Medical & Biological Engineering & Computing

, Volume 55, Issue 12, pp 2209–2225 | Cite as

Enhanced visualization of the retinal vasculature using depth information in OCT

  • Joaquim de MouraEmail author
  • Jorge Novo
  • Pablo Charlón
  • Noelia Barreira
  • Marcos Ortega
Original Article


Retinal vessel tree extraction is a crucial step for analyzing the microcirculation, a frequently needed process in the study of relevant diseases. To date, this has normally been done by using 2D image capture paradigms, offering a restricted visualization of the real layout of the retinal vasculature. In this work, we propose a new approach that automatically segments and reconstructs the 3D retinal vessel tree by combining near-infrared reflectance retinography information with Optical Coherence Tomography (OCT) sections. Our proposal identifies the vessels, estimates their calibers, and obtains the depth at all the positions of the entire vessel tree, thereby enabling the reconstruction of the 3D layout of the complete arteriovenous tree for subsequent analysis. The method was tested using 991 OCT images combined with their corresponding near-infrared reflectance retinography. The different stages of the methodology were validated using the opinion of an expert as a reference. The tests offered accurate results, showing coherent reconstructions of the 3D vasculature that can be analyzed in the diagnosis of relevant diseases affecting the retinal microcirculation, such as hypertension or diabetes, among others.


Computer-aided diagnosis Vascular structure Retinal imaging Optical Coherence Tomography 



This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the PI14/02161 and the DTS15/00153 research projects 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) and 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.

Supplementary material

(MP4 44.5 MB)


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Copyright information

© International Federation for Medical and Biological Engineering 2017

Authors and Affiliations

  • Joaquim de Moura
    • 1
    Email author
  • Jorge Novo
    • 1
  • Pablo Charlón
    • 2
  • Noelia Barreira
    • 1
  • Marcos Ortega
    • 1
  1. 1.Department of Computer ScienceUniversity of A CoruñaA CoruñaSpain
  2. 2.Instituto Oftalmológico Victoria de RojasA CoruñaSpain

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