title: Blood vessels and feature points detection on retinal images.
abstract: In this paper we present a method for the automatic extraction of blood vessels from retinal images, while capturing points of intersection/overlap and endpoints of the vascular tree. The algorithm performance is evaluated through a comparison with handmade segmented images available on the STARE project database (STructured Analysis of the REtina). The algorithm is performed on the green channel of the RGB triad. The green channel can be used to represent the illumination component. The matched filter is used to enhance vessels w.r.t. the background. The separation between vessels and background is accomplished by a threshold operator based on gaussian probability density function. The length filtering removes pixels and isolated segments from the resulting image. Finally endpoints, intersections and overlapping vessels are extracted.
authors.affiliation: Dipartimento di Ingegneria Informatica viale delle Scienze, Italy. ardizzon@unipa.it
authors.forename: Edoardo
authors.initials: E
authors.lastname: Ardizzone
authors.forename: Roberto
authors.initials: R
authors.lastname: Pirrone
authors.forename: Orazio
authors.initials: O
authors.lastname: Gambino
authors.forename: Salvatore
authors.initials: S
authors.lastname: Radosta
mesh_terms: D000465:Algorithms; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012160:Retina / Q000033:anatomy & histology; D012171:Retinal Vessels / Q000502:physiology*; D012680:Sensitivity and Specificity