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Efficient Metropolis-Hasting Image Analysis for the Location of Vascular Entity

  • Henrik SkibbeEmail author
  • Marco Reisert
  • Shin Ishii
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8753)

Abstract

In this paper we present a novel approach for probabilistically exploring and modeling vascular networks in 3D angiograms. For modeling the vascular morphology and topology a graph-like particle model is used. Each particle represents the intrinsic properties of a small fraction of a vessel including position, orientation and scale. Explicit connections between particles determine the network topology. In evaluation using simulated as well as real X-ray and time-of-flight MRI angiograms the proposed method was able to accurately model the vascular network.

Notes

Acknowledgment

This work was supported by Bioinformatics for Brain Sciences under the Strategic Research Program for Brain Sciences, MEXT (Japan). The work of M. Reisert is supported by the Deutsche Forschungsgemeinschaft (DFG), grant RE 3286/2-1.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Graduate School of InformaticsKyoto UniversityKyotoJapan
  2. 2.Department of RadiologyUniversity Hospital FreiburgFreiburgGermany

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