Dissimilarity-based classification of anatomical tree structures

Authors:
Lauge Sørensen;Pechin Lo;Asger Dirksen;Jens Petersen;Marleen De Bruijne
Affiliations:
The Image Group, Department of Computer Science, University of Copenhagen, Denmark;The Image Group, Department of Computer Science, University of Copenhagen, Denmark;Department of Respiratory Medicine, Gentofte University Hospital, Denmark;The Image Group, Department of Computer Science, University of Copenhagen, Denmark;The Image Group, Department of Computer Science, University of Copenhagen, Denmark and Biomedical Imaging Group Rotterdam, Departments of Radiology & Medical Informatics, The Netherlands
Venue:
IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
Year:
2011

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Abstract

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%.