Scholars@Duke publication: Persistent homology analysis of brain artery trees

Persistent homology analysis of brain artery trees

Publication , Journal Article

Bendich, P; Marron, JS; Miller, E; Pieloch, A; Skwerer, S

Published in: Annals of Applied Statistics

2016

New representations of tree-structured data objects, using ideas from topological data analysis, enable improved statistical analyses of a population of brain artery trees. A number of representations of each data tree arise from persistence diagrams that quantify branching and looping of vessels at multiple scales. Novel approaches to the statistical analysis, through various summaries of the persistence diagrams, lead to heightened correlations with covariates such as age and sex, relative to earlier analyses of this data set. The correlation with age continues to be significant even after controlling for correlations from earlier significant summaries

Duke Scholars

Author Paul L Bendich Mathematics

Author Ezra Miller Mathematics

Published In

Annals of Applied Statistics

Publication Date

2016

Volume

Issue

Start / End Page

198 / 218

Related Subject Headings

Statistics & Probability
4905 Statistics
1403 Econometrics
0104 Statistics

Citation

APA

Chicago

ICMJE

MLA

NLM

Bendich, P., Marron, J. S., Miller, E., Pieloch, A., & Skwerer, S. (2016). Persistent homology analysis of brain artery trees. Annals of Applied Statistics, 10(1), 198–218.

Bendich, P., J. S. Marron, E. Miller, A. Pieloch, and S. Skwerer. “Persistent homology analysis of brain artery trees.” Annals of Applied Statistics 10, no. 1 (2016): 198–218.

Bendich P, Marron JS, Miller E, Pieloch A, Skwerer S. Persistent homology analysis of brain artery trees. Annals of Applied Statistics. 2016;10(1):198–218.

Bendich, P., et al. “Persistent homology analysis of brain artery trees.” Annals of Applied Statistics, vol. 10, no. 1, 2016, pp. 198–218.

Bendich P, Marron JS, Miller E, Pieloch A, Skwerer S. Persistent homology analysis of brain artery trees. Annals of Applied Statistics. 2016;10(1):198–218.