@inproceedings{e1ec0272e8c349a08e9a2bcade1cea81,
title = "Detection of Retinal Vascular Bifurcations by Trainable V4-Like Filters",
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.",
keywords = "DRIVE, Gabor filters, retinal fundus, trainable filters, V4 neurons, vessel bifurcation, AREA V4, FEATURES, IMAGES, SHAPE",
author = "G. Azzopardi and N. Petkov",
note = "Rights: Springer; 14th International Conference on Computer Analysis of Images and Patterns (CAIP) ; Conference date: 29-08-2011 Through 31-08-2011",
year = "2011",
language = "English",
isbn = "978-3-642-23671-6",
volume = "6854",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "451--459",
editor = "A Berciano and D DiazPernil and W Kropatsch and H MolinaAbril and P Real",
booktitle = "Computer Analysis of Images and Patterns",
}