Detection of microaneurysms using multi-scale correlation coefficients

Authors:
Bob Zhang;Xiangqian Wu;Jane You;Qin Li;Fakhri Karray
Affiliations:
Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, PR China and Biometrics Research Center, Department of Computing, The Hong Kong Polytechnic University, Kowloon, ...;Biometrics Research Center, Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Biometrics Research Center, Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada
Venue:
Pattern Recognition
Year:
2010

Citing 5
Cited 5

An image-processing strategy for the segmentation and quantification of microaneurysms in fluorescein angiograms of the ocular fundus

Computers and Biomedical Research
Irregular motion recovery in fluorescein angiograms

Pattern Recognition Letters
Automatic Segmentation of Microaneurysms in Retinal Angiograms of Diabetic Patients

ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
A modified matched filter with double-sided thresholding for screening proliferative diabetic retinopathy

IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
A local adaptive algorithm for microaneurysms detection in digital fundus images

CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications

Improving microaneurysm detection using an optimally selected subset of candidate extractors and preprocessing methods

Pattern Recognition
Detection and discrimination of disease-related abnormalities based on learning normal cases

Pattern Recognition
Identification and classification of microaneurysms for early detection of diabetic retinopathy

Pattern Recognition
A complementary method for automated detection of microaneurysms in fluorescein angiography fundus images to assess diabetic retinopathy

Pattern Recognition
Computer-aided diagnosis of diabetic retinopathy: A review

Computers in Biology and Medicine

Quantified Score

Hi-index	0.01

Visualization

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.