title: Automated analysis of retinal vascular network connectivity.
abstract: This paper describes an algorithm that forms a retinal vessel graph by analysing the potential connectivity of segmented retinal vessels. Self organizing feature maps (SOFMs) are used to model implicit cost functions for the junction geometry. The algorithm uses these cost functions to resolve the configuration of local sets of segment ends, thus determining the network connectivity. The system includes specialized algorithms to handle overlapping vessels. The algorithm is tested on junctions drawn from the public-domain DRIVE database.
authors.affiliation: Lincoln School of Computer Science, University of Lincoln, UK. baldiri@lincoln.ac.uk
authors.forename: Bashir
authors.initials: B
authors.lastname: Al-Diri
authors.forename: Andrew
authors.initials: A
authors.lastname: Hunter
authors.forename: David
authors.initials: D
authors.lastname: Steel
authors.forename: Maged
authors.initials: M
authors.lastname: Habib
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted; D011859:Radiography; D012171:Retinal Vessels / Q000033:anatomy & histology* / Q000000981:diagnostic imaging