Cited by 1,548Advanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and ApplicationsFunctional Brain Connectivity Studies

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity

Tuch, David S., Reese, Timothy G., Wiegell, Mette R., Makris, Nikos, Belliveau, John W., Wedeen, Van J.·2002·Magnetic Resonance in Medicine

DOI 10.1002/mrm.10268

Open this paper in CoChat — free account

Abstract

Magnetic resonance (MR) diffusion tensor imaging (DTI) can resolve the white matter fiber orientation within a voxel provided that the fibers are strongly aligned. However, a given voxel may contain a distribution of fiber orientations due to, for example, intravoxel fiber crossing. The present study sought to test whether a geodesic, high b-value diffusion gradient sampling scheme could resolve multiple fiber orientations within a single voxel. In regions of fiber crossing the diffusion signal exhibited multiple local maxima/minima as a function of diffusion gradient orientation, indicating the presence of multiple intravoxel fiber orientations. The multimodality of the observed diffusion signal precluded the standard tensor reconstruction, so instead the diffusion signal was modeled as arising from a discrete mixture of Gaussian diffusion processes in slow exchange, and the underlying mixture of tensors was solved for using a gradient descent scheme. The multitensor reconstruction resolved multiple intravoxel fiber populations corresponding to known fiber anatomy. Ma

Integrity signals

Registry

Crossref · 10.1002/mrm.10268

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

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

Claims the paper makes

This paper’s full text isn’t openly available, 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?

Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
MR diffusion tensor spectroscopy and imaging
Basser, P. J., Mattiello, J., & LeBihan, D. (1994) · Biophysical Journal · doi:10.1016/s0006-3495(94)80775-1 · Cited by 5,970
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
Statistical Analysis of Finite Mixture Distributions.
Lindsay, B. G., Titterington, D. M., Smith, A. F. M., & Makov, U. E. (1987) · Journal of the American Statistical Association · doi:10.2307/2289504 · Cited by 2,906
Diffusion tensor MR imaging of the human brain
Pierpaoli, C., Jezzard, P., Basser, P. J., Barnett, A., & Di Chiro, G. (1996) · Radiology · doi:10.1148/radiology.201.3.8939209 · Cited by 2,664
Statistical Analysis of Finite Mixture Distributions.
Newton, J., Titterington, D. M., Smith, A. F. M., & Makov, U. E. (1986) · Biometrics · doi:10.2307/2531224 · Cited by 1,986
Tracking neuronal fiber pathways in the living human brain
Conturo, T. E., Lori, N. F., Cull, T. S., Akbudak, E., Snyder, A. Z., Shimony, J. S., McKinstry, R. C., Burton, H., & Raichle, M. E. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.18.10422 · Cited by 1,774
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
Analysis of partial volume effects in diffusion‐tensor MRI
Alexander, A. L., Hasan, K. M., Lazar, M., Tsuruda, J. S., & Parker, D. L. (2001) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1105 · Cited by 695
On standardizing the MR image intensity scale
Ny�l, L. G., & Udupa, J. K. (1999) · Magnetic Resonance in Medicine · doi:10.1002/(sici)1522-2594(199912)42:6 · Cited by 575

Show all 27 references

Research works printed but not linked: 1

ReeseTG WeisskoffRM WedeenVJ.Diffusion NMR facilitated by a refocused eddy‐current EPI pulse sequence. In: Proceedings of the 6th Annual Meeting of ISMRM Sydney Australia 1998. p663.

