title: Anatomical labeling of the circle of willis using maximum a posteriori graph matching.
abstract: A new method for anatomically labeling the vasculature is presented and applied to the Circle of Willis. Our method converts the segmented vasculature into a graph that is matched with an annotated graph atlas in a maximum a posteriori (MAP) way. The MAP matching is formulated as a quadratic binary programming problem which can be solved efficiently. Unlike previous methods, our approach can handle non tree-like vasculature and large topological differences. The method is evaluated in a leave-one-out test on MRA of 30 subjects where it achieves a sensitivity of 93% and a specificity of 85% with an average error of 1.5 mm on matching bifurcations in the vascular graph.
authors: iMinds-Medical Image Computing (ESAT/PSI), KU Leuven, Belgium. david.robben@esat.kuleuven.be
authors: David
authors: D
authors: Robben
authors: Department of Radiology, University Hospitals Leuven, KU Leuven, Belgium.
authors: Stefan
authors: S
authors: Sunaert
authors: Department of Neurology, University Hospitals Leuven, KU Leuven, Belgium.
authors: Vincent
authors: V
authors: Thijs
authors: Department of Radiology, University Hospitals Leuven, KU Leuven, Belgium.
authors: Guy
authors: G
authors: Wilms
authors: iMinds-Medical Image Computing (ESAT/PSI), KU Leuven, Belgium.
authors: Frederik
authors: F
authors: Maes
authors: iMinds-Medical Image Computing (ESAT/PSI), KU Leuven, Belgium.
authors: Paul
authors: P
authors: Suetens
mesh_terms: D000465:Algorithms; D002941:Circle of Willis / Q000033:anatomy & histology*; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008953:Models, Anatomic; D008955:Models, Cardiovascular; D008959:Models, Neurological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity