Published in
Association for Women in Mathematics Series, p. 57-79
DOI: 10.1007/978-3-319-16348-2_5
Links
- ORCID
- ORCID
- Crossref
- [arxiv.org] | PDF
- [curis.ku.dk]
- [arxiv.org] | PDF
- [arxiv.org] | PDF
- [www.researchgate.net] | PDF
Tools
Quantification and visualization of variation in anatomical trees
Journal article published in 2014 by
Nina Amenta,
Manasi Datar,
Asger Dirksen,
Marleen de Bruijne 
,
Aasa Feragen,
Xiaoyin Ge,
Jesper Holst Pedersen,
Marylesa Howard,
Megan Owen,
Jens Petersen ,
Jie Shi,
Qiuping Xu
,
Aasa Feragen,
Xiaoyin Ge,
Jesper Holst Pedersen,
Marylesa Howard,
Megan Owen,
Jens Petersen ,
Jie Shi,
Qiuping Xu
Abstract
This paper presents two approaches to quantifying and visualizing variation in datasets of trees. The first approach localizes subtrees in which significant population differences are found through hypothesis testing and sparse classifiers on subtree features. The second approach visualizes the global metric structure of datasets through low-distortion embedding into hyperbolic planes in the style of multidimensional scaling. A case study is made on a dataset of airway trees in relation to Chronic Obstructive Pulmonary Disease. ; Comment: 22 pages