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Cited by 664

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

“Voxel-Based Morphometry” Should Not Be Used with Imperfectly Registered Images

Bookstein, Fred L.·2001·NeuroImage

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Registry

Crossref · 10.1006/nimg.2001.0770

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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Citations

Cites

Show all 3 references

Research works printed but not linked: 6

  1. Andreasen, 1994, Thalamic abnormalities in schizophrenia visualized through magnetic resonance image averaging, Science, 266, 294, 10.1126/science.7939669 · DOI · Paper page
  2. Ashburner, 1997, Incorporating prior knowledge into image registration, NeuroImage, 6, 344, 10.1006/nimg.1997.0299 · DOI · Paper page
  3. Ashburner, 1999, Nonlinear spatial normalization using basis functions, Hum. Brain Mapp., 7, 254, 10.1002/(SICI)1097-0193(1999)7:4<254::AID-HBM4>3.0.CO;2-G · DOI
  4. Bullmore, 1999, Global, voxel, and cluster tests, by theory and permutation for a difference between two groups of structural MR images of the brain, IEEE Trans. Med. Imag., 18, 32, 10.1109/42.750253 · DOI · Paper page
  5. Stuart, A., and Ord, K.1994. Kendall's Advanced Theory of Statistics, 6th ed., Vol. 1: Distribution Theory. Halsted Press, New York.
  6. Worsley, 1999, Detecting changes in nonisotropic images, Hum. Brain Mapp., 8, 98, 10.1002/(SICI)1097-0193(1999)8:2/3<98::AID-HBM5>3.0.CO;2-F · doi:10.1002/(sici)1097-0193(1999)8:2/3<98::aid-hbm5>3.0.co;2-f

Cited by

Metadata

Authors
Bookstein, F. L.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2001-12
Volume
14
Issue
6
Pages
1454-1462
ISSN
1053-8119 (ISSN-L)
OpenAlex
W2001469430
Cited by
664
References
3
FWCI
24.14
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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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.