The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Consistent image registration
Abstract
This paper presents a new method for image registration based on jointly estimating the forward and reverse transformations between two images while constraining these transforms to be inverses of one another. This approach produces a consistent set of transformations that have less pairwise registration error, i.e., better correspondence, than traditional methods that estimate the forward and reverse transformations independently. The transformations are estimated iteratively and are restricted to preserve topology by constraining them to obey the laws of continuum mechanics. The transformations are parameterized by a Fourier series to diagonalize the covariance structure imposed by the continuum mechanics constraints and to provide a computationally efficient numerical implementation. Results using a linear elastic material constraint are presented using both magnetic resonance and X-ray computed tomography image data. The results show that the joint estimation of a consistent set of forward and reverse transformations constrained by linear-elasticity give better registration results than using either constraint alone or none at all.
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Citations
Cites
Multimodality image registration by maximization of mutual information
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., & Suetens, P. (1997) · IEEE Transactions on Medical Imaging · doi:10.1109/42.563664 · Cited by 4,547
Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space
Collins, D. L., Neelin, P., Peters, T. M., & Evans, A. C. (1994) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199403000-00005 · Cited by 3,431
Image matching as a diffusion process: an analogy with maxwell’s demons
Thirion, J.-P. (1998) · Medical Image Analysis · doi:10.1016/s1361-8415(98)80022-4 · Cited by 2,445
Cited by
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration
Klein, A., Andersson, J., Ardekani, B. A., Ashburner, J., Avants, B., Chiang, M.-C., Christensen, G. E., Collins, D. L., Gee, J., Hellier, P., et al. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.037 · Cited by 2,227
Self-citationDeformable medical image registration: a survey
Sotiras, A., Davatzikos, C., & Paragios, N. (2013) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2265603 · Cited by 1,587
“to tackle this shortcoming, Christensen and Johnson [19] pro-”
BackgroundInfluentialA Review of Geometric Transformations for Nonrigid Body Registration
Holden, M. (2008) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2007.904691 · Cited by 369
Symmetric Log-Domain Diffeomorphic Registration: A Demons-Based Approach
Vercauteren, T., Pennec, X., Perchant, A., & Ayache, N. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-85988-8_90 · Cited by 342
Evaluating fMRI preprocessing pipelines
Strother, S. C. (2006) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2006.1607667 · Cited by 169
Metadata
- Authors
- Christensen, G. E., & Johnson, H. J.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2001-07
- Volume
- 20
- Issue
- 7
- Pages
- 568-582
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2001666669
- Cited by
- 636
- References
- 3
- FWCI
- 28.80
- Type
- journal article
- Language
- en
- Open access
- closed
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