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

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaPattern Recognition - 6th Mexican Conference, MCPR 2014, Proceedings
EditorialSpringer Verlag
Páginas251-260
Número de páginas10
ISBN (versión impresa)9783319074900
DOI
EstadoPublicada - 2014
Evento6th Mexican Conference on Pattern Recognition, MCPR 2014 - Cancun, México
Duración: 25 jun. 201428 jun. 2014

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen8495 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia6th Mexican Conference on Pattern Recognition, MCPR 2014
País/TerritorioMéxico
CiudadCancun
Período25/06/1428/06/14

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