Vascular intersection detection in retina fundus images using a new hybrid approach

Document type: Journal Articles
Article type: Original article
Peer reviewed: Yes
Author(s): A.M. Aibinu, Muhammad Imran Iqbal, A.A. Shafie, M.J.E. Salami, Mikael Nilsson
Title: Vascular intersection detection in retina fundus images using a new hybrid approach
Journal: Computers in Biology and Medicine
Year: 2010
Volume: 40
Issue: 1
Pagination: 81-89
ISSN: 0010-4825
Publisher: Elsevier
URI/DOI: 10.1016/j.compbiomed.2009.11.004
ISI number: 000274948300009
Organization: Blekinge Institute of Technology
Department: School of Engineering - Dept. of Electrical Engineering (Sektionen för ingenjörsvetenskap - Avd. för elektroteknik)
School of Engineering S-371 79 Karlskrona
+46 455 38 50 00
Language: English
Abstract: The use of vascular intersection aberration as one of the signs when monitoring and diagnosing diabetic retinopathy from retina fundus images (FIs) has been widely reported in the literature. In this paper, a new hybrid approach called the combined cross-point number (CCN) method able to detect the vascular bifurcation and intersection points in FIs is proposed. The CCN method makes use of two vascular intersection detection techniques, namely the modified cross-point number (MCN) method and the simple cross-point number (SCN) method. Our proposed approach was tested on images obtained from two different and publicly available fundus image databases. The results show a very high precision, accuracy, sensitivity and low false rate in detecting both bifurcation and crossover points compared with both the MCN and the SCN methods.
Subject: Signal Processing\General
Keywords: Bifurcation, Crossover, Diabetic retinopathy, Fundus image, Vascular intersection