Quantification and Visualization of Variation in Anatomical Trees

Conference · Wed Jul 01 00:00:00 EDT 2015 · Proceedings from the Women in Shape Modeling Workshop, Institute for Pure and Applied Mathematics

OSTI ID:1179459

Amenta, Nina; Datar, Manasi; Dirksen, Asger; de Bruihne, Marleen; Feragen, Aasa; Ge, Xiaoyin; Holst Pedersen, Jesper; Howard, Marylesa; Owen, Megan; Petersen, Jens; Shi, Jie; Xu, Qiuping

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.

• Research Organization: Nevada Test Site (NTS), Mercury, NV (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: DE-AC52-06NA25946
• OSTI ID: 1179459
• Report Number(s): DOE/NV/25946-2016
• Journal Information: Proceedings from the Women in Shape Modeling Workshop, Institute for Pure and Applied Mathematics, Conference: Women in Shape Modeling Workshop, Institute for Pure and Applied Mathematics, July 2014
• Country of Publication: United States
• Language: English

Related Subjects

dataset
tree
quantification
visualization