Sorted by citations

Items 801–900 of 1,001

Quantitative quality assurance in a multicenter HARDI clinical trial at 3 T
Zhou, X., Sakaie, K., Debbins, J. P., KIRSCH, J. E., Tatsuoka, C. M., Fox, R. J., & Lowe, M. J. (2016) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2016.08.022 · Cited by 14
“A secondary outcome of this trial is change in diffusivity measurements as measured by high angular resolution diffusion imaging (HARDI) [2].”
Method
The Lamellar Structure of the Brain Fiber Pathways
Galinsky, V. L., & Frank, L. R. (2016) · Neural Computation · doi:10.1162/neco_a_00896 · Cited by 14
“It is important to point out at this juncture that a key result of our analysis leading to the GO-ESP method (Galinsky & Frank, 2015) is that the generally accepted view that the diffusion PDF is the fundamental quantity in diffusion MRI methods is predicated on the assumption that voxel diffusion profiles are indepen…”
MethodInfluential
Retrospective correction of bias in diffusion tensor imaging arising from coil combination mode
Sakaie, K., & Lowe, M. J. (2016) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2016.12.004 · Cited by 14
“A high angular resolution diffusion imaging [4] acquisition was acquired on each subject (51 2mm-thick axial slices with 256mm ×256 mm FOV, 128 × 128 matrix, twice-refocused spin echo twice-refocused spin echo [5] with TE = 92 msec, TR = 7800 msec, 71 noncollinear gradient directions with b = 1000 sec/mm2 and 8 b = 0…”
Method
Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection
Xiao, Y., Eikenes, L., Reinertsen, I., & Rivaz, H. J. (2018) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-017-1699-x · Cited by 14
“Although it is true that more advanced imaging techniques, such as high angular resolution diffusion-weighted imaging (HARDI) [51] and its variants, can further improve the accuracy of fiber tracking, they are still rarely seen in the clinic, primarily due to time and hardware constraints.”
Background
Acute MR-Guided High-Intensity Focused Ultrasound Lesion Assessment Using Diffusion-Weighted Imaging and Histological Analysis
Walker, M. R., zhong, J., Waspe, A. C., Looi, T., Piorkowska, K., Hawkins, C. E., Drake, J. M., & Hodaie, M. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.01069 · Cited by 14
Imaging the aging brain: study design and baseline findings of the SENIOR cohort
Haeger, A., Mangin, J., Vignaud, A., Poupon, C., Grigis, A., Boumezbeur, F., Frouin, V., Deverre, J.-R., Sarazin, M., Hertz‐Pannier, L., et al. (2020) · Alzheimer s Research & Therapy · doi:10.1186/s13195-020-00642-1 · Cited by 21
Analytical and fast Fiber Orientation Distribution reconstruction in 3D-Polarized Light Imaging
Alimi, A., Deslauriers‐Gauthier, S., Matuschke, F., Müller, A. F., Muenzing, S. E. A., Axer, M., & Rachid Deriche, B. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101760 · Cited by 14
“With a millimeter resolution, diffusion Magnetic Resonance Imaging (MRI) (35, 11, 55, 28, 23, 50, 36) is the only in vivo and non invasive imaging technique able to assess the structural architecture of human fibrous organs such as the brain and the heart and to infer their respective connectivity (41, 18, 27, 26).”
Background
Efficient and accurate EAP imaging from multi-shell dMRI with micro-structure adaptive convolution kernels and dual Fourier Integral Transforms (MiSFIT)
Tristán‐Vega, A., & Aja‐Fernández, S. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117616 · Cited by 14
Distribution and orientation of nerve fibers and myelin assembly in a brain section retrieved by small-angle neutron scattering
Maiti, S., Frielinghaus, H., Gräßel, D., Dulle, M., Axer, M., & Förster, S. (2021) · Scientific Reports · doi:10.1038/s41598-021-92995-2 · Cited by 13
Comparison of Diffusion Signal Models for Fiber Tractography in Eloquent Glioma Surgery–Determination of Accuracy Under Awake Craniotomy Conditions
Becker, D., Neher, P., Jungk, C., Jesser, J., Pflüger, I., Brinster, R., Bendszus, M., Bruckner, T. M., Maier-Hein, K. H., Scherer, M., et al. (2021) · World Neurosurgery · doi:10.1016/j.wneu.2021.11.006 · Cited by 14
Repetitive Transcranial Magnetic Stimulation of the Contralesional Dorsal Premotor Cortex for Upper Extremity Motor Improvement in Severe Stroke: Study Protocol for a Pilot Randomized Clinical Trial
Li, X., Lin, Y., Cunningham, D. A., Wolf, S. L., Sakaie, K., Conforto, A. B., Machado, A. G., Mohan, A., O’Laughlin, K., Wang, X., et al. (2022) · Cerebrovascular Diseases · doi:10.1159/000521514 · Cited by 14
