Standard
A hierarchical scheme for geodesic anatomical labeling of airway trees. / Feragen, Aasa; Petersen, Jens; Owen, Megan; Lo, Pechin Chien Pau; Thomsen, Laura; Wille, Mathilde M. W.; Dirksen, Asger; de Bruijne, Marleen.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III. ed. / Nicholas Ayache ; Hervé Delingette ; Polina Golland; Kensaku Mori . Springer, 2012. p. 147-155 (Lecture notes in computer science, Vol. 7512).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Feragen, A
, Petersen, J, Owen, M, Lo, PCP, Thomsen, L, Wille, MMW, Dirksen, A
& de Bruijne, M 2012,
A hierarchical scheme for geodesic anatomical labeling of airway trees. in N Ayache , H Delingette , P Golland & K Mori (eds),
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III. Springer, Lecture notes in computer science, vol. 7512, pp. 147-155, 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, Nice, France,
01/10/2012.
https://doi.org/10.1007/978-3-642-33454-2_19APA
Feragen, A.
, Petersen, J., Owen, M., Lo, P. C. P., Thomsen, L., Wille, M. M. W., Dirksen, A.
, & de Bruijne, M. (2012).
A hierarchical scheme for geodesic anatomical labeling of airway trees. In N. Ayache , H. Delingette , P. Golland, & K. Mori (Eds.),
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III (pp. 147-155). Springer. Lecture notes in computer science Vol. 7512
https://doi.org/10.1007/978-3-642-33454-2_19Vancouver
Feragen A
, Petersen J, Owen M, Lo PCP, Thomsen L, Wille MMW et al.
A hierarchical scheme for geodesic anatomical labeling of airway trees. In Ayache N, Delingette H, Golland P, Mori K, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III. Springer. 2012. p. 147-155. (Lecture notes in computer science, Vol. 7512).
https://doi.org/10.1007/978-3-642-33454-2_19Author
Feragen, Aasa ; Petersen, Jens ; Owen, Megan ; Lo, Pechin Chien Pau ; Thomsen, Laura ; Wille, Mathilde M. W. ; Dirksen, Asger ; de Bruijne, Marleen. / A hierarchical scheme for geodesic anatomical labeling of airway trees. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III. editor / Nicholas Ayache ; Hervé Delingette ; Polina Golland ; Kensaku Mori . Springer, 2012. pp. 147-155 (Lecture notes in computer science, Vol. 7512).
Bibtex
@inproceedings{7afc1510bdb64b3f8a2e37beb9a574ba,
title = "A hierarchical scheme for geodesic anatomical labeling of airway trees",
abstract = "We present a fast and robust supervised algorithm for label-ing anatomical airway trees, based on geodesic distances in a geometrictree-space. Possible branch label configurations for a given unlabeled air-way tree are evaluated based on the distances to a training set of labeledairway trees. In tree-space, the airway tree topology and geometry changecontinuously, giving a natural way to automatically handle anatomicaldifferences and noise. The algorithm is made efficient using a hierarchicalapproach, in which labels are assigned from the top down. We only usefeatures of the airway centerline tree, which is relatively unaffected bypathology.A thorough leave-one-patient-out evaluation of the algorithm is made on40 segmented airway trees from 20 subjects labeled by 2 medical experts.We evaluate accuracy, reproducibility and robustness in patients withChronic Obstructive Pulmonary Disease (COPD). Performance is statis-tically similar to the inter- and intra-expert agreement, and we found nosignificant correlation between COPD stage and labeling accuracy.",
author = "Aasa Feragen and Jens Petersen and Megan Owen and Lo, {Pechin Chien Pau} and Laura Thomsen and Wille, {Mathilde M. W.} and Asger Dirksen and {de Bruijne}, Marleen",
year = "2012",
doi = "10.1007/978-3-642-33454-2_19",
language = "English",
isbn = "978-3-642-33453-5",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "147--155",
editor = "{Ayache }, {Nicholas } and {Delingette }, {Herv{\'e} } and Golland, {Polina } and {Mori }, {Kensaku }",
booktitle = "Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012",
address = "Switzerland",
note = "15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 ; Conference date: 01-10-2012 Through 05-10-2012",
}
RIS
TY - GEN
T1 - A hierarchical scheme for geodesic anatomical labeling of airway trees
AU - Feragen, Aasa
AU - Petersen, Jens
AU - Owen, Megan
AU - Lo, Pechin Chien Pau
AU - Thomsen, Laura
AU - Wille, Mathilde M. W.
AU - Dirksen, Asger
AU - de Bruijne, Marleen
N1 - Conference code: 15
PY - 2012
Y1 - 2012
N2 - We present a fast and robust supervised algorithm for label-ing anatomical airway trees, based on geodesic distances in a geometrictree-space. Possible branch label configurations for a given unlabeled air-way tree are evaluated based on the distances to a training set of labeledairway trees. In tree-space, the airway tree topology and geometry changecontinuously, giving a natural way to automatically handle anatomicaldifferences and noise. The algorithm is made efficient using a hierarchicalapproach, in which labels are assigned from the top down. We only usefeatures of the airway centerline tree, which is relatively unaffected bypathology.A thorough leave-one-patient-out evaluation of the algorithm is made on40 segmented airway trees from 20 subjects labeled by 2 medical experts.We evaluate accuracy, reproducibility and robustness in patients withChronic Obstructive Pulmonary Disease (COPD). Performance is statis-tically similar to the inter- and intra-expert agreement, and we found nosignificant correlation between COPD stage and labeling accuracy.
AB - We present a fast and robust supervised algorithm for label-ing anatomical airway trees, based on geodesic distances in a geometrictree-space. Possible branch label configurations for a given unlabeled air-way tree are evaluated based on the distances to a training set of labeledairway trees. In tree-space, the airway tree topology and geometry changecontinuously, giving a natural way to automatically handle anatomicaldifferences and noise. The algorithm is made efficient using a hierarchicalapproach, in which labels are assigned from the top down. We only usefeatures of the airway centerline tree, which is relatively unaffected bypathology.A thorough leave-one-patient-out evaluation of the algorithm is made on40 segmented airway trees from 20 subjects labeled by 2 medical experts.We evaluate accuracy, reproducibility and robustness in patients withChronic Obstructive Pulmonary Disease (COPD). Performance is statis-tically similar to the inter- and intra-expert agreement, and we found nosignificant correlation between COPD stage and labeling accuracy.
U2 - 10.1007/978-3-642-33454-2_19
DO - 10.1007/978-3-642-33454-2_19
M3 - Article in proceedings
SN - 978-3-642-33453-5
T3 - Lecture notes in computer science
SP - 147
EP - 155
BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012
A2 - Ayache , Nicholas
A2 - Delingette , Hervé
A2 - Golland, Polina
A2 - Mori , Kensaku
PB - Springer
T2 - 15th International Conference on Medical Image Computing and Computer-Assisted Intervention
Y2 - 1 October 2012 through 5 October 2012
ER -
