NDLI: Automated Microaneurysm Segmentation and Detection using Generalized Eigenvectors

Content Provider	IEEE Xplore Digital Library
Author	Pallawala, P.M.D. Wynne Hsu Mong Li Lee Say Song Goh
Copyright Year	2005
Description	Author affiliation: Sch. of Comput., Nat. Univ. of Singapore, Singapore (Pallawala, P.M.D.; Wynne Hsu; Mong Li Lee)
Abstract	Diabetic retinopathy is a major cause of blindness and microaneurysms are the first clinically observable manifestations of diabetic retinopathy. Regular screening and timely intervention can halt or reverse the progression of this disease. This paper describes an approach that is based on the generalized eigenvectors of affinity matrix to extract microaneurysms from digital retinal images. Microaneurysms are in the low intensity regions and detection is complicated by their small sizes, the presence of retinal vessels, and their similarity to another type of retinal abnormality - haemorrhages. In order to accurately detect microaneurysms, the affinity matrix is defined to suppress larger structures such as blood vessels, haemorrhages, etc and to create uniform affinity distribution for pixels belonging to microaneurysms. The generalized eigenvector solution seeks to find the optimal segmentation for microaneurysms and provides indication to the possible locations of microaneurysms. We differentiate the true microaneurysms by studying their feature characteristics. Experiments on 70 retinal sub-images of diabetic patients indicate that we are able to achieve 93% accuracy in the detection of microaneurysms.
Starting Page	322
Ending Page	327
File Size	199369
Page Count	6
File Format	PDF
ISBN	0769522718
DOI	10.1109/ACVMOT.2005.26
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-01-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Retina Diabetes Retinopathy Blindness Hemorrhaging Diseases Retinal vessels Pigmentation Filtering Image segmentation
Content Type	Text
Resource Type	Article

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