@inproceedings{3a1703e732cb4c2c9814d32347f97970,
title = "Dissimilarity-based classification of anatomical tree structures",
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%.",
author = "Lauge S{\o}rensen and Pechin Lo and Asger Dirksen and Jens Petersen and {De Bruijne}, Marleen",
year = "2011",
doi = "10.1007/978-3-642-22092-0_39",
language = "English",
isbn = "9783642220913",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science+Business Media",
pages = "475--485",
booktitle = "Information Processing in Medical Imaging - 22nd International Conference, IPMI 2011, Proceedings",
note = "22nd International Conference on Information Processing in Medical Imaging, IPMI 2011 ; Conference date: 03-07-2011 Through 08-07-2011",
}