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Detection of microaneurysms using multi-scale correlation coefficients
Authors:Bob Zhang [Author Vitae]  Jane You [Author Vitae]  Qin Li [Author Vitae]
Affiliation:a Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada
b School of Computer Science and Technology, Harbin Institute of Technology, Harbin, PR China
c Biometrics Research Center, Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong
Abstract:This paper presents a new approach to the computer aided diagnosis (CAD) of diabetic retinopathy (DR)—a common and severe complication of long-term diabetes which damages the retina and cause blindness. Since microaneurysms are regarded as the first signs of DR, there has been extensive research on effective detection and localization of these abnormalities in retinal images. In contrast to existing algorithms, a new approach based on multi-scale correlation filtering (MSCF) and dynamic thresholding is developed. This consists of two levels, microaneurysm candidate detection (coarse level) and true microaneurysm classification (fine level). The approach was evaluated based on two public datasets—ROC (retinopathy on-line challenge, http://roc.healthcare.uiowa.edu) and DIARETDB1 (standard diabetic retinopathy database, http://www.it.lut.fi/project/imageret/diaretdb1). We conclude our method to be effective and efficient.
Keywords:Computer-aided diagnosis (CAD)  Diabetic retinopathy (DR)  Multi-scale correlation filtering  Microaneurysm (red lesion) detection
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