Detection of Retinal Vascular Bifurcations by Trainable V4-Like Filters

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Abstract

The detection of vascular bifurcations in retinal fundus images is important for finding signs of various cardiovascular diseases. We propose a novel method to detect such bifurcations. Our method is implemented in trainable filters that mimic the properties of shape-selective neurons in area V4 of visual cortex. Such a filter is configured by combining given channels of a bank of Gabor filters in an AND-gate-like operation. Their selection is determined by the automatic analysis of a bifurcation feature that is specified by the user from a training image. Consequently, the filter responds to the same and similar bifurcations. With only 25 filters we achieved a correct detection rate of 98.52% at a precision rate of 95.19% on a set of 40 binary fundus images, containing more than 5000 bifurcations. In principle, all vascular bifurcations can be detected if a sufficient number of filters are configured and used.

Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns
Subtitle of host publication14th International Conference, CAIP 2011, Seville, Spain, August 29-31, 2011, Proceedings, Part I
EditorsA Berciano, D DiazPernil, W Kropatsch, H MolinaAbril, P Real
Place of PublicationBERLIN
PublisherSpringer
Pages451-459
Number of pages9
Volume6854
ISBN (Electronic)9783642236723
ISBN (Print)978-3-642-23671-6
Publication statusPublished - 2011
Event14th International Conference on Computer Analysis of Images and Patterns (CAIP) - , Spain
Duration: 29-Aug-201131-Aug-2011

Publication series

NameLecture Notes in Computer Science
PublisherSPRINGER-VERLAG BERLIN
Volume6854
ISSN (Print)0302-9743

Other

Other14th International Conference on Computer Analysis of Images and Patterns (CAIP)
Country/TerritorySpain
Period29/08/201131/08/2011

Keywords

  • DRIVE
  • Gabor filters
  • retinal fundus
  • trainable filters
  • V4 neurons
  • vessel bifurcation
  • AREA V4
  • FEATURES
  • IMAGES
  • SHAPE

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