Max-min central vein detection in retinal fundus images

Hind Azegrouz, Emanuele Trucco

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)


This paper describes a new framework for the automated tracking of the central retinal vein in retinal images. The procedure first computes a binary image of the retinal vasculature, then obtains the skeleton (medial axis) of the vascular network. Terminal and branching points of the network are then located, and the network converted into a graph representation including length and thickness information for all vessels. Finally, a MaxMin approach is used to locate the central vein:The candidates central vein are the minimal paths from the optic disk to all terminal nodes found using Dijkstra algorithm. The actual central vein is selected among the all candidates by maximizing a merit function estimating the total vessel area in the image. Results are presented and compared with those provided by a manual classification on 20 images of the DRIVE set. An overall performance ratio of 92% is achieved. ©2006 IEEE.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
Number of pages4
Publication statusPublished - 2006
Event13th IEEE International Conference on Image Processing 2006 - Atlanta, GA, United States
Duration: 8 Oct 200611 Oct 2006


Conference13th IEEE International Conference on Image Processing 2006
Abbreviated titleICIP 2006
Country/TerritoryUnited States
CityAtlanta, GA


  • Central
  • Graph
  • Retinal
  • Vein
  • Vessel


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