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Detection of Red Lesions in Eye Fundus Images

Automated detection of red lesions in eye fundus images is a critical step in screening for eye diseases like Diabetic Retinopathy in a computer assisted manner. In this short project, we attempt to study and implement an automated red lesion detection method based on that proposed by Niemeijer et al. (2004). The method involves extraction of candidate objects by morphological filtering of the fundus image followed by their classification based on k-Nearest Neighbour clustering of the feature vectors. The feature vectors used are a subset of those used by Niemeijer. A limited evaluation was performed on a small data set representative of the variety of images usually found in a screening set. The method, as it stands, is shown to detect red lesions, but not with very high accuracy or specificity.