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Journal of Biomedical Optics

Optimal algorithm for automatic detection of microaneurysms based on receiver operating characteristic curve
Author(s): Lili Xu; Shuqian Luo
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Paper Abstract

Microaneurysms (MAs) are the first manifestations of the diabetic retinopathy (DR) as well as an indicator for its progression. Their automatic detection plays a key role for both mass screening and monitoring and is therefore in the core of any system for computer-assisted diagnosis of DR. The algorithm basically comprises the following stages: candidate detection aiming at extracting the patterns possibly corresponding to MAs based on mathematical morphological black top hat, feature extraction to characterize these candidates, and classification based on support vector machine (SVM), to validate MAs. Feature vector and kernel function of SVM selection is very important to the algorithm. We use the receiver operating characteristic (ROC) curve to evaluate the distinguishing performance of different feature vectors and different kernel functions of SVM. The ROC analysis indicates the quadratic polynomial SVM with a combination of features as the input shows the best discriminating performance.

Paper Details

Date Published: 1 November 2010
PDF: 6 pages
J. Biomed. Opt. 15(6) 065004 doi: 10.1117/1.3523367
Published in: Journal of Biomedical Optics Volume 15, Issue 6
Show Author Affiliations
Lili Xu, Capital Medical Univ. (China)
Shuqian Luo, Capital Medical Univ. (China)

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