Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/14131
Title: Retinal blood vessel segmentation via graph cut
Authors: Salazar-Gonzalez, AG
Li, Y
Liu, X
Keywords: Retinal images;Vessel segmentation;Graph cut
Issue Date: 2011
Publisher: IEEE
Citation: 11th International Conference on Control, Automation, Robotics and Vision, (ICARCV 2010), 7-10 December, pp. 225 - 230, (2010)
Abstract: Image analysis is becoming increasingly prominent as a non intrusive diagnosis in modern ophthalmology. Blood vessel morphology is an important indicator for diseases like diabetes, hypertension and retinopathy. This paper presents an automated and unsupervised method for retinal blood vessels segmentation using the graph cut technique. The graph is constructed using a rough segmentation from a pre-processed image together with spatial pixel connection. The proposed method was tested on two public datasets and compared with other methods. Experimental results show that this method outperforms other unsupervised methods and demonstrate the competitiveness with supervised methods. ©2010 IEEE.
URI: http://bura.brunel.ac.uk/handle/2438/14131
DOI: http://dx.doi.org/10.1109/ICARCV.2010.5707265
ISBN: 978-1-4244-7815-6
Appears in Collections:Dept of Computer Science Research Papers

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