This paper presents an 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 red lesions 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 Multiscale Correlation Filtering (MSCF)
and dynamic thresholding is developed. This consists of two levels, Red Lesion Candidate Detection (coarse level) and
True Red Lesion Detection (fine level). The approach was evaluated using data from Retinopathy On-line Challenge
(ROC) competition website and we conclude our method to be effective and efficient.