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. © 2011 Springer-Verlag.
CITATION STYLE
Jiang, Y., Zhuang, Z. W., Sinusas, A. J., Staib, L. H., & Papademetris, X. (2011). Vessel connectivity using Murray’s hypothesis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6893 LNCS, pp. 528–536). https://doi.org/10.1007/978-3-642-23626-6_65
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