Detection of Retinal Vascular Bifurcations by Trainable V4-Like Filters

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23 Citaten (Scopus)


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.

Originele taal-2English
TitelComputer Analysis of Images and Patterns
Subtitel14th International Conference, CAIP 2011, Seville, Spain, August 29-31, 2011, Proceedings, Part I
RedacteurenA Berciano, D DiazPernil, W Kropatsch, H MolinaAbril, P Real
Plaats van productieBERLIN
Aantal pagina's9
ISBN van elektronische versie9783642236723
ISBN van geprinte versie978-3-642-23671-6
StatusPublished - 2011
Evenement14th International Conference on Computer Analysis of Images and Patterns (CAIP) - , Spain
Duur: 29-aug-201131-aug-2011

Publicatie series

NaamLecture Notes in Computer Science
ISSN van geprinte versie0302-9743


Other14th International Conference on Computer Analysis of Images and Patterns (CAIP)

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