Vessel connectivity using Murray's hypothesis

Authors:
Yifeng Jiang;Zhen W. Zhuang;Albert J. Sinusas;Lawrence H. Staib;Xenophon Papademetris
Affiliations:
Department of Diagnostic Radiology, Yale University, New Haven, CT;Department of Internal Medicine Cardiology, Yale University, New Haven, CT;Department of Diagnostic Radiology and Department of Internal Medicine Cardiology, Yale University, New Haven, CT;Department of Diagnostic Radiology and Department of Internal Medicine Cardiology and Department of Electrical Engineering, Yale University, New Haven, CT;Department of Diagnostic Radiology and Department of Internal Medicine Cardiology, Yale University, New Haven, CT
Venue:
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
Year:
2011

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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.