Evaluating Structural Connectomics in Relation to Different Q-space Sampling Techniques
Rodrigues, P., Prats‐Galino, A., Gallardo‐Pujol, D., Villoslada, P., Falcón, C., & Prčkovska, V. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40811-3_84 · Cited by 14
“Therefore, more complex acquisitions models were developed, known as High Angular Resolution Diffusion Imaging (HARDI) [5], with denser q-space sampling on a spherical shell.”
Method
Diffusion tensor imaging of white matter pathology in the mouse brain
Zhang, J. (2010) · Imaging in Medicine · doi:10.2217/iim.10.60 · Cited by 16
Development of the transcallosal motor fiber from the corticospinal tract in the human brain: diffusion tensor imaging study
Kwon, H. G., Son, S. M., & Jang, S. H. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00153 · Cited by 14
“However, several limitations of this study should be considered (Wiegell et al., 2000; Tuch et al., 2002; Lee et al., 2005; Parker and Alexander, 2005; Yamada, 2009; Yamada et al., 2009).”
Background
Finsler Streamline Tracking with Single Tensor Orientation Distribution Function for High Angular Resolution Diffusion Imaging
Astola, L., Jalba, A. C., Balmashnova, E. E., & Florack, L. M. J. (2011) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-011-0264-4 · Cited by 14
“The tensors in the crossing area are generated using the Gaussian mixture model [37] assuming signal with bvalue 1000 s/m2.”
Q-ball imaging models: comparison between high and low angular resolution diffusion-weighted MRI protocols for investigation of brain white matter integrity
Caiazzo, G., Trojsi, F., Cirillo, M., Tedeschi, G., & Esposito, F. (2015) · Neuroradiology · doi:10.1007/s00234-015-1616-3 · Cited by 14
“In fact, the medial portion of SLF may be reconstructed only by a two-fiber approach, resulting invisible with a single-fiber approach [20].”
Background
Recent advancement in the challenges to connectomics
Ohno, N., Katoh, M., Saitoh, Y., & Saitoh, S. (2015) · Microscopy · doi:10.1093/jmicro/dfv371 · Cited by 15
Numerical Schemes for Linear and Non-Linear Enhancement of DW-MRI
Creusen, E., Duits, R., Vilanova, A., & Florack, L. M. J. (2013) · Numerical Mathematics Theory Methods and Applications · doi:10.4208/nmtma.2013.mssvm08 · Cited by 14
Diffusion Tensor Imaging Evaluation of Neural Network Development in Patients Undergoing Therapeutic Repetitive Transcranial Magnetic Stimulation following Stroke
Yamada, N., Ueda, R., Kakuda, W., Momosaki, R., Kondo, T., Hada, T., Sasaki, N., Hara, T., Senoo, A., & Abo, M. (2018) · Neural Plasticity · doi:10.1155/2018/3901016 · Cited by 14
“Second, previous reports have used GFA on high-angular-resolution-diffusion imaging data with 200+ directions [5, 23, 35].”
Method
Investigation of Neurodegenerative Processes in Amyotrophic Lateral Sclerosis Using White Matter Fiber Density
Stämpfli, P., Sommer, S., Czell, D., Kozerke, S., Neuwirth, C., Weber, M., Sartoretti‐Schefer, S., Seifritz, E., Gutzeit, A., & Reischauer, C. (2018) · Clinical Neuroradiology · doi:10.1007/s00062-018-0670-8 · Cited by 15
Simultaneous and inherent correction of B0 and eddy-current induced distortions in high-resolution diffusion MRI using reversed polarity gradients and multiplexed sensitivity encoding (RPG-MUSE)
Bruce, I. P., Petty, C., & Song, A. W. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.09.055 · Cited by 14
“Over the past two decades, diffusion MRI (dMRI) and diffusion tensor imaging (DTI) (Mori et al., 1999; Tuch et al., 2002; LeBihan et al., 1986; Basser et al., 1994; Pierpaoli et al., 1996) have been commonly used to investigate neuronal microstructures in the brain and map brain connectivity.”
Review: Using diffusion-weighted magnetic resonance imaging techniques to explore the microstructure and connectivity of subcortical white matter tracts in the human auditory system.
Zanin, J., Dhollander, T., Farquharson, S., Rance, G., Connelly, A., & Nayagam, B. (2019) · Hearing Research · doi:10.1016/j.heares.2019.02.014 · Cited by 10
Precommissural and postcommissural fornix microstructure in healthy aging and cognition
Coad, B. M., Craig, E., Louch, R. C., Aggleton, J. P., Vann, S. D., & Metzler‐Baddeley, C. (2020) · Brain and Neuroscience Advances · doi:10.1177/2398212819899316 · Cited by 14
