The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Spatial registration and normalization of images
Abstract
This paper concerns the spatial and intensity transformations that map one image onto another. We present a general technique that facilitates nonlinear spatial (stereotactic) normalization and image realignment. This technique minimizes the sum of squares between two images following nonlinear spatial deformations and transformations of the voxel (intensity) values. The spatial and intensity transformations are obtained simultaneously, and explicitly, using a least squares solution and a series of linearising devices. The approach is completely noninteractive (automatic), nonlinear, and noniterative. It can be applied in any number of dimensions. Various applications are considered, including the realignment of functional magnetic resonance imaging (MRI) time‐series, the linear (affine) and nonlinear spatial normalization of positron emission tomography (PET) and structural MRI images, the coregistration of PET to structural MRI, and, implicitly, the conjoining of PET and MRI to obtain high resolution functional images. © 1995 Wiley‐Liss, Inc.
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Citations
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 · cited 1×
“Again, these can be linear (e.g., principal axes [Alpert et al., 19901; image realignment [Woods et al., 1992; Collins et al., 1994; and see Lange, 19941) or nonlinear (e.g., plastic transformation [Friston et al., 1991bI with some interesting developments using neural nets [Kosugi et al., 19931.”
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Cited by
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888
Statistical parametric maps in functional imaging: A general linear approach
Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J. ‐., Frith, C. D., & Frackowiak, R. S. J. (1994) · Human Brain Mapping · doi:10.1002/hbm.460020402 · Cited by 9,688
Self-citationThe organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304
Ashburner, J., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.018 · Cited by 7,507
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Metadata
- Authors
- Friston, K. J., Ashburner, J., Frith, C. D., Poline, J. ‐., Heather, J. D., & Frackowiak, R. S. J.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 1995-01
- Volume
- 3
- Issue
- 3
- Pages
- 165-189
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2063237661
- Cited by
- 3,744
- References
- 1
- FWCI
- 109.16
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Spatial registration and normalization of images. https://app.cochat.ai/papers/10.1002/hbm.460030303
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- Friston, K. J., Ashburner, J., Frith, C. D., Poline, J. ‐., Heather, J. D., & Frackowiak, R. S. J. (1995). Spatial registration and normalization of images. Human Brain Mapping. https://doi.org/10.1002/hbm.460030303
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