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Teleophthalmology in Preventive Medicine pp 93–104Cite as

Computer-Aided Diagnostics and Pattern Recognition: Automated Glaucoma Detection

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Abstract

Glaucoma is one of the major causes for blindness with a high rate of unreported cases. To reduce this number, screening programs are performed. However, these are characterized by a high workload for manual and cost-intensive assessment. Computer-aided diagnostics (CAD) to perform an automated pre-exclusion of normals might help to improve program’s efficiency.

This chapter reviews and discusses recent advances in the development of pattern recognition algorithms for automated glaucoma detection based on structural retinal image data. Two main methodologies for glaucoma detection are introduced: (i) structure-driven approaches that mainly rely on the automated extraction of specific medically relevant indicators and (ii) data-driven techniques that perform a generic machine learning approach on entire image data blobs. Both approaches show a reasonable and comparable performance although they rely on different basic assumptions. A combination of these might further improve CAD for a more efficient and cost-sensitive workflow as a major proportion of normals will be excluded from unnecessary detailed investigations.

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Acknowledgment

The authors gratefully acknowledge funding of the Erlangen Graduate School in Advanced Optical Technologies (SAOT) by the German National Science Foundation (DFG) in the framework of the excellence initiative.

Author information

Authors and Affiliations

  1. Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Bavaria, Germany

    Thomas Köhler MSc, Rüdiger Bock & Joachim Hornegger Dr.-Ing.

  2. Erlangen Graduate School in Advanced Optical Technologies (SAOT), Erlangen, Bavaria, Germany

    Thomas Köhler MSc, Rüdiger Bock & Joachim Hornegger Dr.-Ing.

  3. Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen Graduate School in Advanced Optical Technologies (SAOT), Erlangen, Bavaria, Germany

    Georg Michelson MD

  4. Department of Ophthalmology, Interdisciplinary Center of Ophthalmic Preventive Medicine and Imaging, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Bavaria, Germany

    Georg Michelson MD

Authors
  1. Thomas Köhler MSc
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  2. Rüdiger Bock
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  3. Joachim Hornegger Dr.-Ing.
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  4. Georg Michelson MD
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Corresponding author

Correspondence to Thomas Köhler MSc .

Editor information

Editors and Affiliations

  1. Department of Ophthalmology, University Erlangen-Nürnberg, Erlangen, Germany

    Georg Michelson

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Köhler, T., Bock, R., Hornegger, J., Michelson, G. (2015). Computer-Aided Diagnostics and Pattern Recognition: Automated Glaucoma Detection. In: Michelson, G. (eds) Teleophthalmology in Preventive Medicine. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44975-2_9

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  • DOI: https://doi.org/10.1007/978-3-662-44975-2_9

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  • Online ISBN: 978-3-662-44975-2

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