Cited by 8Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesAdvanced MRI Techniques and Applications

The DOI matches its Crossref record; the references it cites are not checked yet.

Cross-Subject Comparison of Local Diffusion MRI Parameters

Smith, Stephen M., Kindlmann, Gordon, Jbabdi, Saad·2014·Diffusion MRI

Overview

Integrity signals

Registry

Crossref · 10.1016/b978-0-12-396460-1.00010-x

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

The citation lists haven’t been fetched yet

References 97 · Cited by 8

Research works printed but not linked: 76

  1. Ashburner, 2000, Voxel-based morphometry—the methods, NeuroImage, 11, 805, 10.1006/nimg.2000.0582 · DOI · Paper page
  2. Ashburner, 2001, Why voxel-based morphometry should be used, NeuroImage, 14, 1238, 10.1006/nimg.2001.0961 · DOI · Paper page
  3. Ashburner, 2004, Generative and recognition models for neuroanatomy, NeuroImage, 23, 21, 10.1016/j.neuroimage.2004.04.021 · DOI
  4. Barnea-Goraly, 2003, White matter tract alterations in fragile X syndrome: Preliminary evidence from diffusion tensor imaging, Am. J. Med. Genet. B (Neuropsych. Genet.), 118B, 81, 10.1002/ajmg.b.10035 · DOI
  5. Beckmann, 2004, Probabilistic independent component analysis for functional magnetic resonance imaging, IEEE Trans. on Med. Imaging, 23, 137, 10.1109/TMI.2003.822821 · DOI
  6. Behrens, 2003, Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging, Nat. Neurosci., 6, 750, 10.1038/nn1075 · DOI · Paper page
  7. Behrens, 2007, Probabilistic diffusion tractography with multiple fibre orientations. What can we gain?, NeuroImage, 23, 144, 10.1016/j.neuroimage.2006.09.018 · DOI · Paper page
  8. Bookstein, 2001, “Voxel-based morphometry” should not be used with imperfectly registered images, NeuroImage, 14, 1454, 10.1006/nimg.2001.0770 · DOI
  9. Büchel, 2004, White matter asymmetry in the human brain: A diffusion tensor MRI study, Cerebral Cortex, 14, 945, 10.1093/cercor/bhh055 · DOI
  10. Cader, 2007, Discordant white matter N-acetylasparate and diffusion MRI measures suggest that chronic metabolic dysfunction contributes to axonal pathology in multiple sclerosis, NeuroImage, 36, 19, 10.1016/j.neuroimage.2007.02.036 · DOI
  11. Cercignani, 2001, Mean diffusivity and fractional anisotropy histograms of patients with multiple sclerosis, Am. J. Neuroradiol., 22, 952
  12. Cercignani, 2003, Inter-sequence and inter-imaging unit variability of diffusion tensor MR imaging histogram-derived metrics of the brain in healthy volunteers, Am. J. Neuroradiol., 24, 638
  13. Ciccarelli, 2009, Investigation of white matter pathology in ALS and PLS using tract-based spatial statistics, Human Brain Mapping, 30, 615, 10.1002/hbm.20527 · DOI
  14. Conturo, 1999, Tracking neuronal fiber pathways in the living human brain, Proc. Natl. Acad. Sci. U.S.A., 96, 10422, 10.1073/pnas.96.18.10422 · DOI · Paper page
  15. Corouge, 2006, Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis, Med. Image Anal., 10, 786, 10.1016/j.media.2006.07.003 · DOI · Paper page
  16. Davatzikos, 2004, Why voxel-based morphometric analysis should be used with great caution when characterizing group differences, NeuroImage, 23, 17, 10.1016/j.neuroimage.2004.05.010 · DOI
  17. Douaud, 2009, Schizophrenia delays and alters maturation of the brain in adolescence, Brain, 132, 2437, 10.1093/brain/awp126 · DOI
  18. Durrleman, 2011, Registration, atlas estimation and variability analysis of white matter fiber bundles modeled as currents, NeuroImage, 55, 1073, 10.1016/j.neuroimage.2010.11.056 · DOI
