title: Detecting the optic disc boundary in digital fundus images using morphological, edge detection, and feature extraction techniques.
abstract: Optic disc (OD) detection is an important step in developing systems for automated diagnosis of various serious ophthalmic pathologies. This paper presents a new template-based methodology for segmenting the OD from digital retinal images. This methodology uses morphological and edge detection techniques followed by the Circular Hough Transform to obtain a circular OD boundary approximation. It requires a pixel located within the OD as initial information. For this purpose, a location methodology based on a voting-type algorithm is also proposed. The algorithms were evaluated on the 1200 images of the publicly available MESSIDOR database. The location procedure succeeded in 99% of cases, taking an average computational time of 1.67 s. with a standard deviation of 0.14 s. On the other hand, the segmentation algorithm rendered an average common area overlapping between automated segmentations and true OD regions of 86%. The average computational time was 5.69 s with a standard deviation of 0.54 s. Moreover, a discussion on advantages and disadvantages of the models more generally used for OD segmentation is also presented in this paper.
authors.affiliation: Department of Electronic, Computer Science and Automatic Engineering, ”La Rábida” Polytechnic School, University of Huelva, 21071 Huelva, Spain. arturo.aquino@diesia.uhu.es
authors.forename: Arturo
authors.initials: A
authors.lastname: Aquino
authors.forename: Manuel Emilio
authors.initials: ME
authors.lastname: Gegundez-Arias
authors.forename: Diego
authors.initials: D
authors.lastname: Marin
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005654:Fundus Oculi; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009898:Optic Disk / Q000033:anatomy & histology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity