Vessel Connectivity Using Murray’s Hypothesis

  • Yifeng Jiang
  • Zhen W. Zhuang
  • Albert J. Sinusas
  • Lawrence H. Staib
  • Xenophon Papademetris
Conference paper

DOI: 10.1007/978-3-642-23626-6_65

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6893)
Cite this paper as:
Jiang Y., Zhuang Z.W., Sinusas A.J., Staib L.H., Papademetris X. (2011) Vessel Connectivity Using Murray’s Hypothesis. In: Fichtinger G., Martel A., Peters T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6893. Springer, Berlin, Heidelberg

Abstract

We describe a new method for vascular image analysis that incorporates a generic physiological principle to estimate vessel connectivity, which is a key issue in reconstructing complete vascular trees from image data. We follow Murray’s hypothesis of the minimum work principle to formulate the problem as an optimization problem. This principle reflects a global property of any vascular network, in contrast to various local geometric properties adopted as constraints previously. We demonstrate the effectiveness of our method using a set of microCT mouse coronary images. It is shown that the performance of our method has a statistically significant improvement over the widely adopted minimum spanning tree methods that rely on local geometric constraints.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yifeng Jiang
    • 1
  • Zhen W. Zhuang
    • 2
  • Albert J. Sinusas
    • 1
    • 2
  • Lawrence H. Staib
    • 1
    • 3
    • 4
  • Xenophon Papademetris
    • 1
    • 3
  1. 1.Department of Diagnostic RadiologyYale UniversityNew HavenUSA
  2. 2.Department of Internal Medicine CardiologyYale UniversityNew HavenUSA
  3. 3.Department of Biomedical EngineeringYale UniversityNew HavenUSA
  4. 4.Department of Electrical EngineeringYale UniversityNew HavenUSA

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