ABSTRACT
Detecting retinal exudate lesions in a large number of images generated by screening programs is very expensive in professional time and open to human error. Thus, we explore the benefits of developing an automated decision support system for the purpose of detecting and classifying exudate pathologies of diabetic retinopathy. The retinal images are automatically analyzed in terms of pixel resolution and an assessment of the level of retinopathy is derived.
