NDLI: A new curvelet transform based method for extraction of red lesions in digital color retinal images

Content Provider	IEEE Xplore Digital Library
Author	Esmaeili, M. Rabbani, H. Dehnavi, A.M. Dehghani, A.
Copyright Year	2010
Description	Author affiliation: Department of Biomedical Engineering, Isfahan University of Medical Sciences, Iran (Esmaeili, M.; Rabbani, H.; Dehnavi, A.M.) \|\| Department of Ophthalmology, Isfahan University of Medical Sciences, Iran (Dehghani, A.)
Abstract	Red lesions in the form of Microaneurysms (MAs) and Hemorrhages (HMs) are among the first explicit signs of diabetic retinopathy (DR). Hence robust detection of these lesions is an important diagnostic task in computer assistance systems. In this paper we present a new curvelet based algorithm to separate these red lesions from the rest of the color retinal image. In order to prevent fovea to be considered as red lesion, we introduce a new illumination equalization algorithm and apply that to green plane of retinal image. In the next stage, we apply digital curvelet transform (DCUT) to produced enhanced image and modify curvelet coefficients in order to lead red objects to zero. Then we separate these lesions as candidate region by applying an appropriate threshold. Finally, the total structure of blood vessel is extracted employing a curvelet-based technique and the false positives (FPs) are eliminated by subtracting the vessel structure from the candidate images. Experiments on 89 retinal images of diabetic patients indicate that we are able to achieve 94% sensitivity and 87% specificity in detection of red lesion.
Starting Page	4093
Ending Page	4096
File Size	404980
Page Count	4
File Format	PDF
ISBN	9781424479924
ISSN	15224880
e-ISBN	9781424479948
e-ISBN	9781424479931
DOI	10.1109/ICIP.2010.5652820
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-26
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lesions Pixel Retina Image color analysis Transforms Biomedical imaging Diabetes Digital Curvelet Transform (DCUT) Retinal Image Red Lesion
Content Type	Text
Resource Type	Article

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