Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,592

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Diffeomorphic demons: Efficient non-parametric image registration

Open access
Vercauteren, Tom, Pennec, Xavier, Perchant, Aymeric, Ayache, Nicholas·2009·NeuroImage

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.neuroimage.2008.10.040

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Research works printed but not linked: 26

  1. Aubert-Broche, 2006, Twenty new digital brain phantoms for creation of validation image data bases, IEEE Trans. Med. Imag., 25, 1410, 10.1109/TMI.2006.883453 · DOI · Paper page
  2. Avants, 2008, Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain, Med. Image Anal., 12, 26, 10.1016/j.media.2007.06.004 · DOI · Paper page
  3. Barron, 1994, Performance of optical flow techniques, Int. J. Comput. Vis., 12, 43, 10.1007/BF01420984 · DOI · Paper page
  4. Beg, 2005, Computing large deformation metric mappings via geodesic flows of diffeomorphisms, Int. J. Comput. Vis., 61, 139, 10.1023/B:VISI.0000043755.93987.aa · DOI · Paper page
  5. Benhimane, 2007, Homography-based 2d visual tracking and servoing, Int. J. Rob. Res., 26, 661, 10.1177/0278364907080252 · DOI
  6. Cachier, 2004, Isotropic energies, filters and splines for vectorial regularization, J. Math. Imag. Vision, 20, 251, 10.1023/B:JMIV.0000024042.88755.4f · doi:10.1023/b:jmiv.0000024042.88755.4f
  7. Cachier, 2003, Iconic feature based nonrigid registration: the PASHA algorithm, Comput. Vis. Image Underst., 89, 272, 10.1016/S1077-3142(03)00002-X · DOI
  8. Christensen, 1996, Deformable templates using large deformation kinematics, IEEE Trans. Image Process., 5, 1435, 10.1109/83.536892 · DOI · Paper page
  9. Christensen, 1997, Volumetric transformation of brain anatomy, IEEE Trans. Med. Imag., 16, 864, 10.1109/42.650882 · DOI · Paper page
  10. Joshi, 2000, Landmark matching via large deformation diffeomorphisms, IEEE Trans. Image Process, 9, 1357, 10.1109/83.855431 · DOI · Paper page
  11. Leow, 2007, Statistical properties of Jacobian maps and the realization of unbiased large-deformation nonlinear image registration, IEEE Trans. Med. Imag., 26, 822, 10.1109/TMI.2007.892646 · DOI · Paper page
  12. Lepore, 2008, Generalized tensor-based morphometry of HIV/AIDS using multivariate statistics on deformation tensors, IEEE Trans. Med. Imag., 27, 129, 10.1109/TMI.2007.906091 · DOI · Paper page
  13. Mahony, 2002, The geometry of the Newton method on non-compact Lie-groups, J. Global Optim., 23, 309, 10.1023/A:1016586831090 · DOI
  14. Marsland, 2004, Constructing diffeomorphic representations for the groupwise analysis of non-rigid registrations of medical images, IEEE Trans. Med. Imag., 23, 1006, 10.1109/TMI.2004.831228 · DOI
  15. Noblet, 2005, 3-D deformable image registration: a topology preservation scheme based on hierarchical deformation models and interval analysis optimization, IEEE Trans. Image Process., 14, 553, 10.1109/TIP.2005.846026 · DOI
  16. Rogelj, 2006, Symmetric image registration, Med. Image Anal., 10, 484, 10.1016/j.media.2005.03.003 · DOI
  17. Trouvé, 1998, Diffeomorphisms groups and pattern matching in image analysis, Int. J. Comput. Vis., 28, 213, 10.1023/A:1008001603737 · DOI · Paper page
  18. Urschler, M., Kluckner, S., Bischof, H., 2007. A framework for comparison and evaluation of nonlinear intra-subject image registration algorithms. Insight Journal — ISC/NA-MIC Workshop on Open Science at MICCAI. Available online with code source at http://hdl.handle.net/1926/561. (Nov.) · DOI
  19. Vaillant, 2004, Statistics on diffeomorphisms via tangent space representations, Neuroimage, 23, 161, 10.1016/j.neuroimage.2004.07.023 · DOI · Paper page
  20. Vercauteren, T., 2008. Image registration and mosaicing for dynamic in vivo fibered confocal microscopy. PhD thesis, École Nationale Supérieure des Mines de Paris. (Jan.)
  21. Vercauteren, T., Pennec, X., Perchant, A., Ayache, N., 2007b. Diffeomorphic demons using ITK's finite difference solver hierarchy. Insight Journal — ISC/NA-MIC Workshop on Open Science at MICCAI. Available online with source code at http://hdl.handle.net/1926/510. (Nov.) · DOI
  22. Wang, 2005, Validation of an accelerated ‘demons’ algorithm for deformable image registration in radiation therapy, Phys. Med. Biol., 50, 2887, 10.1088/0031-9155/50/12/011 · DOI · Paper page
  23. Wüstner, 2003, A connected Lie group equals the square of the exponential image, J. Lie Theory, 13, 307
  24. Xue, 2006, Simulating deformations of MR brain images for validation of atlas-based segmentation and registration algorithms, Neuroimage, 33, 855, 10.1016/j.neuroimage.2006.08.007 · DOI
  25. Yeo, 2008, Effects of registration regularization and atlas sharpness on segmentation accuracy, Med. Image Anal., 12, 603, 10.1016/j.media.2008.06.005 · DOI
  26. Younes, 2007, Jacobi fields in groups of diffeomorphisms and applications, Quart. Appl. Math., 65, 113, 10.1090/S0033-569X-07-01027-5 · DOI

Cited by

See all 1,592

Metadata

Authors
Vercauteren, T., Pennec, X., Perchant, A., & Ayache, N.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2009-03
Volume
45
Issue
1
Pages
S61-S72
ISSN
1053-8119 (ISSN-L)
OpenAlex
W2103857226
Cited by
1,592
References
3
FWCI
68.25
Type
journal article
Language
en
Open access
green
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Diffeomorphic demons: Efficient non-parametric image registration. https://app.cochat.ai/papers/10.1016/j.neuroimage.2008.10.040
The paper
Vercauteren, T., Pennec, X., Perchant, A., & Ayache, N. (2009). Diffeomorphic demons: Efficient non-parametric image registration. NeuroImage. https://doi.org/10.1016/j.neuroimage.2008.10.040

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.