A semi-supervised puzzle-based method for separating the venous and arterial vascular networks in retinal images

Edgardo M. Felipe-Riveron, Fabiola M. Villalobos Castaldi, Ernesto Suaste Gómez, Marcos A. Leiva Vasconcellos, Cecilia Albortante Morato

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The focus of this work is to create a methodology to separate the entire vascular network into its independent veins and arteries networks in optical human fundus images. It has been developed following the logical procedure used by humans when they assemble a puzzle. In the development of the methodology we take into consideration physiological properties, topological properties of the tree structure and morphological properties of both networks, that is, they have only bifurcations, crosses and ending points, and also that crosses are produced always between venous and arterial branches. For arterial blood vessels we get a classification capability, based on the pixel counting, of 84.88% while for venous was 82.87%. This indicates that the methodology classified correctly as average 83.80% of the total blood vessels in the images.

Original languageEnglish
Title of host publicationPattern Recognition - 6th Mexican Conference, MCPR 2014, Proceedings
PublisherSpringer Verlag
Pages251-260
Number of pages10
ISBN (Print)9783319074900
DOIs
StatePublished - 2014
Event6th Mexican Conference on Pattern Recognition, MCPR 2014 - Cancun, Mexico
Duration: 25 Jun 201428 Jun 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8495 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th Mexican Conference on Pattern Recognition, MCPR 2014
Country/TerritoryMexico
CityCancun
Period25/06/1428/06/14

Keywords

  • Retinal image analysis
  • puzzle-based method
  • retinal vascular network separation

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