Loading [a11y]/accessibility-menu.js
Anatomical Labeling of the Circle of Willis Using Maximum A Posteriori Probability Estimation | IEEE Journals & Magazine | IEEE Xplore

Anatomical Labeling of the Circle of Willis Using Maximum A Posteriori Probability Estimation


Abstract:

Anatomical labeling of the cerebral arteries forming the Circle of Willis (CoW) enables inter-subject comparison, which is required for geometric characterization and dis...Show More

Abstract:

Anatomical labeling of the cerebral arteries forming the Circle of Willis (CoW) enables inter-subject comparison, which is required for geometric characterization and discovering risk factors associated with cerebrovascular pathologies. We present a method for automated anatomical labeling of the CoW by detecting its main bifurcations. The CoW is modeled as rooted attributed relational graph, with bifurcations as its vertices, whose attributes are characterized as points on a Riemannian manifold. The method is first trained on a set of pre-labeled examples, where it learns the variability of local bifurcation features as well as the variability in the topology. Then, the labeling of the target vasculature is obtained as maximum a posteriori probability (MAP) estimate where the likelihood of labeling individual bifurcations is regularized by the prior structural knowledge of the graph they span. The method was evaluated by cross-validation on 50 subjects, imaged with magnetic resonance angiography, and showed a mean detection accuracy of 95%. In addition, besides providing the MAP, the method can rank the labelings. The proposed method naturally handles anatomical structural variability and is demonstrated to be suitable for labeling arterial segments of the CoW.
Published in: IEEE Transactions on Medical Imaging ( Volume: 32, Issue: 9, September 2013)
Page(s): 1587 - 1599
Date of Publication: 23 April 2013

ISSN Information:

PubMed ID: 23674438

References

References is not available for this document.