The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution
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Citations
Cites
Tuch, D. S. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20279 · Cited by 1,880
High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity
Tuch, D. S., Reese, T. G., Wiegell, M. R., Makris, N., Belliveau, J. W., & Wedeen, V. J. (2002) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10268 · Cited by 1,548 · cited 2×
“Unfortunately, the diffusion tensor model is not always adequate, particularly in voxels containing contributions from differently oriented fibre bundles (Alexander et al., 2002; Frank, 2002; Tuch et al., 2002; Behrens et al., 2007).”
BackgroundAssaf, Y., Freidlin, R. Z., Rohde, G. K., & Basser, P. J. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20274 · Cited by 519
Cited by
MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation
Tournier, J.-D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C.-H., & Connelly, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116137 · Cited by 2,974
Self-citationWhite matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI
Jones, D. K., Knösche, T. R., & Turner, R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.081 · Cited by 2,402
Denoising of diffusion MRI using random matrix theory
Veraart, J., Novikov, D. S., Christiaens, D., Ades-aron, B., Sijbers, J., & Fieremans, E. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.016 · Cited by 1,905
Jeurissen, B., Tournier, J.-D., Dhollander, T., Connelly, A., & Sijbers, J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.061 · Cited by 1,454
Self-citationDipy, a library for the analysis of diffusion MRI data
Garyfallidis, E., Brett, M., Amirbekian, B., Rokem, A., van der Walt, S., Descoteaux, M., Nimmo-Smith, I., & Contributors, D. (2014) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2014.00008 · Cited by 1,371
“The method is inspired by CSD (Tournier et al., 2007) with the main difference that the CSD is applied directly to the initial signal and the SDT directly to the ODF (Descoteaux, 2008; Descoteaux et al., 2009).”
BackgroundMethodInfluential
Metadata
- Authors
- Tournier, J.-D., Calamante, F., & Connelly, A.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2007-05
- Volume
- 35
- Issue
- 4
- Pages
- 1459-1472
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2001611992
- Cited by
- 2,188
- References
- 3
- FWCI
- 20.52
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution. https://app.cochat.ai/papers/10.1016/j.neuroimage.2007.02.016
- The paper
- Tournier, J.-D., Calamante, F., & Connelly, A. (2007). Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution. NeuroImage. https://doi.org/10.1016/j.neuroimage.2007.02.016
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.
