Growcut-based drusen segmentation for age-related macular degeneration detection

Growcut-based drusen segmentation for age-related macular degeneration detection
Title:
Growcut-based drusen segmentation for age-related macular degeneration detection
Other Titles:
2014 IEEE Visual Communications and Image Processing Conference
DOI:
10.1109/VCIP.2014.7051529
Keywords:
Publication Date:
07 December 2014
Citation:
Liu, Huiying, Yanwu Xu, Damon WK Wong, and Jiang Liu. "Growcut-based drusen segmentation for age-related macular degeneration detection." In Visual Communications and Image Processing Conference, 2014 IEEE, pp. 161-164. IEEE, 2014. Harvard
Abstract:
Age-related Macular Degeneration (AMD) is the third leading cause of blindness. Its prevalence is increasing in these years for the coming of "aging time". Early detection and grading can prohibit it from becoming severe and protect vision. The appearance of drusen is an important indicator for AMD thus automatic drusen detection and segmentation have attracted much research attention in the past years. In this paper, we propose a novel drusen segmentation method by using Growcut. This method first detects the local maximum and minimum points. The maximum points, which are potential drusen, are then classified as drusen or non-drusen. The drusen points will be used as foreground labels while the non-drusen points together with the minima will be used as background labels. These labels are fed into Growcut to obtain the drusen boundaries. The method is tested on a manually labeled dataset with 96 images containing drusen. The experimental results verify the effectiveness of the method.
License type:
PublisherCopyrights
Funding Info:
Description:
(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISBN:
978-1-4799-6139-9
978-1-4799-6140-5
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