Journal of Digital Imaging

, Volume 32, Issue 6, pp 947–962 | Cite as

Artery/Vein Vessel Tree Identification in Near-Infrared Reflectance Retinographies

  • Joaquim de MouraEmail author
  • Jorge Novo
  • José Rouco
  • Pablo Charlón
  • Marcos Ortega
Original Paper


An accurate identification of the retinal arteries and veins is a relevant issue in the development of automatic computer-aided diagnosis systems that facilitate the analysis of different relevant diseases that affect the vascular system as diabetes or hypertension, among others. The proposed method offers a complete analysis of the retinal vascular tree structure by its identification and posterior classification into arteries and veins using optical coherence tomography (OCT) scans. These scans include the near-infrared reflectance retinography images, the ones we used in this work, in combination with the corresponding histological sections. The method, firstly, segments the vessel tree and identifies its characteristic points. Then, Global Intensity-Based Features (GIBS) are used to measure the differences in the intensity profiles between arteries and veins. A k-means clustering classifier employs these features to evaluate the potential of artery/vein identification of the proposed method. Finally, a post-processing stage is applied to correct misclassifications using context information and maximize the performance of the classification process. The methodology was validated using an OCT image dataset retrieved from 46 different patients, where 2,392 vessel segments and 97,294 vessel points were manually labeled by an expert clinician. The method achieved satisfactory results, reaching a best accuracy of 93.35% in the identification of arteries and veins, being the first proposal that faces this issue in this image modality.


Computer-aided diagnosis Retinal image analysis Vasculature Artery/vein classification Optical coherence tomography 


Funding Information

This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the DTS18/00136 research project and by the Ministerio de Economía y Competitividad, Government of Spain through the DPI2015-69948-R research project. Also, this work has received financial support from the European Union (European Regional Development Fund—ERDF); the Xunta de Galicia, Centro singular de investigación de Galicia accreditation 2016–2019, Ref. ED431G/01; and Grupos de Referencia Competitiva, Ref. ED431C 2016-047.

Compliance with Ethical Standards

The local ethics committee approved the study and the tenets of the Declaration of Helsinki were followed.


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Copyright information

© Society for Imaging Informatics in Medicine 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of A CoruñaA CoruñaSpain
  2. 2.CITIC - Research Center of Information and Communication TechnologiesUniversity of A CoruñaA CoruñaSpain
  3. 3.Instituto Oftalmológico Victoria de RojasA CoruñaSpain

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