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Improving retinal artery and vein classification by means of a minimal path approach

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Abstract

This paper describes a technique for the retinal vessel classification into artery and vein categories from fundus images within a framework to compute the arteriovenous ratio. This measure is used to assess the patient condition, mainly in hypertension and it is computed as the ratio between artery and vein widths. To this end, the vessels are segmented and measured in several circumferences concentric to the optic nerve. The resulting vessel segments at each radius are classified as artery or vein independently. After that, a tracking procedure joins vessel segments in different radii that belong to the same vessel. Finally, a voting system is applied to obtain the final class of the whole vessel. The methodology has been tested in a data set of 100 images labeled manually by two medical experts and a classification rate of over 87.68 % has been obtained.

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Authors and Affiliations

  1. Varpa Group, Department of Computer Science, University of A Coruña, A Coruña, Spain

    S. G. Vázquez, B. Cancela, N. Barreira & M. G. Penedo

  2. Service of Ophthalmology, Complejo Hospitalario Universitario, Santiago de Compostela, Spain

    M. Rodríguez-Blanco

  3. Service of Internal Medicine, Hospital de Conxo, Santiago de Compostela, Spain

    M. Pena Seijo

  4. Research Unit, Health Care Institute, Girona, Spain

    G. Coll de Tuero

  5. Research Group on Statistics, Applied Economic and Health, GRECS, University of Girona, Girona, Spain

    M. A. Barceló & M. Saez

Authors
  1. S. G. Vázquez
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  2. B. Cancela
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  3. N. Barreira
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  4. M. G. Penedo
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  5. M. Rodríguez-Blanco
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  6. M. Pena Seijo
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  7. G. Coll de Tuero
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  8. M. A. Barceló
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  9. M. Saez
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Correspondence to S. G. Vázquez.

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Vázquez, S.G., Cancela, B., Barreira, N. et al. Improving retinal artery and vein classification by means of a minimal path approach. Machine Vision and Applications 24, 919–930 (2013). https://doi.org/10.1007/s00138-012-0442-4

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  • DOI: https://doi.org/10.1007/s00138-012-0442-4

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