Extracting vascular networks under physiological constraints via integer programming

Markus Rempfler, Matthias Schneider, Giovanna D. Ielacqua, Xianghui Xiao, Stuart R. Stock, Jan Klohs, Gábor Székely, Bjoern Andres, Bjoern H. Menze

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

ASJC Scopus subject areas

  • Medicine(all)


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