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          Institute: MPI für Entwicklungsbiologie     Collection: Abteilung 6 - Molecular Biology (D. Weigel)     Display Documents

ID: 681904.0, MPI für Entwicklungsbiologie / Abteilung 6 - Molecular Biology (D. Weigel)
Geometric tree kernels: Classification of COPD from airway tree geometry
Authors:Feragen, A.; Petersen, J.; Grimm, D.; Dirksen, A.; Pedersen, J.H.; Borgwardt, K.; de Bruijne, M.
Date of Publication (YYYY-MM-DD):2013
Title of Journal:Information Processing in Medical Imaging
Journal Abbrev.:IPMI
Start Page:171
End Page:183
Sequence Number of Article:24683967
Review Status:Internal review
Audience:Experts Only
Abstract / Description:Methodological contributions: This paper introduces a family of kernels for analyzing (anatomical) trees endowed with vector valued measurements made along the tree. While state-of-the-art graph and tree kernels use combinatorial tree/graph structure with discrete node and edge labels, the kernels presented in this paper can include geometric information such as branch shape, branch radius or other vector valued properties. In addition to being flexible in their ability to model different types of attributes, the presented kernels are computationally efficient and some of them can easily be computed for large datasets (N - 10.000) of trees with 30 - 600 branches. Combining the kernels with standard machine learning tools enables us to analyze the relation between disease and anatomical tree structure and geometry. Experimental results: The kernels are used to compare airway trees segmented from low-dose CT, endowed with branch shape descriptors and airway wall area percentage measurements made along the tree. Using kernelized hypothesis testing we show that the geometric airway trees are significantly differently distributed in patients with Chronic Obstructive Pulmonary Disease (COPD) than in healthy individuals. The geometric tree kernels also give a significant increase in the classification accuracy of COPD from geometric tree structure endowed with airway wall thickness measurements in comparison with state-of-the-art methods, giving further insight into the relationship between airway wall thickness and COPD. Software: Software for computing kernels and statistical tests is available at http://image.diku.dk/aasa/software.php.
External Publication Status:published
Document Type:Article
Affiliations:MPI für Entwicklungsbiologie/Abteilung 6 - Molekulare Biologie (Detlef Weigel)
Identifiers:URL:http://www.ncbi.nlm.nih.gov/pubmed/?term=Geometric... [PubMed]
ISBN:978-3-642-38868-2 [Online]
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