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International Conference on Innovative Techniques and Applications of Artificial Intelligence

SGAI 2010: Research and Development in Intelligent Systems XXVII pp 325–338Cite as

Retinal Image Classification for the Screening of Age-Related Macular Degeneration

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Abstract

Age-related Macular Degeneration (AMD) is the most common cause of blindness in old-age. Early identification of AMD can allow for mitigation (but not cure). One of the fist symptoms of AMD is the presence of fatty deposits, called drusen, on the retina. The presence of drusen may be identified through inspection of retina images. Given the aging global population, the prevalence of AMD is increasing. Many health authorities therefore run screening programmes. The automation, or at least partial automation, of retina image screening is therefore seen as beneficial. This paper describes a Case Based Reasoning (CBR) approach to retina image classification to provide support for AMD screening programmes. In the proposed approach images are represented in the form of spatial-histograms that store both colour and spatial image information. Each retina image is represented using a series of histograms each encapsulated as a time series curve. The Case Base (CB) is populated with a labelled set of such curves. New cases are classified by finding the most similar case (curve) in the CB. Similarity checking is achieved using the Dynamic Time warping (DTW).

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Author information

Authors and Affiliations

  1. Department of Computer Science, The University of Liverpool, Liverpool, UK

    Mohd Hanafi Ahmad Hijazi & Frans Coenen

  2. Ophthalmology Research Unit, School of Clinical Sciences, The University of Liverpool, Liverpool, UK

    Yalin Zheng

Authors
  1. Mohd Hanafi Ahmad Hijazi
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  2. Frans Coenen
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  3. Yalin Zheng
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Corresponding authors

Correspondence to Mohd Hanafi Ahmad Hijazi , Frans Coenen or Yalin Zheng .

Editor information

Editors and Affiliations

  1. Dept. Computer Science and, Software Engineering, University of Portsmouth, Buckingham Building, Lion Terrace, Portsmouth, PO1 3HE, United Kingdom

    Max Bramer

  2. School of Computing &, Mathematical Sciences, University of Greenwich, Park Row 30, London, SE10 9LS, United Kingdom

    Miltos Petridis

  3. , Faculty of Technology, De Montford University, The Gateway, Leicester, LE1 9BH, United Kingdom

    Adrian Hopgood

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© 2011 Springer-Verlag London Limited

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Hijazi, M.H.A., Coenen, F., Zheng, Y. (2011). Retinal Image Classification for the Screening of Age-Related Macular Degeneration. In: Bramer, M., Petridis, M., Hopgood, A. (eds) Research and Development in Intelligent Systems XXVII. SGAI 2010. Springer, London. https://doi.org/10.1007/978-0-85729-130-1_25

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  • DOI: https://doi.org/10.1007/978-0-85729-130-1_25

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  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-129-5

  • Online ISBN: 978-0-85729-130-1

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