The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Automated Image Registration: II. Intersubject Validation of Linear and Nonlinear Models
Abstract
PURPOSE: Our goal was to validate linear and nonlinear intersubject image registration using an automated method (AIR 3.0) based on voxel intensity. METHOD: PET and MRI data from 22 normal subjects were registered to corresponding averaged PET or MRI brain atlases using several specific linear and nonlinear spatial transformation models with an automated algorithm. Validation was based on anatomically defined landmarks. RESULTS: Automated registration produced results that were superior to a manual nine parameter variant of the Talairach registration method. Increasing the degrees of freedom in the spatial transformation model improved the accuracy of automated intersubject registration. CONCLUSION: Linear or nonlinear automated intersubject registration based on voxel intensities is computationally practical and produces more accurate alignment of homologous landmarks than manual nine parameter Talairach registration. Nonlinear models provide better registration than linear models but are slower.
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Cites
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
Riemannian center of mass and mollifier smoothing
Karcher, H. (1977) · Communications on Pure and Applied Mathematics · doi:10.1002/cpa.3160300502 · Cited by 995
Cited by
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610
Ashburner, J., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.018 · Cited by 7,507
A reproducible evaluation of ANTs similarity metric performance in brain image registration
Avants, B. B., Tustison, N. J., Song, G., Cook, P. A., Klein, A., & Gee, J. C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.09.025 · Cited by 4,796
Andersson, J. L. R., Skare, S., & Ashburner, J. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00336-7 · Cited by 3,469
Automated Talairach Atlas labels for functional brain mapping
Lancaster, J. L., Woldorff, M. G., Parsons, L. M., Liotti, M., Freitas, C. S., Rainey, L., Kochunov, P. V., Nickerson, D., Mikiten, S. A., & Fox, P. T. (2000) · Human Brain Mapping · doi:10.1002/1097-0193(200007)10:3<120::aid-hbm30>3.0.co;2-8 · Cited by 3,387
Metadata
- Authors
- Woods, R. P., Grafton, S. T., Watson, J. D. G., Sicotte, N. L., & Mazziotta, J. C.
- Venue
- Journal of Computer Assisted Tomography
- Published
- 1998-01
- Volume
- 22
- Issue
- 1
- Pages
- 153-165
- ISSN
- 0363-8715 (ISSN-L)
- OpenAlex
- W2053133374
- Cited by
- 994
- References
- 2
- FWCI
- 75.37
- Type
- journal article
- Language
- en
- Open access
- closed
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- Woods, R. P., Grafton, S. T., Watson, J. D. G., Sicotte, N. L., & Mazziotta, J. C. (1998). Automated Image Registration: II. Intersubject Validation of Linear and Nonlinear Models. Journal of Computer Assisted Tomography. https://doi.org/10.1097/00004728-199801000-00028
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