Automated feature extraction for early detection of diabetic retinopathy in fundus images

By Saiprasad Ravishankar, Arpit Jain, Anurag Mittal. 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009

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Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus images (2017, background): “A lot of research has been conducted to detect specific lesion areas, like blood vessel transformations, exudates, microaneurysms and hemorrhages [10, 11, 12, 13, 14].”
Automatic hemorrhage detection in color fundus images based on gradual removal of vascular branches (2016, methodology): “Instead of the commonly used vessel subtraction in previous methods [3–5, 8, 16], we integrate them into a new image by fusing their individual advantages.”
An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading (2012, methodology): “We investigate the effect of processing images with the complete vessel system being removed based on the idea proposed in [11].”