Vessel connectivity using Murray's hypothesis

Med Image Comput Comput Assist Interv. 2011;14(Pt 3):528-36. doi: 10.1007/978-3-642-23626-6_65.

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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Animals
  • Coronary Circulation*
  • Coronary Vessels / pathology
  • Diagnostic Imaging / methods
  • Image Processing, Computer-Assisted / methods*
  • Mice
  • Mice, Inbred C57BL
  • Models, Cardiovascular
  • Models, Statistical
  • Models, Theoretical
  • X-Ray Microtomography / methods*