Dissimilarity-based classification of anatomical tree structures

Lauge Sørensen*, Pechin Lo, Asger Dirksen, Jens Petersen, Marleen De Bruijne

*Corresponding author for this work

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

5 Citations (Scopus)


A novel method for classification of abnormality in anatomical tree structures is presented. A tree is classified based on direct comparisons with other trees in a dissimilarity-based classification scheme. The pair-wise dissimilarity measure between two trees is based on a linear assignment between the branch feature vectors representing those trees. Hereby, localized information in the branches is collectively used in classification and variations in feature values across the tree are taken into account. An approximate anatomical correspondence between matched branches can be achieved by including anatomical features in the branch feature vectors. The proposed approach is applied to classify airway trees in computed tomography images of subjects with and without chronic obstructive pulmonary disease (COPD). Using the wall area percentage (WA%), a common measure of airway abnormality in COPD, as well as anatomical features to characterize each branch, an area under the receiver operating characteristic curve of 0.912 is achieved. This is significantly better than computing the average WA%.

Original languageEnglish
Title of host publicationInformation Processing in Medical Imaging - 22nd International Conference, IPMI 2011, Proceedings
Number of pages11
Publication statusPublished - 2011
Event22nd International Conference on Information Processing in Medical Imaging, IPMI 2011 - Kloster Irsee, Germany
Duration: 3 Jul 20118 Jul 2011

Publication series

SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6801 LNCS


Conference22nd International Conference on Information Processing in Medical Imaging, IPMI 2011
CityKloster Irsee


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