title: Automatic tracing of optic disc and exudates from color fundus images using fixed and variable thresholds.
abstract: The detection of bright objects such as optic disc (OD) and exudates in color fundus images is an important step in the diagnosis of eye diseases such as diabetic retinopathy and glaucoma. In this paper, a novel approach to automatically segment the OD and exudates is proposed. The proposed algorithm makes use of the green component of the image and preprocessing steps such as average filtering, contrast adjustment, and thresholding. The other processing techniques used are morphological opening, extended maxima operator, minima imposition, and watershed transformation. The proposed algorithm is evaluated using the test images of STARE and DRIVE databases with fixed and variable thresholds. The images drawn by human expert are taken as the reference images. The proposed method yields sensitivity values as high as 96.7%, which are better than the results reported in the literature.
authors.affiliation: Centre for Multimedia and Distributed Computing, Faculty of Information Technology, Multimedia University, 63100 Cyberjaya, Malaysia. awreza98@yahoo.com
authors.forename: Ahmed Wasif
authors.initials: AW
authors.lastname: Reza
authors.forename: C
authors.initials: C
authors.lastname: Eswaran
authors.forename: Subhas
authors.initials: S
authors.lastname: Hati
mesh_terms: D003116:Color; D003930:Diabetic Retinopathy / Q000175:diagnosis; D003952:Diagnostic Imaging / Q000379:methods*; D005122:Exudates and Transudates; D005128:Eye Diseases / Q000175:diagnosis*; D005654:Fundus Oculi; D005901:Glaucoma / Q000175:diagnosis; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D009887:Ophthalmoscopy / Q000379:methods*; D009898:Optic Disk / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods