - 304
Main Authors: Pereira, Carla, Gonçalves, Luís, Ferreira, Manuel
Format: research Journal Article
Published: Springer Nature Mar2013
Online Access:View this record in EBSCOhost
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      jtl: Medical & Biological Engineering & Computing
      issn: 01400118
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      dt: Mar2013
      vid: 51
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-012-0994-5
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        atl: Optic disc detection in color fundus images using ant colony optimization.
      aug:
        au:
          Pereira, Carla
          Gonçalves, Luís
          Ferreira, Manuel
        affil: Industrial Electronics, University of Minho, Guimaraes, Portugal, id2723@alunos.uminho.pt.
      sug:
        subj:
          Algorithms
          Diagnosis, Eye
          Image Processing, Computer Assisted Methods
          Optic Nerve
          Resource Databases
          Diabetic Retinopathy Pathology
          Diffusion
          Models, Biological
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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