“Whole-brain High Angular Resolution Diffusion Imaging (HARDI; Tuch et al., 2002) data were collected using a spin-echo echo-planar dual-shell sequence with diffusion encoded along 90 isotropically distributed directions (30 directions at b-value = 1200 s/mm 2 , 60 directions at b-value = 2300 s/mm 2 ).”
Method
Recovery of intra-voxel structure from HARD DWI
Chen, Y., Guo, W., Zeng, Q., He, G., Vemuri, B. C., & Liu, Y. (2004) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2004.1398716 · Cited by 14
Plasticity of Interhemispheric Temporal Lobe White Matter Pathways Due to Early Disruption of Corpus Callosum Development in Spina Bifida
Bradley, K., Juranek, J. J., Romanowska-Pawliczek, A. M., Hannay, H. J., Cirino, P. T., Dennis, M., Kramer, L. A., & Fletcher, J. M. (2015) · Brain Connectivity · doi:10.1089/brain.2015.0387 · Cited by 14
“Newer imaging methods such as high angular-resolution diffusion imaging, which uses larger numbers of diffusion directions, may better isolate interhemispheric tracts (Shattuck et al., 2008; Tuch et al., 2002) and allow for more detailed investigations of interhemispheric tract structure, while minimizing partial volu…”
Advances in Neuroimaging
Rodie, M., Forbes, K. P. N., & Muir, K. W. (2014) · Endocrine development · doi:10.1159/000363628 · Cited by 14
Diffusion Tensor Imaging (DTI)
Mori, S., & Zhang, J. (2009) · Elsevier eBooks · doi:10.1016/b978-008045046-9.00315-6 · Cited by 14
A novel framework for in-vivo diffusion tensor distribution MRI of the human brain
Magdoom, K. N., Avram, A. V., Sarlls, J. E., Gasbarra, D., & Basser, P. J. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120003 · Cited by 13
A Proposed Human Structural Brain Connectivity Matrix in the Center for Morphometric Analysis Harvard-Oxford Atlas Framework: A Historical Perspective and Future Direction for Enhancing the Precision of Human Structural Connectivity with a Novel Neuroanatomical Typology
Makris, N., Rushmore, J., Kaiser, J. R., Albaugh, M. D., Kubicki, M. R., Yogesh Rathi, A., Zhang, F., O’Donnell, L. J., Yeterian, E. H., Caviness, V. S., et al. (2023) · Developmental Neuroscience · doi:10.1159/000530358 · Cited by 14
“…of brain lesions on remote brain regions connected with the lesioned area, validating DTI and high angular resolution diffusion imaging (HARDI) data [163], as well as aiding a multitude of functional and metabolic brain investigations where anatomic connections are relevant (see, e.g., [155]).”
Self-citation
A Riemannian scalar measure for diffusion tensor images
Astola, L., Fuster, A., & Florack, L. M. J. (2010) · Pattern Recognition · doi:10.1016/j.patcog.2010.09.009 · Cited by 13
Characterizing white matter health and organization in atherosclerotic vascular disease: A diffusion tensor imaging study
Bijanki, K. R., Arndt, S. V., Magnotta, V. A., Nopoulos, P., Paradiso, S., Matsui, J., Johnson, H. J., & Moser, D. J. (2013) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2013.07.011 · Cited by 13
A survey of current trends in diffusion MRI for structural brain connectivity
Ghosh, A., & Rachid Deriche, B. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/1/011001 · Cited by 13
“The multi-tensor formulation proposed in [135] assumed slow or no exchange between the various compartments and”
Background
VRfRNet: Volumetric ROI fODF reconstruction network for estimation of multi-tissue constrained spherical deconvolution with only single shell dMRI
Jha, R. R., Pathak, S., Nath, V., Schneider, W., Kumar, B., Bhavsar, A. V., & Nigam, A. (2022) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2022.03.004 · Cited by 13
Clustering method for estimating principal diffusion directions
Nazem‐Zadeh, M., Jafari‐Khouzani, K., Davoodi‐Bojd, E., Jiang, Q., & Hamid Soltanian-zadeh, A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.056 · Cited by 13
“To address the time complexity, high angular resolution diffusion imaging (HARDI) and orientation distribution function (ODF) have been introduced as alternatives to DSI and diffusion PDF, respectively (Tuch et al., 2002).”
Method
Advanced Magnetic Resonance Techniques in Neuroimaging: Diffusion, Spectroscopy, and Perfusion
Sood, S., Gupta, A. K., & Tsiouris, A. J. (2010) · Seminars in Roentgenology · doi:10.1053/j.ro.2009.09.008 · Cited by 13
POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data
Tabelow, K., Mohammadi, S., Weiskopf, N., & Polzehl, J. (2014) · Neuroinformatics · doi:10.1007/s12021-014-9228-3 · Cited by 13
