Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40903
Title: Constrained-MSER detection of retinal pathology
Authors: San, G.L.Y.
Lee, M.L. 
Hsu, W. 
Issue Date: 2012
Source: San, G.L.Y.,Lee, M.L.,Hsu, W. (2012). Constrained-MSER detection of retinal pathology. Proceedings - International Conference on Pattern Recognition : 2059-2062. ScholarBank@NUS Repository.
Abstract: With the increase in age and diabetes-related eye diseases, there is a rising demand for systems which can efficiently screen and locate abnormalities in retinal images. In this paper, we propose a framework that utilizes a variant of the Maximally Stable Extremal Region method, termed C-MSER, to systematically detect various retinopathy pathologies such as microaneurysms, haemorrhages, hard exudates and soft exudates. Experiments on three real-world datasets show that C-MSER is effective for online screening of diabetic retinopathy. © 2012 ICPR Org Committee.
Source Title: Proceedings - International Conference on Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/40903
ISBN: 9784990644109
ISSN: 10514651
Appears in Collections:Staff Publications

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