Journals Proceedings

Abstract

Diabetic retinopathy is a serious complication of diabetes mellitus and a major cause of blindness worldwide. Microaneurysms are the first clinically observable lesions indicating diabetic retinopathy. We propose an ensemble-based framework to improve microaneurysm detection. Unlike the well-known approach of considering the output of multiple classifiers, we propose a combination of internal components of microaneurysm detectors, namely preprocessing methods and candidate extractors.