Standard
Weight preserving image registration for monitoring disease progression in lung CT. / Gorbunova, Vladlena; Lo, Pechin Chien Pau; Haseem, Ashraf; Dirksen, Asger; Nielsen, Mads; de Bruijne, Marleen.
Mecical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, proceedings, Part II. red. / D. Metaxas; L. Axel; G. Fichtinger; G. Szekely. Springer, 2008. s. 863-871 (Lecture notes in computer science; Nr. 5242).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Gorbunova, V, Lo, PCP, Haseem, A, Dirksen, A
, Nielsen, M & de Bruijne, M 2008,
Weight preserving image registration for monitoring disease progression in lung CT. i D Metaxas, L Axel, G Fichtinger & G Szekely (red),
Mecical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, proceedings, Part II. Springer, Lecture notes in computer science, nr. 5242, s. 863-871, International Conference on Medical Image Computing and Computer-Assisted Intervention, New York, NY, USA,
06/09/2008.
https://doi.org/10.1007/978-3-540-85990-1_104APA
Gorbunova, V., Lo, P. C. P., Haseem, A., Dirksen, A.
, Nielsen, M., & de Bruijne, M. (2008).
Weight preserving image registration for monitoring disease progression in lung CT. I D. Metaxas, L. Axel, G. Fichtinger, & G. Szekely (red.),
Mecical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, proceedings, Part II (s. 863-871). Springer. Lecture notes in computer science Nr. 5242
https://doi.org/10.1007/978-3-540-85990-1_104Vancouver
Gorbunova V, Lo PCP, Haseem A, Dirksen A
, Nielsen M, de Bruijne M.
Weight preserving image registration for monitoring disease progression in lung CT. I Metaxas D, Axel L, Fichtinger G, Szekely G, red., Mecical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, proceedings, Part II. Springer. 2008. s. 863-871. (Lecture notes in computer science; Nr. 5242).
https://doi.org/10.1007/978-3-540-85990-1_104Author
Gorbunova, Vladlena ; Lo, Pechin Chien Pau ; Haseem, Ashraf ; Dirksen, Asger ; Nielsen, Mads ; de Bruijne, Marleen. / Weight preserving image registration for monitoring disease progression in lung CT. Mecical Image Computing and Computer-Assisted Intervention - MICCAI 2008: 11th International Conference, New York, NY, USA, September 6-10, 2008, proceedings, Part II. red. / D. Metaxas ; L. Axel ; G. Fichtinger ; G. Szekely. Springer, 2008. s. 863-871 (Lecture notes in computer science; Nr. 5242).
Bibtex
@inproceedings{43b477f0c85c11dd9473000ea68e967b,
title = "Weight preserving image registration for monitoring disease progression in lung CT.",
abstract = "We present a new image registration based method for monitoring regional disease progression in longitudinal image studies of lung disease. A free-form image registration technique is used to match a baseline 3D CT lung scan onto a following scan. Areas with lower intensity in the following scan compared with intensities in the deformed baseline image indicate local loss of lung tissue that is associated with progression of emphysema. To account for differences in lung intensity owing to differences in the inspiration level in the two scans rather than disease progression, we propose to adjust the density of lung tissue with respect to local expansion or compression such that the total weight of the lungs is preserved during deformation. Our method provides a good estimation of regional destruction of lung tissue for subjects with a significant difference in inspiration level between CT scans and may result in a more sensitive measure of disease progression than standard quantitative CT measures.",
author = "Vladlena Gorbunova and Lo, {Pechin Chien Pau} and Ashraf Haseem and Asger Dirksen and Mads Nielsen and {de Bruijne}, Marleen",
year = "2008",
doi = "10.1007/978-3-540-85990-1_104",
language = "English",
isbn = "978-3-540-85989-5",
series = "Lecture notes in computer science",
publisher = "Springer",
number = "5242",
pages = "863--871",
editor = "D. Metaxas and L. Axel and G. Fichtinger and G. Szekely",
booktitle = "Mecical Image Computing and Computer-Assisted Intervention - MICCAI 2008",
address = "Switzerland",
note = "null ; Conference date: 06-09-2008 Through 10-09-2008",
}
RIS
TY - GEN
T1 - Weight preserving image registration for monitoring disease progression in lung CT.
AU - Gorbunova, Vladlena
AU - Lo, Pechin Chien Pau
AU - Haseem, Ashraf
AU - Dirksen, Asger
AU - Nielsen, Mads
AU - de Bruijne, Marleen
N1 - Conference code: 11
PY - 2008
Y1 - 2008
N2 - We present a new image registration based method for monitoring regional disease progression in longitudinal image studies of lung disease. A free-form image registration technique is used to match a baseline 3D CT lung scan onto a following scan. Areas with lower intensity in the following scan compared with intensities in the deformed baseline image indicate local loss of lung tissue that is associated with progression of emphysema. To account for differences in lung intensity owing to differences in the inspiration level in the two scans rather than disease progression, we propose to adjust the density of lung tissue with respect to local expansion or compression such that the total weight of the lungs is preserved during deformation. Our method provides a good estimation of regional destruction of lung tissue for subjects with a significant difference in inspiration level between CT scans and may result in a more sensitive measure of disease progression than standard quantitative CT measures.
AB - We present a new image registration based method for monitoring regional disease progression in longitudinal image studies of lung disease. A free-form image registration technique is used to match a baseline 3D CT lung scan onto a following scan. Areas with lower intensity in the following scan compared with intensities in the deformed baseline image indicate local loss of lung tissue that is associated with progression of emphysema. To account for differences in lung intensity owing to differences in the inspiration level in the two scans rather than disease progression, we propose to adjust the density of lung tissue with respect to local expansion or compression such that the total weight of the lungs is preserved during deformation. Our method provides a good estimation of regional destruction of lung tissue for subjects with a significant difference in inspiration level between CT scans and may result in a more sensitive measure of disease progression than standard quantitative CT measures.
U2 - 10.1007/978-3-540-85990-1_104
DO - 10.1007/978-3-540-85990-1_104
M3 - Article in proceedings
SN - 978-3-540-85989-5
T3 - Lecture notes in computer science
SP - 863
EP - 871
BT - Mecical Image Computing and Computer-Assisted Intervention - MICCAI 2008
A2 - Metaxas, D.
A2 - Axel, L.
A2 - Fichtinger, G.
A2 - Szekely, G.
PB - Springer
Y2 - 6 September 2008 through 10 September 2008
ER -