  19. Eberly, 1994, Ridges for image analysis, J. Math. Imag. Vision, 4, 353, 10.1007/BF01262402 · DOI
  20. Eickhoff, 2005, A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data, NeuroImage, 25, 1325, 10.1016/j.neuroimage.2004.12.034 · DOI · Paper page
  21. Ellis, 1999, Diffusion tensor MRI assesses corticospinal tract damage in ALS, Neurology, 53, 1051, 10.1212/WNL.53.5.1051 · DOI
  22. Ennis, 2005, Visualization of tensor fields using superquadric glyphs, Magn. Reson. Med., 53, 169, 10.1002/mrm.20318 · DOI
  23. Eriksson, 2001, Diffusion tensor imaging in patients with epilepsy and malformations of cortical development, Brain, 124, 617, 10.1093/brain/124.3.617 · DOI
  24. Everitt, 1999, Mixture model mapping of brain activation in functional magnetic resonance images, Human Brain Mapping, 7, 1, 10.1002/(SICI)1097-0193(1999)7:1<1::AID-HBM1>3.0.CO;2-H · DOI
  25. Gong, 2005, Asymmetry analysis of cingulum based on scale-invariant parameterization by diffusion tensor imaging, Human Brain Mapping, 24, 92, 10.1002/hbm.20072 · DOI
  26. Good, 2001, A voxel-based morphometric study of ageing in 465 normal adult human brains, NeuroImage, 14, 21, 10.1006/nimg.2001.0786 · DOI · Paper page
  27. Groves, 2012, Benefits of multi-modal fusion analysis on a large-scale dataset: Life-span patterns of inter-subject variability in cortical morphometry and white matter microstructure, NeuroImage, 63, 365, 10.1016/j.neuroimage.2012.06.038 · DOI
  28. Guevara, 2012, Automatic fiber bundle segmentation in massive tractography datasets using a multi-subject bundle atlas, NeuroImage, 61, 1083, 10.1016/j.neuroimage.2012.02.071 · DOI
  29. Guimond, 2000, Average brain models: A convergence study, Comput. Vis. Image Und., 77, 192, 10.1006/cviu.1999.0815 · DOI
  30. Hayasaka, 2004, Nonstationary cluster-size inference with random field and permutation methods, NeuroImage, 22, 676, 10.1016/j.neuroimage.2004.01.041 · DOI
  31. Heiervang, 2006, Between session reproducibility and between subject variability of diffusion MR and tractography measures, NeuroImage, 33, 867, 10.1016/j.neuroimage.2006.07.037 · DOI · Paper page
  32. Jbabdi, 2012, Model-based analysis of multishell diffusion MR data for tractography: How to get over fitting problems, Magn. Reson. Med., 68, 1846, 10.1002/mrm.24204 · DOI · Paper page
  33. Jenkinson, 2001, A global optimisation method for robust affine registration of brain images, Medical Image Analysis, 5, 143, 10.1016/S1361-8415(01)00036-6 · DOI
  34. Jensen, 2005, Diffusional kurtosis imaging: The quantification of non-Gaussian water diffusion by means of magnetic resonance imaging, Magn. Reson. Med., 53, 1432, 10.1002/mrm.20508 · DOI · Paper page
  35. Jones, 2002, Spatial normalisation and averaging of diffusion tensor MRI data sets, NeuroImage, 17, 592, 10.1006/nimg.2002.1148 · DOI
  36. Jones, 2005, The effect of filter size on VBM analyses of DT-MRI data, NeuroImage, 26, 546, 10.1016/j.neuroimage.2005.02.013 · DOI
  37. Jones, 2006, Age effects on diffusion tensor magnetic resonance imaging tractography measures of frontal cortex connections in schizophrenia, Human Brain Mapping, 27, 230, 10.1002/hbm.20179 · DOI
  38. Kindlmann, 2007, Delineating white matter structure in diusion tensor MRI with anisotropy creases, Medical Image Analysis, 11, 492, 10.1016/j.media.2007.07.005 · DOI
  39. Kindlmann, 2007, Diffusion tensor analysis with invariant gradients and rotation tangents, IEEE Trans. on Medical Imaging, 26, 1483, 10.1109/TMI.2007.907277 · DOI
