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%.