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. © 2013 Springer-Verlag.
CITATION STYLE
Robben, D., Sunaert, S., Thijs, V., Wilms, G., Maes, F., & Suetens, P. (2013). Anatomical labeling of the Circle of Willis using maximum a posteriori graph matching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8149 LNCS, pp. 566–573). https://doi.org/10.1007/978-3-642-40811-3_71
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