  40. Kindlmann, 2009, Sampling and visualizing creases with scale-space particles, IEEE Trans. Visualization and Computer Graphics, 15, 1415, 10.1109/TVCG.2009.177 · DOI
  41. Kubicki, 2003, Cingulate fasciculus integrity disruption in schizophrenia: A magnetic resonance diffusion tensor imaging study, Biological Psychiatry, 54, 1171, 10.1016/S0006-3223(03)00419-0 · DOI · Paper page
  42. Lee, 2009, A study of diffusion tensor imaging by tissue-specific, smoothing-compensated voxel-based analysis, NeuroImage, 44, 870, 10.1016/j.neuroimage.2008.09.041 · DOI
  43. Li, 2010, A hybrid approach to automatic clustering of white matter fibers, NeuroImage, 49, 1249, 10.1016/j.neuroimage.2009.08.017 · DOI
  44. Li, 2012, Independent component analysis of DTI reveals multivariate microstructural correlations of white matter in the human brain, Human Brain Mapping, 33, 1431, 10.1002/hbm.21292 · DOI
  45. Lilliefors, 1967, On the Kolmogorov-Smirnov test for normality with mean and variance unknown, Journal of the American Statistical Association, 62, 399, 10.1080/01621459.1967.10482916 · DOI · Paper page
  46. Lim, 2002, Neuropsychiatric applications of DTI—a review, NMR Biomed., 15, 587, 10.1002/nbm.789 · DOI
  47. Lin, 2006, Quantitative analysis along the pyramidal tract by length-normalized parameterization based on diffusion tensor tractography: Application to patients with relapsing neuromyelitis optica, NeuroImage, 33, 154, 10.1016/j.neuroimage.2006.03.055 · DOI
  48. Miller, 2011, Diffusion imaging of whole, post-mortem human brains on a clinical MRI scanner, NeuroImage, 57, 167, 10.1016/j.neuroimage.2011.03.070 · DOI
  49. Moseley, 2002, Diffusion tensor imaging and aging -A review, NMR Biomed., 15, 553, 10.1002/nbm.785 · DOI · Paper page
  50. Nichols, 2002, Nonparametric permutation tests for functional neuroimaging: A primer with examples, Hum. Brain Mapp., 15, 1, 10.1002/hbm.1058 · DOI · Paper page
  51. O’Donnell, 2009, Tract-based morphometry for white matter group analysis, NeuroImage, 45, 832, 10.1016/j.neuroimage.2008.12.023 · DOI · Paper page
  52. Pagani, 2005, A method for obtaining tract-specfic diffusion tensor MRI measurements in the presence of disease: Application to patients with clinically isolated syndromes suggestive of multiple sclerosis, NeuroImage, 26, 258, 10.1016/j.neuroimage.2005.01.008 · DOI
  53. Pajevic, 1999, Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: Application to white matter fiber tract mapping in the human brain, Magn. Reson. Med., 42, 526, 10.1002/(SICI)1522-2594(199909)42:3<526::AID-MRM15>3.0.CO;2-J · DOI
  54. Park, 2003, Spatial normalization of diffusion tensor MRI using multiple channels, NeuroImage, 20, 1995, 10.1016/j.neuroimage.2003.08.008 · DOI
  55. Park, 2004, White matter hemisphere asymmetries in healthy subjects and in schizophrenia: a diffusion tensor MRI study, NeuroImage, 23, 213, 10.1016/j.neuroimage.2004.04.036 · DOI · Paper page
  56. Pasternak, 2009, Free water elimination and mapping from diffusion MRI, Magn. Reson. Med., 62, 717, 10.1002/mrm.22055 · DOI · Paper page
  57. Pierpaoli, 1996, Toward a quantitive assessment of diffusion anisotropy, Magn. Reson. Med., 36, 893, 10.1002/mrm.1910360612 · DOI
  58. Rueckert, 1999, Nonrigid registration using free-form deformations: Application to breast MR images, IEEE Trans. on Med. Imaging, 18, 712, 10.1109/42.796284 · DOI · Paper page
  59. Rugg-Gunn, 2001, Diffusion tensor imaging of cryptogenic and acquired partial epilepsies, Brain, 124, 627, 10.1093/brain/124.3.627 · DOI
