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Journal of Ophthalmology
Volume 2016 (2016), Article ID 4176547, 5 pages
http://dx.doi.org/10.1155/2016/4176547
Research Article

An Automated Detection System for Microaneurysms That Is Effective across Different Racial Groups

1Moorfields Eye Hospital NHS Foundation Trust, London, UK
2Department of Computing, Faculty of Engineering, University of Surrey, Guildford, UK
3National Institute for Health Research Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
4Barking, Havering and Redbridge University Hospitals Trust, London, UK
5Statistics Department, Faculty of Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
6Institute of Ophthalmology, UCL, London, UK

Received 22 March 2016; Revised 28 June 2016; Accepted 10 July 2016

Academic Editor: Neil Lagali

Copyright © 2016 George Michael Saleh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

George Michael Saleh, James Wawrzynski, Silvestro Caputo, et al., “An Automated Detection System for Microaneurysms That Is Effective across Different Racial Groups,” Journal of Ophthalmology, vol. 2016, Article ID 4176547, 5 pages, 2016. doi:10.1155/2016/4176547