DocumentCode
1392612
Title
A Successive Clutter-Rejection-Based Approach for Early Detection of Diabetic Retinopathy
Author
Ram, Keerthi ; Joshi, Gopal Datt ; Sivaswamy, Jayanthi
Author_Institution
Centre for Visual Inf. Technol., Int. Inst. of Inf. Technol., Hyderabad, India
Volume
58
Issue
3
fYear
2011
fDate
3/1/2011 12:00:00 AM
Firstpage
664
Lastpage
673
Abstract
The presence of microaneurysms (MAs) is usually an early sign of diabetic retinopathy and their automatic detection from color retinal images is of clinical interest. In this paper, we present a new approach for automatic MA detection from digital color fundus images. We formulate MA detection as a problem of target detection from clutter, where the probability of occurrence of target is considerably smaller compared to the clutter. A successive rejection-based strategy is proposed to progressively lower the number of clutter responses. The processing stages are designed to reject specific classes of clutter while passing majority of true MAs, using a set of specialized features. The true positives that remain after the final rejector are assigned a score which is based on its similarity to a true MA. Results of extensive evaluation of the proposed approach on three different retinal image datasets are reported, and used to highlight the promise in the presented strategy.
Keywords
clutter; diseases; eye; image colour analysis; medical image processing; object detection; color retinal image; diabetic retinopathy; digital color fundus image; microaneurysm; successive clutter-rejection-based approach; target detection; Clutter; Context; Feature extraction; Image color analysis; Noise; Pixel; Retina; Clutter-rejection; diabetic retinopathy; microaneurysm; retinal image; Algorithms; Aneurysm; Diabetic Retinopathy; Diagnostic Techniques, Ophthalmological; Humans; Image Processing, Computer-Assisted; Retinal Vessels;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2010.2096223
Filename
5654583
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