Math @ Duke
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Publications [#221013] of Ezra Miller
Papers Accepted
- Sean Skwerer, Elizabeth Bullitt, Stephan Huckemann, Ezra Miller, Ipek Oguz, Megan Owen, Vic Patrangenaru, Scott Provan, and J.S. Marron, Tree-oriented analysis of brain artery structure,
Journal of Mathematical Imaging and Vision
(2013) (25 pages.)
(last updated on 2013/12/20)
Abstract: Statistical analysis of magnetic resonance angiography (MRA) brain
artery trees is performed using two methods for mapping brain artery
trees to points in phylogenetic treespace: cortical landmark
correspondence and descendant correspondence. The differences in end
results based on these mappings are highlighted to emphasize the
importance of correspondence in tree-oriented data analysis.
Representation of brain artery systems as points in phylogenetic tree
space, a mathematical space developed by Billera, Holmes, and
Vogtmann, facilitates this analysis. Phylogenetic tree space is a
rich setting for tree-oriented data analysis. The Fréchet sample mean
or an approximation is reported. Multidimensional scaling is used to
explore structure in the data set based on pairwise distances between
data points. This analysis of MRA data shows a statistically
significant effect of age and sex on brain artery structure.
Variation in the proximity of brain arteries to the cortical surface
results in strong statistical difference between sexes and
statistically significant age effect. That particular observation is
possible with cortical correspondence but did not appear in the
descendant correspondence.
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