Dissimilarity-based classification of anatomical tree structures
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Dissimilarity-based classification of anatomical tree structures. / Sørensen, Lauge; Lo, Pechin Chien Pau; Dirksen, Asger; Petersen, Jens; de Bruijne, Marleen.
Information Processing in Medical Imaging: 22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. Proceedings. red. / Gábor Székely; Horst K. Hahn. Springer, 2011. s. 475-485 (Lecture notes in computer science, Bind 6801).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - Dissimilarity-based classification of anatomical tree structures
AU - Sørensen, Lauge
AU - Lo, Pechin Chien Pau
AU - Dirksen, Asger
AU - Petersen, Jens
AU - de Bruijne, Marleen
N1 - Conference code: 22
PY - 2011
Y1 - 2011
N2 - 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%.
AB - 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%.
U2 - 10.1007/978-3-642-22092-0_39
DO - 10.1007/978-3-642-22092-0_39
M3 - Article in proceedings
SN - 978-3-642-22091-3
T3 - Lecture notes in computer science
SP - 475
EP - 485
BT - Information Processing in Medical Imaging
A2 - Székely, Gábor
A2 - Hahn, Horst K.
PB - Springer
Y2 - 3 July 2011 through 8 July 2011
ER -
ID: 33166996