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International Conference Image Analysis and Recognition

ICIAR 2014: Image Analysis and Recognition pp 285–292Cite as

Automatic Optic Disc Detection in Retinal Fundus Images Based on Geometric Features

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8815))

Abstract

Regular eye examinations are the key to limiting the vision loss caused by glaucoma and diabetic retinopathy. Optic disc (OD) detection is of vital importance in developing automated diagnosis systems for these diseases. In this work we present a method for automatic localization and boundary detection of the optic disc in retinal fundus images. In the first step, we rely on the OD geometric feature and utilize gaussian and mean curvatures for the localization of the OD. In the second step, we extract a region of interest based on the OD localization. Then, to the edges of this extracted region a circular Hough transform is applied to segment the OD boundary. The experimental results on three public datasets show the efficacy of the proposed method.

This work was partially supported by the project PTDC/MATNAN/0593/2012, and also by CMUC and FCT (Portugal), through European program COMPETE/FEDER and project PEst-C/MAT/UI0324/2011.

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Authors and Affiliations

  1. CMUC, Department of Mathematics, University of Coimbra, Coimbra, Portugal

    Isabel N. Figueiredo & Sunil Kumar

Authors
  1. Isabel N. Figueiredo
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  2. Sunil Kumar
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Corresponding author

Correspondence to Sunil Kumar .

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Editors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Aurélio Campilho

  2. Dept. of Electrical and Computer Eng., University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

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Figueiredo, I.N., Kumar, S. (2014). Automatic Optic Disc Detection in Retinal Fundus Images Based on Geometric Features. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8815. Springer, Cham. https://doi.org/10.1007/978-3-319-11755-3_32

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  • DOI: https://doi.org/10.1007/978-3-319-11755-3_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11754-6

  • Online ISBN: 978-3-319-11755-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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