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Machine Vision and Applications

, Volume 24, Issue 5, pp 919–930 | Cite as

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

  • S. G. Vázquez
  • B. Cancela
  • N. Barreira
  • M. G. Penedo
  • M. Rodríguez-Blanco
  • M. Pena Seijo
  • G. Coll de Tuero
  • M. A. Barceló
  • M. Saez
Original Paper

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.

Keywords

Retinal vessel classification Arteries Veins Minimal path Arteriovenous ratio 

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • S. G. Vázquez
    • 1
  • B. Cancela
    • 1
  • N. Barreira
    • 1
  • M. G. Penedo
    • 1
  • M. Rodríguez-Blanco
    • 2
  • M. Pena Seijo
    • 3
  • G. Coll de Tuero
    • 4
  • M. A. Barceló
    • 5
  • M. Saez
    • 5
  1. 1.Varpa Group, Department of Computer ScienceUniversity of A CoruñaA CoruñaSpain
  2. 2.Service of OphthalmologyComplejo Hospitalario UniversitarioSantiago de CompostelaSpain
  3. 3.Service of Internal MedicineHospital de ConxoSantiago de CompostelaSpain
  4. 4.Research UnitHealth Care InstituteGironaSpain
  5. 5.Research Group on Statistics, Applied Economic and Health, GRECSUniversity of GironaGironaSpain

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