NDLI: Microaneurysm detection in retinal images using a rotating cross-section based model

Content Provider	IEEE Xplore Digital Library
Author	Lazar, I. Hajdu, A.
Copyright Year	2011
Description	Author affiliation: Faculty of Informatics, University of Debrecen, POB 12, 4010, Hungary (Lazar, I.; Hajdu, A.)
Abstract	Retinal image analysis is currently a very vivid field in biomedical image analysis. One of the most challenging tasks is the reliable automatic detection of microaneurysms (MAs). Computer systems that aid the automatic detection of diabetic retinopathy (DR) greatly rely on MA detection. In this paper, we present a method to construct an MA score map, from which the final MAs can be extracted by simple thresholding for a binary output, or by considering all the regional maxima to obtain probability scores. In contrary to most of the currently available MA detectors, the proposed one does not use any supervised training and classification. However, it is still competitive in the field, with a prominent performance in the detection of MAs close to the vasculature, regarding the state-of-the-art methods. The algorithm has been evaluated in a publicly available online challenge.
Starting Page	1405
Ending Page	1409
File Size	268937
Page Count	5
File Format	PDF
ISBN	9781424441273
ISSN	19457928
DOI	10.1109/ISBI.2011.5872663
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Retina Pixel Training Retinopathy Detectors Image segmentation Biomedical imaging intensity profile Biomedical image processing pattern recognition microaneurysm detection
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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