Quantification and visualization of variation in anatomical trees

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

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationResearch in shape modeling
EditorsKathryn Leonard, Sibel Tari
Number of pages23
PublisherSpringer
Publication date2015
Pages57-79
Chapter5
ISBN (Print)978-3-319-16347-5
DOIs
Publication statusPublished - 2015
SeriesAssociation for Women in Mathematics Series
Volume1
ISSN2364-5733

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