  60. Salimi-Khorshidi, 2011, Adjusting the effect of nonstationarity in cluster-based and TFCE inference, NeuroImage, 54, 2006, 10.1016/j.neuroimage.2010.09.088 · DOI
  61. Simon, 2005, Volumetric, connective, and morphologic changes in the brains of children with chromosome 22q11.2 deletion syndrome: An integrative study, NeuroImage, 25, 169, 10.1016/j.neuroimage.2004.11.018 · DOI
  62. Smith, 2006, Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data, NeuroImage, 31, 1487, 10.1016/j.neuroimage.2006.02.024 · DOI
  63. Smith, 2007, Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics, Nature Protocols, 2, 499, 10.1038/nprot.2007.45 · DOI
  64. Sommer, 2002, Disconnection of speech-relevant brain areas in persistent developmental stuttering, The Lancet, 360, 380, 10.1016/S0140-6736(02)09610-1 · DOI
  65. Toga, 2006, Towards multimodal atlases of the human brain, Nature Rev. Neurosci., 7, 952, 10.1038/nrn2012 · DOI
  66. Tuch, 2004, Q-ball imaging, Magn. Reson. Med., 52, 1358, 10.1002/mrm.20279 · DOI · Paper page
  67. Tuch, 2005, Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention, Proc. Natl. Acad. Sci. USA, 102, 12212, 10.1073/pnas.0407259102 · DOI · Paper page
  68. Wakana, 2007, Reproducibility of quantitative tractography methods applied to cerebral white matter, NeuroImage, 36, 630, 10.1016/j.neuroimage.2007.02.049 · DOI · Paper page
  69. Woolrich, 2005, Mixture models with adaptive spatial regularisation for segmentation with an application to FMRI data, IEEE Trans. Med. Imaging, 24, 1, 10.1109/TMI.2004.836545 · DOI
  70. Worsley, 1992, A three-dimensional statistical analysis for CBF activation studies in human brain, J. Cereb. Blood Flow Metab., 12, 900, 10.1038/jcbfm.1992.127 · DOI · Paper page
  71. Yendiki, 2011, Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy, Frontiers in Neuroinformatics,, 5
  72. Yushkevich, 2008, Structure-specific statistical mapping of white matter tracts, NeuroImage, 41, 448, 10.1016/j.neuroimage.2008.01.013 · DOI
  73. Zhang, 2010, A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features, Med. Image Analysis, 14, 666, 10.1016/j.media.2010.05.002 · DOI
  74. Zhang, 2001, Segmentation of brain MR images through a hidden Markov random field model and the expectation maximization algorithm, IEEE Trans. Med. Imaging, 20, 45, 10.1109/42.906424 · DOI
  75. Zhu, 2010, FRATS: Functional Regression Analysis of DTI Tract Statistics, IEEE Trans. Med. Imaging, 29, 1039, 10.1109/TMI.2010.2040625 · DOI
  76. Zhu, 2011, FADTTS: Functional analysis of diffusion tensor tract statistics, NeuroImage, 56, 1412, 10.1016/j.neuroimage.2011.01.075 · DOI

Metadata

Authors
Smith, S. M., Kindlmann, G., & Jbabdi, S.
Affiliations
  • John Radcliffe Hospital (GB)
  • University of Chicago (US)
Venue
Diffusion MRI
Publisher
Elsevier
Published
2014
Pages
209-239
OpenAlex
W2921650321
Cited by
8
References
97
Citations by year
2025: 1 · 2024: 4 · 2023: 1 · 2022: 1 · 2021: 1
FWCI
0.00
Type
book chapter
Language
en
Open access
closed
Locations
Elsevier eBooks (publishedVersion)
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
diffusion MRI, fractional anisotropy, anatomical correspondence, white matter tracts, brain connectivity, tractography

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Cross-Subject Comparison of Local Diffusion MRI Parameters. https://app.cochat.ai/papers/10.1016/b978-0-12-396460-1.00010-x
The paper
Smith, S. M., Kindlmann, G., & Jbabdi, S. (2014). Cross-Subject Comparison of Local Diffusion MRI Parameters. Diffusion MRI. https://doi.org/10.1016/b978-0-12-396460-1.00010-x