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Tree-oriented analysis of brain artery structure

Publication ,  Journal Article
Skwerer, S; Bullitt, E; Huckemann, S; Miller, E; Oguz, I; Owen, M; Patrangenaru, V; Provan, S; Marron, JS
Published in: Journal of Mathematical Imaging and Vision
January 1, 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 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 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.

Duke Scholars

Published In

Journal of Mathematical Imaging and Vision

DOI

EISSN

1573-7683

ISSN

0924-9907

Publication Date

January 1, 2014

Volume

50

Issue

1

Start / End Page

126 / 143

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4901 Applied mathematics
  • 4606 Distributed computing and systems software
  • 4603 Computer vision and multimedia computation
  • 0802 Computation Theory and Mathematics
  • 0801 Artificial Intelligence and Image Processing
  • 0102 Applied Mathematics
 

Citation

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Skwerer, S., Bullitt, E., Huckemann, S., Miller, E., Oguz, I., Owen, M., … Marron, J. S. (2014). Tree-oriented analysis of brain artery structure. Journal of Mathematical Imaging and Vision, 50(1), 126–143. https://doi.org/10.1007/s10851-013-0473-0
Skwerer, S., E. Bullitt, S. Huckemann, E. Miller, I. Oguz, M. Owen, V. Patrangenaru, S. Provan, and J. S. Marron. “Tree-oriented analysis of brain artery structure.” Journal of Mathematical Imaging and Vision 50, no. 1 (January 1, 2014): 126–43. https://doi.org/10.1007/s10851-013-0473-0.
Skwerer S, Bullitt E, Huckemann S, Miller E, Oguz I, Owen M, et al. Tree-oriented analysis of brain artery structure. Journal of Mathematical Imaging and Vision. 2014 Jan 1;50(1):126–43.
Skwerer, S., et al. “Tree-oriented analysis of brain artery structure.” Journal of Mathematical Imaging and Vision, vol. 50, no. 1, Jan. 2014, pp. 126–43. Scopus, doi:10.1007/s10851-013-0473-0.
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. 2014 Jan 1;50(1):126–143.
Journal cover image

Published In

Journal of Mathematical Imaging and Vision

DOI

EISSN

1573-7683

ISSN

0924-9907

Publication Date

January 1, 2014

Volume

50

Issue

1

Start / End Page

126 / 143

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4901 Applied mathematics
  • 4606 Distributed computing and systems software
  • 4603 Computer vision and multimedia computation
  • 0802 Computation Theory and Mathematics
  • 0801 Artificial Intelligence and Image Processing
  • 0102 Applied Mathematics