Standard
Kernel bundle EPDiff : Evolution equations for multi-scale diffeomorphic image registration. / Sommer, Stefan Horst; Lauze, Francois Bernard; Nielsen, Mads; Pennec, Xavier.
Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers: Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 – June 2, 2011, Revised Selected Papers. red. / Alfred Bruckstein; Bart M. ter Haar Romeny; Alexander M. Bronstein; Michael M. Bronstein. Springer, 2012. s. 677-688 (Lecture notes in computer science, Bind 6667).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Sommer, SH, Lauze, FB, Nielsen, M & Pennec, X 2012,
Kernel bundle EPDiff: Evolution equations for multi-scale diffeomorphic image registration. i A Bruckstein, BM ter Haar Romeny, AM Bronstein & MM Bronstein (red),
Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers: Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 – June 2, 2011, Revised Selected Papers. Springer, Lecture notes in computer science, bind 6667, s. 677-688, 3rd International Conference on Scale Space and Variational Methods in Computer Vision, Ein-Gedi, Israel,
29/05/2011.
https://doi.org/10.1007/978-3-642-24785-9_57,
https://doi.org/10.1007/978-3-642-24785-9_57
APA
Sommer, S. H., Lauze, F. B., Nielsen, M., & Pennec, X. (2012).
Kernel bundle EPDiff: Evolution equations for multi-scale diffeomorphic image registration. I A. Bruckstein, B. M. ter Haar Romeny, A. M. Bronstein, & M. M. Bronstein (red.),
Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers: Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 – June 2, 2011, Revised Selected Papers (s. 677-688). Springer. Lecture notes in computer science Bind 6667
https://doi.org/10.1007/978-3-642-24785-9_57,
https://doi.org/10.1007/978-3-642-24785-9_57
Vancouver
Sommer SH, Lauze FB, Nielsen M, Pennec X.
Kernel bundle EPDiff: Evolution equations for multi-scale diffeomorphic image registration. I Bruckstein A, ter Haar Romeny BM, Bronstein AM, Bronstein MM, red., Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers: Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 – June 2, 2011, Revised Selected Papers. Springer. 2012. s. 677-688. (Lecture notes in computer science, Bind 6667).
https://doi.org/10.1007/978-3-642-24785-9_57,
https://doi.org/10.1007/978-3-642-24785-9_57
Author
Sommer, Stefan Horst ; Lauze, Francois Bernard ; Nielsen, Mads ; Pennec, Xavier. / Kernel bundle EPDiff : Evolution equations for multi-scale diffeomorphic image registration. Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers: Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 – June 2, 2011, Revised Selected Papers. red. / Alfred Bruckstein ; Bart M. ter Haar Romeny ; Alexander M. Bronstein ; Michael M. Bronstein. Springer, 2012. s. 677-688 (Lecture notes in computer science, Bind 6667).
Bibtex
@inproceedings{438aa80e196d4fe6a47c5cdd5c265f38,
title = "Kernel bundle EPDiff: Evolution equations for multi-scale diffeomorphic image registration",
abstract = "In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space information to be automatically incorporated in registrations and promises to improve the standard framework in several aspects. We present the mathematical foundations of LDDKBM and derive the KB-EPDiff evolution equations, which provide optimal warps in this new framework. To illustrate the resulting diffeomorphism paths, we give examples showing the decoupled evolution across scales and how the method automatically incorporates deformation at appropriate scales.",
keywords = "computational anatomy, diffeomorphic registration, kernels, LDDKBM, LDDMM, momentum, scale space",
author = "Sommer, {Stefan Horst} and Lauze, {Francois Bernard} and Mads Nielsen and Xavier Pennec",
year = "2012",
doi = "10.1007/978-3-642-24785-9_57",
language = "English",
isbn = "978-3-642-24784-2",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "677--688",
editor = "{ Bruckstein}, Alfred and { ter Haar Romeny}, {Bart M.} and Bronstein, {Alexander M.} and Bronstein, {Michael M.}",
booktitle = "Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers",
address = "Switzerland",
note = "null ; Conference date: 29-05-2011 Through 02-06-2011",
}
RIS
TY - GEN
T1 - Kernel bundle EPDiff
AU - Sommer, Stefan Horst
AU - Lauze, Francois Bernard
AU - Nielsen, Mads
AU - Pennec, Xavier
N1 - Conference code: 3
PY - 2012
Y1 - 2012
N2 - In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space information to be automatically incorporated in registrations and promises to improve the standard framework in several aspects. We present the mathematical foundations of LDDKBM and derive the KB-EPDiff evolution equations, which provide optimal warps in this new framework. To illustrate the resulting diffeomorphism paths, we give examples showing the decoupled evolution across scales and how the method automatically incorporates deformation at appropriate scales.
AB - In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space information to be automatically incorporated in registrations and promises to improve the standard framework in several aspects. We present the mathematical foundations of LDDKBM and derive the KB-EPDiff evolution equations, which provide optimal warps in this new framework. To illustrate the resulting diffeomorphism paths, we give examples showing the decoupled evolution across scales and how the method automatically incorporates deformation at appropriate scales.
KW - computational anatomy
KW - diffeomorphic registration
KW - kernels
KW - LDDKBM
KW - LDDMM
KW - momentum
KW - scale space
U2 - 10.1007/978-3-642-24785-9_57
DO - 10.1007/978-3-642-24785-9_57
M3 - Article in proceedings
AN - SCOPUS:84855665269
SN - 978-3-642-24784-2
T3 - Lecture notes in computer science
SP - 677
EP - 688
BT - Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers
A2 - Bruckstein, Alfred
A2 - ter Haar Romeny, Bart M.
A2 - Bronstein, Alexander M.
A2 - Bronstein, Michael M.
PB - Springer
Y2 - 29 May 2011 through 2 June 2011
ER -
