The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Crossing fibres in tract-based spatial statistics
Abstract
Voxelwise analysis of white matter properties typically relies on scalar measurements derived, for example, from a tensor model fit to diffusion MRI data. These are spatially matched across subjects prior to statistical modelling. In this paper, we show why and how this can be improved through the use of directionally dependent measurements. In the case where different orientations relate to different fibre populations (e.g., in the presence of crossing fibres), distinguishing and matching those populations of fibres across subjects are important prior to any statistical modelling. It allows one to compare measurements that are related to the same fibres across subjects. We show how this framework applies to the parameters of a crossing fibre model and discuss its implications for voxelwise analysis of the white matter.
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“The DTI model cannot differentiate these components or even crossing fibers (Tuch et al., 2002; Jbabdi et al., 2010), which are estimated to occur in up to 90% of WM voxels at the typical dMRI resolution (Descoteaux et al., 2009; Jeurissen et al., 2013).”
From Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3 (2019) · cites this paper as Jbabdi et al., 2010
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Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
Smith, S. M., Jenkinson, M., Johansen‐Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., Watkins, K. E., Ciccarelli, O., Cader, M. Z., Matthews, P. M., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.024 · Cited by 6,598
Self-citationThe basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,628
Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo
Basser, P. J., Mattiello, J., & Bihan, D. L. (1994) · Journal of Magnetic Resonance Series B · doi:10.1006/jmrb.1994.1037 · Cited by 3,656
Level Set Methods and Fast Marching Methods
Sethian, J. A. (1999) · Medical Entomology and Zoology · Cited by 3,616
Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?
Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S., & Woolrich, M. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.018 · Cited by 3,471
Self-citationSong, S.-K., Sun, S.-W., Ju, W.-K., Lin, S.-J., Cross, A. H., & Neufeld, A. H. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.07.005 · Cited by 1,738
Tournier, J.-D., Calamante, F., Gadian, D. G., & Connelly, A. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.037 · Cited by 1,635
Water diffusion changes in wallerian degeneration and their dependence on white matter architecture
Pierpaoli, C., Barnett, A., Pajevic, S., Chen, R., Penix, L., Virta, A., & Basser, P. (2001) · NeuroImage · doi:10.1006/nimg.2001.0765 · Cited by 938
About “axial” and “radial” diffusivities
Wheeler‐Kingshott, C. A. M., & Cercignani, M. (2009) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21965 · Cited by 885
Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain
Assaf, Y., & Basser, P. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.03.042 · Cited by 856
Spatial transformations of diffusion tensor magnetic resonance images
Alexander, D. C., Pierpaoli, C., Basser, P. J., & Gee, J. C. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.963816 · Cited by 610 · cited 1×
“In particular, and as noted by Alexander et al. (2001), the warp fields contain an implicit local rotation that needs to be estimated and applied locally to each vector after registration.”
Tuch, D. S., Salat, D. H., Wisco, J. J., Zaleta, A. K., Hevelone, N. D., & Rosas, H. D. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407259102 · Cited by 364
Parker, G. J. M., & Alexander, D. C. (2005) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2005.1639 · Cited by 339
Tomassini, V., Jbabdi, S., Klein, J. C., Behrens, T. E. J., Pozzilli, C., Matthews, P. M., Rushworth, M. F. S., & Johansen‐Berg, H. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.2144-07.2007 · Cited by 334
Self-citationThe “wet mind”: Water and functional neuroimaging
Bihan, D. L. (2007) · Physics in Medicine and Biology · doi:10.1088/0031-9155/52/7/r02 · Cited by 320
Level Set Methods and Fast Marching Methods
Suba�i�, M. (2003) · Journal of Computing and Information Technology · doi:10.2498/cit.2003.01.07 · Cited by 295
Age‐Related Changes in Prefrontal White Matter Measured by Diffusion Tensor Imaging
SALAT, D. H., TUCH, D. S., HEVELONE, N. D., FISCHL, B., CORKIN, S., ROSAS, H. D., & DALE, A. M. (2005) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1340.009 · Cited by 292
Orthogonal tensor invariants and the analysis of diffusion tensor magnetic resonance images
Ennis, D. B., & Kindlmann, G. (2006) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20741 · Cited by 276
Spatial normalization of diffusion tensor MRI using multiple channels
Park, H. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.08.008 · Cited by 199
Group analysis of DTI fiber tract statistics with application to neurodevelopment
Goodlett, C., Fletcher, P. T., Gilmore, J. H., & Gerig, G. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.10.060 · Cited by 187
Tract-based morphometry for white matter group analysis
O'Donnell, L. J., Westin, C.-F., & Golby, A. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.023 · Cited by 186
Structure-specific statistical mapping of white matter tracts
Yushkevich, P. A., Zhang, H. G., Simon, T. J., & Gee, J. C. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.01.013 · Cited by 167
Inference of multiple fiber orientations in high angular resolution diffusion imaging
Hosey, T. P., Williams, G. B., & Ansorge, R. E. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20723 · Cited by 154
Active fibers: Matching deformable tract templates to diffusion tensor images
Eckstein, I., Shattuck, D. W., Stein, J. L., McMahon, K. L., de Zubicaray, G. I., Wright, M. J., Thompson, P. M., & Toga, A. W. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.065 · Cited by 23
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Jeurissen, B., Leemans, A., Tournier, J., Jones, D. K., & Sijbers, J. (2013) · Human Brain Mapping · doi:10.1002/hbm.22099 · Cited by 1,088
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Westlye, L. T., Walhovd, K. B., Dale, A. M., Bjornerud, A., Due-Tonnessen, P., Engvig, A., Grydeland, H., Tamnes, C. K., Ostby, Y., & Fjell, A. M. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp280 · Cited by 765
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Raffelt, D. A., Tournier, J.-D., Smith, R. E., Vaughan, D. N., Jackson, G., Ridgway, G. R., & Connelly, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.029 · Cited by 620
“, 2013), partial volume fraction (Jbabdi et al., 2010), fibre density (Alexander et al.”
BackgroundTractography: Where Do We Go from Here?
Jbabdi, S., & Johansen-Berg, H. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0033 · Cited by 614
Self-citation
Metadata
- Authors
- Jbabdi, S., Behrens, T. E. J., & Smith, S. M.
- Affiliations
- John Radcliffe Hospital (GB)
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-01
- Volume
- 49
- Issue
- 1
- Pages
- 249-256
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1982877110
- Cited by
- 187
- References
- 24
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 6 · 2023: 5 · 2022: 8 · 2021: 12 · 2020: 11 · 2019: 10 · 2018: 14 · 2017: 14 · 2016: 20 · 2015: 15 · 2014: 21 · 2013: 10 · 2012: 10
- FWCI
- 6.79
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Medical Research Council
- Engineering and Physical Sciences Research Council (EP/F05727X/1)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- crossing fibers, tract-based spatial statistics, white matter, diffusion MRI, voxelwise analysis
- MeSH terms
- Adult, Brain, Female, Humans, Image Processing, Computer-Assisted, Male, Models, Neurological, Nerve Fibers, Regression Analysis, Sex Characteristics, Diffusion Magnetic Resonance Imaging, Young Adult
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