title: Automated intracranial aneurysm isolation and quantification.
abstract: Until today, geometrical descriptors of intracranial aneurysms are largely used for diagnosis and treatment selection. Nevertheless, relatively little work has been devoted to automatize these measurements. In this work we propose a methodology for the automated isolation and quantification from vascular segmentation. The proposed methodology is based on skeleton topology analysis, geometrical analysis and deformable models to isolate, automatically, the aneurysm dome as well as its geometrical characteristics. The accuracy of this methodology when compared to manually isolated aneurysms is evaluated in 10 patient-specific vascular geometries. Good correspondence is observed between manual and automated results.
authors.affiliation: Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain. ignacio.larrabide@upf.edu
authors.forename: Ignacio
authors.initials: I
authors.lastname: Larrabide
authors.forename: Maria
authors.initials: M
authors.lastname: Cruz Villa-Urio
authors.forename: Ruben
authors.initials: R
authors.lastname: Cardenes
authors.forename: Jose Maria
authors.initials: JM
authors.lastname: Pozo
authors.forename: D
authors.initials: D
authors.lastname: Hose
authors.forename: Alejandro F
authors.initials: AF
authors.lastname: Frangi
mesh_terms: D000465:Algorithms; D000783:Aneurysm; D001331:Automation; D003198:Computer Simulation; D003952:Diagnostic Imaging / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted; D002532:Intracranial Aneurysm / Q000175:diagnosis* / Q000503:physiopathology*; D008953:Models, Anatomic; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D012984:Software