DocumentCode :
3650827
Title :
Drusen quantification for early identification of age related macular degeneration (AMD) using color fundus imaging
Author :
Alauddin Bhuiyan;C. Karmakar;Di Xiao;Kotagiri Ramamohanarao;Yogi Kanagasingam
Author_Institution :
Australian E-Health Research Centre, Commonwealth Scientific and Industrial Research Organization (CSIRO), Perth, Australia
fYear :
2013
fDate :
7/1/2013 12:00:00 AM
Firstpage :
7392
Lastpage :
7395
Abstract :
Age-related macular degeneration (AMD) is a major cause of visual impairment in the elderly and identifying people with the early stages of AMD is important when considering the design and implementation of preventative strategies for late AMD. Quantification of drusen size and total area covered by drusen is an important risk factor for progression. In this paper, we propose a method to detect drusen and quantify drusen size along with the area covered with drusen in macular region from standard color retinal images. We used combined local intensity distribution, adaptive intensity thresholding and edge information to detect potential drusen areas. The proposed method detected the presence of any drusen with 100% accuracy (50/50 images). For drusen detection accuracy (DDA), the segmentations produced by the automated method on individual images achieved mean sensitivity and specificity values of 74.94% and 81.17%, respectively.
Keywords :
"Retina","Image edge detection","Accuracy","Shape","Image segmentation","Image color analysis","Histograms"
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
ISSN :
1094-687X
Electronic_ISBN :
1558-4615
Type :
conf
DOI :
10.1109/EMBC.2013.6611266
Filename :
6611266
Link To Document :
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