Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEMBS.2010.5627289
Title: Towards automatic detection of age-related macular degeneration in retinal fundus images
Authors: Liang, Z.
Wong, D.W.K.
Liu, J.
Chan, K.L.
Wong, T.Y. 
Issue Date: 2010
Citation: Liang, Z., Wong, D.W.K., Liu, J., Chan, K.L., Wong, T.Y. (2010). Towards automatic detection of age-related macular degeneration in retinal fundus images. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 : 4100-4103. ScholarBank@NUS Repository. https://doi.org/10.1109/IEMBS.2010.5627289
Abstract: Age-related macular degeneration (AMD) is a leading cause of blindness worldwide. The disease is highly associated with age, and becoming increasingly prevalent in our aging societies. Drusen is a pathological feature that is well-associated with AMD. In this paper, we present a method of detecting drusen in retinal fundus images. The method first determines the location of the macula, which is used as a landmark for a clinical drusen grading overlay. Subsequently, regions of drusen are identified though a maximal region-based pixel intensity approach via RGB and HSV channels. Methods of reducing the effect of retinal and choroidal vessels are also described. The system is tested on a sample set of 16 fundus images from a clinical study, with half having drusen. Experiments on the results show a sensitivity and specificity of 0.75 on the test image set. © 2010 IEEE.
Source Title: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
URI: http://scholarbank.nus.edu.sg/handle/10635/108620
ISBN: 9781424441235
DOI: 10.1109/IEMBS.2010.5627289
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

25
checked on Sep 19, 2018

WEB OF SCIENCETM
Citations

17
checked on Sep 19, 2018

Page view(s)

28
checked on Sep 14, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.