title: Accurate and reliable segmentation of the optic disc in digital fundus images.
abstract: We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based optic disc localization, and fitting of incrementally complex contour models at increasing resolutions using information related to inpainted images and vessel masks. Validation experiments, performed on a large dataset of images of healthy and pathological eyes, annotated by experts and partially graded with a quality label, demonstrate the good performances of the proposed approach. The method is able to detect the optic disc and trace its contours better than the other systems presented in the literature and tested on the same data. The average error in the obtained contour masks is reasonably close to the interoperator errors and suitable for practical applications. The optic disc segmentation pipeline is currently integrated in a complete software suite for the semiautomatic quantification of retinal vessel properties from fundus camera images (VAMPIRE).
authors.affiliation: Università di Verona , Dipartimento di Informatica, Strada Le Grazie 15 Verona 37134, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Giachetti
authors.affiliation: University of Dundee , VAMPIRE, School of Computing, School of Computing, Queen Mother Building, Balfour Street, Dundee DD1 4HN, United Kingdom.
authors.forename: Lucia
authors.initials: L
authors.lastname: Ballerini
authors.affiliation: University of Dundee , VAMPIRE, School of Computing, School of Computing, Queen Mother Building, Balfour Street, Dundee DD1 4HN, United Kingdom.
authors.forename: Emanuele
authors.initials: E
authors.lastname: Trucco
keywords: active contours; inpainting; multiresolution; optic disc; radial symmetry; validation