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Publications [#243890] of Ezra Miller

Papers Accepted

  1. Skwerer, S; Bullitt, E; Huckemann, S; Miller, E; Oguz, I; Owen, M; Patrangenaru, V; Provan, S; Marron, JS, Tree-oriented analysis of brain artery structure, Journal of Mathematical Imaging and Vision, vol. 50 no. 1 (January, 2014), pp. 126-143, ISSN 0924-9907 (25 pages.) [doi]
    (last updated on 2018/11/17)

    © Springer Science+Business Media New York 2014. 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 c orrespondence. 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 treespace, a mathematical space developed in (Billera et al. Adv. Appl. Math 27:733–767, 2001), facilitates this analysis. The phylogenetic treespace 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 show up in the descendant correspondence.
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