title: Decision support system for the detection and grading of hard exudates from color fundus photographs.
abstract: Diabetic retinopathy is a major cause of blindness, and its earliest signs include damage to the blood vessels and the formation of lesions in the retina. Automated detection and grading of hard exudates from the color fundus image is a critical step in the automated screening system for diabetic retinopathy. We propose novel methods for the detection and grading of hard exudates and the main retinal structures. For exudate detection, a novel approach based on coarse-to-fine strategy and a new image-splitting method are proposed with overall sensitivity of 93.2% and positive predictive value of 83.7% at the pixel level. The average sensitivity of the blood vessel detection is 85%, and the success rate of fovea localization is 100%. For exudate grading, a polar fovea coordinate system is adopted in accordance with medical criteria. Because of its competitive performance and ability to deal efficiently with images of variable quality, the proposed technique offers promising and efficient performance as part of an automated screening system for diabetic retinopathy.
authors: University of Liverpool, Department of Electrical Engineering and Electronics, Liverpool, United Kingdom.
authors: Hussain F
authors: HF
authors: Jaafar
authors: Asoke K
authors: AK
authors: Nandi
authors: Waleed
authors: W
authors: Al-Nuaimy
mesh_terms: D020000:Decision Support Systems, Clinical; D003930:Diabetic Retinopathy / Q000175:diagnosis* / Q000473:pathology*; D003941:Diagnostic Techniques, Ophthalmological; D005122:Exudates and Transudates / Q000737:chemistry*; D005654:Fundus Oculi; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D012372:ROC Curve; D012171:Retinal Vessels / Q000033:anatomy & histology