title: Detection of optic disc in retinal images by means of a geometrical model of vessel structure.
abstract: We present here a new method to identify the position of the optic disc (OD) in retinal fundus images. The method is based on the preliminary detection of the main retinal vessels. All retinal vessels originate from the OD and their path follows a similar directional pattern (parabolic course) in all images. To describe the general direction of retinal vessels at any given position in the image, a geometrical parametric model was proposed, where two of the model parameters are the coordinates of the OD center. Using as experimental data samples of vessel centerline points and corresponding vessel directions, provided by any vessel identification procedure, model parameters were identified by means of a simulated annealing optimization technique. These estimated values provide the coordinates of the center of OD. A Matlab prototype implementing this method was developed. An evaluation of the proposed procedure was performed using the set of 81 images from the STARE project, containing images from both normal and pathological subjects. The OD position was correctly identified in 79 out of 81 images (98%), even in rather difficult pathological situations.
authors.affiliation: Department of Information Engineering, University of Padova, 35131 Padova, Italy.
authors.forename: M
authors.initials: M
authors.lastname: Foracchia
authors.forename: E
authors.initials: E
authors.lastname: Grisan
authors.forename: A
authors.initials: A
authors.lastname: Ruggeri
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D005451:Fluorescein Angiography / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008954:Models, Biological; D009716:Numerical Analysis, Computer-Assisted; D009898:Optic Disk / Q000033:anatomy & histology* / Q000098:blood supply; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000033:anatomy & histology*; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted