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Abstract Details
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Activity Number:
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136
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #303336 |
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Title:
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Hierarchical Characterization of Loopy Vascular Networks
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Author(s):
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Marcelo Osvaldo Magnasco*+ and Eleni Katifori
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Companies:
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Rockefeller University and Rockefeller University
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Address:
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1230 York Avenue, New York, NY, 10065, United States
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Keywords:
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Venation ;
Network ;
Optimal ;
Transport
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Abstract:
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Two dimensional vascular networks, such as leaf veins, retinal vasculature or the surface arteriole network of the cerebral cortex, are characterized by the presence of dense, hierarchically organized loops. Recent work has shown that networks optimized to be resilient to damage, or to spatio-temporal fluctuations in demand display this characteristic recurrent loopy structure. However, detailed morphological comparisons are hindered by the lack of an adequate statistical characterization of such networks. We show that a procedure based on recursive merging of planar facets by breaking the thinnest link in the network results in a well-ordered hierarchy, and that the corresponding tree can be characterized through Horton-Strahler-like laws, permitting detailed morphological characterization of tree species and comparisons between theory and experiment.
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