title: A knowledge-based approach to 3-D reconstruction of human cerebral vasculature.
abstract: Good visualisation of the vasculature is essential in the diagnosis and treatment of a variety of brain disorders. This paper presents a new approach to 3-D reconstruction of vascular structures using knowledge-based image processing and multimodal image fusion. The task is to reconstruct the human cerebro-vascular system from the partial information collected from a variety of medical imaging instruments and then recombine these limited models into an anatomically accurate one.
authors.affiliation: Faculty of Computer and Information Science, University of Ljubljana, Slovenia. tatjana@fri.uni-lj.si
authors.forename: T
authors.initials: T
authors.lastname: Zrimec
mesh_terms: D000465:Algorithms; D001165:Arteriovenous Malformations / Q000175:diagnosis / Q000628:therapy; D001185:Artificial Intelligence; D002533:Cerebral Angiography; D002536:Cerebral Arteries / Q000033:anatomy & histology*; D002550:Cerebral Veins / Q000033:anatomy & histology*; D006801:Humans; D018810:Magnetic Resonance Angiography; D008955:Models, Cardiovascular; D011856:Radiographic Image Enhancement / Q000379:methods*