Brownian Warps for Non-Rigid Registration

Research output: Contribution to journalJournal articlepeer-review

Standard

Brownian Warps for Non-Rigid Registration. / Nielsen, Mads; Johansen, Peter; Jackson, Andrew D.; Lautrup, Benny Elley; Hauberg, Søren.

In: Journal of Mathematical Imaging and Vision, Vol. 31, No. 2-3, 2008, p. 221-231.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Nielsen, M, Johansen, P, Jackson, AD, Lautrup, BE & Hauberg, S 2008, 'Brownian Warps for Non-Rigid Registration', Journal of Mathematical Imaging and Vision, vol. 31, no. 2-3, pp. 221-231. https://doi.org/10.1007/s10851-008-0083-4

APA

Nielsen, M., Johansen, P., Jackson, A. D., Lautrup, B. E., & Hauberg, S. (2008). Brownian Warps for Non-Rigid Registration. Journal of Mathematical Imaging and Vision, 31(2-3), 221-231. https://doi.org/10.1007/s10851-008-0083-4

Vancouver

Nielsen M, Johansen P, Jackson AD, Lautrup BE, Hauberg S. Brownian Warps for Non-Rigid Registration. Journal of Mathematical Imaging and Vision. 2008;31(2-3):221-231. https://doi.org/10.1007/s10851-008-0083-4

Author

Nielsen, Mads ; Johansen, Peter ; Jackson, Andrew D. ; Lautrup, Benny Elley ; Hauberg, Søren. / Brownian Warps for Non-Rigid Registration. In: Journal of Mathematical Imaging and Vision. 2008 ; Vol. 31, No. 2-3. pp. 221-231.

Bibtex

@article{953af430cc7d11dd9473000ea68e967b,
title = "Brownian Warps for Non-Rigid Registration",
abstract = "A Brownian motion model in the group of diffeomorphisms has been introduced as inducing a least committed prior on warps. This prior is source-destination symmetric, fulfills a natural semi-group property for warps, and with probability 1 creates invertible warps. Using this as a least committed prior, we formulate a Partial Differential Equation for obtaining the maximally likely warp given matching constraints derived from the images. We solve for the free boundary conditions, and the bias toward smaller areas in the finite domain setting. Furthermore, we demonstrate the technique on 2D images, and show that the obtained warps are also in practice source-destination symmetric and in an example on X-ray spine registration provides extrapolations from landmark point superior to those of spline solutions. Udgivelsesdato: July",
keywords = "Faculty of Science, DIKU, Image Group, Non-rigid registration, Brownian motion, Central limit theorem, Invariance",
author = "Mads Nielsen and Peter Johansen and Jackson, {Andrew D.} and Lautrup, {Benny Elley} and S{\o}ren Hauberg",
year = "2008",
doi = "10.1007/s10851-008-0083-4",
language = "English",
volume = "31",
pages = "221--231",
journal = "Journal of Mathematical Imaging and Vision",
issn = "0924-9907",
publisher = "Springer",
number = "2-3",

}

RIS

TY - JOUR

T1 - Brownian Warps for Non-Rigid Registration

AU - Nielsen, Mads

AU - Johansen, Peter

AU - Jackson, Andrew D.

AU - Lautrup, Benny Elley

AU - Hauberg, Søren

PY - 2008

Y1 - 2008

N2 - A Brownian motion model in the group of diffeomorphisms has been introduced as inducing a least committed prior on warps. This prior is source-destination symmetric, fulfills a natural semi-group property for warps, and with probability 1 creates invertible warps. Using this as a least committed prior, we formulate a Partial Differential Equation for obtaining the maximally likely warp given matching constraints derived from the images. We solve for the free boundary conditions, and the bias toward smaller areas in the finite domain setting. Furthermore, we demonstrate the technique on 2D images, and show that the obtained warps are also in practice source-destination symmetric and in an example on X-ray spine registration provides extrapolations from landmark point superior to those of spline solutions. Udgivelsesdato: July

AB - A Brownian motion model in the group of diffeomorphisms has been introduced as inducing a least committed prior on warps. This prior is source-destination symmetric, fulfills a natural semi-group property for warps, and with probability 1 creates invertible warps. Using this as a least committed prior, we formulate a Partial Differential Equation for obtaining the maximally likely warp given matching constraints derived from the images. We solve for the free boundary conditions, and the bias toward smaller areas in the finite domain setting. Furthermore, we demonstrate the technique on 2D images, and show that the obtained warps are also in practice source-destination symmetric and in an example on X-ray spine registration provides extrapolations from landmark point superior to those of spline solutions. Udgivelsesdato: July

KW - Faculty of Science

KW - DIKU

KW - Image Group

KW - Non-rigid registration

KW - Brownian motion

KW - Central limit theorem

KW - Invariance

U2 - 10.1007/s10851-008-0083-4

DO - 10.1007/s10851-008-0083-4

M3 - Journal article

VL - 31

SP - 221

EP - 231

JO - Journal of Mathematical Imaging and Vision

JF - Journal of Mathematical Imaging and Vision

SN - 0924-9907

IS - 2-3

ER -

ID: 9204645