title: Extracting vascular networks under physiological constraints via integer programming.
abstract: We introduce an integer programming-based approach to vessel network extraction that enforces global physiological constraints on the vessel structure and learn this prior from a high-resolution reference network. The method accounts for both image evidence and geometric relationships between vessels by formulating and solving an integer programming problem. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating bifurcation angle and connectivity of the graph. We utilize a high-resolution micro computed tomography (μCT) dataset of a cerebrovascular corrosion cast to obtain a reference network, perform experiments on micro magnetic resonance angiography (μMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.
authors.forename: Markus
authors.initials: M
authors.lastname: Rempfler
authors.forename: Matthias
authors.initials: M
authors.lastname: Schneider
authors.forename: Giovanna D
authors.initials: GD
authors.lastname: Ielacqua
authors.forename: Xianghui
authors.initials: X
authors.lastname: Xiao
authors.forename: Stuart R
authors.initials: SR
authors.lastname: Stock
authors.forename: Jan
authors.initials: J
authors.lastname: Klohs
authors.forename: Gábor
authors.initials: G
authors.lastname: Székely
authors.forename: Bjoern
authors.initials: B
authors.lastname: Andres
authors.forename: Bjoern H
authors.initials: BH
authors.lastname: Menze
mesh_terms: D000465:Algorithms; D002533:Cerebral Angiography / Q000379:methods*; D002536:Cerebral Arteries / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity