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Data fusion for multi-lesion Diabetic Retinopathy detection

Screening of Diabetic Retinopathy (DR) with timely treatment prevents blindness. Several researchers have focused their work on the development of computer-aided lesion-specific detectors. Combining detectors is a complex task as frequently the detectors have different properties and constraints and are not designed under a unified framework. We extend our previous work for detecting DR lesions based on points of interest and visual words to include additional detectors for the most common DR lesions and investigate fusion techniques to combine different classifiers for classification of normal or signs of diabetic retinopathy. The combination methods show promising results and shed light on the possible advantages of combining complementary lesion detectors for the DR diagnosis problem.