An ensemble classification based approach applied to retinal blood vessel segmentation

Fraz, M.M., Remagnino, P., Hoppe, A., Uyyanonvara, B., Rudnicka, A.R., Owen, C.G. and Barman, S.A. (2012) An ensemble classification based approach applied to retinal blood vessel segmentation. IEEE Transactions on Biomedical Engineering, 59(9), pp. 2538-2548. ISSN (print) 0018-9294

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Abstract

This paper presents a new supervised method for segmentation of blood vessels in retinal photographs. This method uses an ensemble system of bagged and boosted decision trees and utilizes a feature vector based on the orientation analysis of gradient vector field, morphological transformation, line strength measures, and Gabor filter responses. The feature vector encodes information to handle the healthy as well as the pathological retinal image. The method is evaluated on the publicly available DRIVE and STARE databases, frequently used for this purpose and also on a new public retinal vessel reference dataset CHASE_DB1 which is a subset of retinal images of multiethnic children from the Child Heart and Health Study in England (CHASE) dataset. The performance of the ensemble system is evaluated in detail and the incurred accuracy, speed, robustness, and simplicity make the algorithm a suitable tool for automated retinal image analysis.

Item Type: Article
Uncontrolled Keywords: ensemble classification, medical image analysis, retinal blood vessels, segmentation
Research Area: Computer science and informatics
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing
Faculty of Science, Engineering and Computing > Digital Imaging Research Centre (DIRC)
Faculty of Science, Engineering and Computing > School of Computing and Information Systems
Related URLs:
Depositing User: Moazam Fraz
Date Deposited: 20 Aug 2012 12:14
Last Modified: 14 Feb 2014 11:54
URI: http://eprints.kingston.ac.uk/id/eprint/23326

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