“These include HARDI (Frank 2001; Tuch et al. 2002), tensor mixture models (Behrens et al. 2003; Assaf and Basser 2005; Tabelow et al. 2012), higher order tensor approximations (Özarslan and Mareci 2003; Liu et al. 2003; Jensen et al. 2005) and methods to determine the full diffusion propagator…”
Method
Comparing structural and functional graph theory features in the human brain using multimodal MRI
Messé, A., Marrelec, G., Bellec, P., Perlbarg, V., Doyon, J., Pélégrini‐Issac, M., & Benali, H. (2012) · IRBM · doi:10.1016/j.irbm.2012.04.005 · Cited by 14
“In reference [44], the structural network was revealed by using hard angular resolution diffusion imaging, which deals with the complexity of diffusion distribution in some voxels [4,5,54] using new diffusion models and tractography methods [31,54,55].”
Method
Use of High Resolution 3D Diffusion Tensor Imaging to Study Brain White Matter Development in Live Neonatal Rats
Cai, Y., McMurray, M., Oguz, I., Yuan, H., Styner, M., Lin, W.-L., Johns, J., & An, H. (2011) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2011.00054 · Cited by 13
“The high angular resolution diffusion imaging (HARDI) approach has been proposed to overcome this problem by using a large number of diffusion encoding directions at an expense of increasing the imaging acquisition time (Tuch et al., 2002).”
Method
Recent advancements in diffusion MRI for investigating cortical development after preterm birth—potential and pitfalls
Dudink, J., Pieterman, K. J., Leemans, A., Kleinnijenhuis, M., van Walsum, A. M. V. C., & Hoebeek, F. E. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.01066 · Cited by 13
“Advances in dMRI, such as more widespread application of high-angular resolution diffusion imaging (HARDI), enable a more reliable assessment of cortical microstructure (Tuch et al., 2002).”
Fiber direction estimation, smoothing and tracking in diffusion MRI
Wong, R. K. W., Lee, T. C. M., Paul, D., Peng, J., & Initiative, A. D. N. (2016) · The Annals of Applied Statistics · doi:10.1214/15-aoas880 · Cited by 13
“methods often require high angular resolution diffusion imaging (HARDI) (Tuch et al., 2002; Hosey, Williams and Ansorge, 2005) where a large number of gradients is sampled.”
Influential
Improved fidelity of brain microstructure mapping from single-shell diffusion MRI
Taquet, M., Scherrer, B., Boumal, N., Peters, J. M., Macq, B. M. M., & Warfield, S. K. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.10.004 · Cited by 13
“In this section, we optimize the parameters for the estimation and we compare our approach with the results obtained with (i) no prior, (ii) a spatial prior only, (iii) a fixed response function as proposed in the literature (Tuch et al., 2002) and (iv) by simply using the population mode without leveraging data (this…”
BackgroundMethodResultInfluential
Longitudinal diffusion tensor imaging of the rat brain after hexachlorophene exposure
Ramu, J., Konak, T., Paule, M. G., Hanig, J. P., & Liachenko, S. M. (2016) · NeuroToxicology · doi:10.1016/j.neuro.2016.08.011 · Cited by 13
“…clearly capture lower-trending DTI scalars, our analyses might also benefit from the use of advanced DTI methodologies such as q-ball imaging (Tuch et al., 2002; Tuch, 2004; Wedeen et al., 2008) and probabilistic fiber tracking (Mori and van Zijl, 2002; Descoteaux et al., 2009) that can…”
Method
Spatial Transformations of High Angular Resolution Diffusion Imaging Data in Q-space
Dhollander, T., Hecke, W. V., Maes, F., Sunaert, S. G., & Suetens, P. (2010) · Lirias · Cited by 13
Age‐related changes in fiber tracts in healthy adult brains: A generalized q‐sampling and connectometry study
Liu, X., Gao, X., Zhang, L., Yuan, Z., Zhang, C., Lu, W., Cui, D., Zheng, F., Qiu, J., & Xie, J. (2018) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.25949 · Cited by 13
“Accordingly, high angular resolution diffusion imaging (HARDI) data have been proposed to arrange the diffusion gradient directions on a spherical shell (or multiple shells) in the diffusion space.(13) Generalized qsampling imaging (GQI) is one model-free method for reconstructing HARDI data.”
Background
Implementation of clinical tractography for pre-surgical planning of space occupying lesions: An investigation of common acquisition and post-processing methods compared to dissection studies
Ashmore, J., Pemberton, H., Crum, W. R., Jarosz, J., & Barker, G. J. (2020) · PLoS ONE · doi:10.1371/journal.pone.0231440 · Cited by 13
Time-dependent diffusion MRI probes cerebellar microstructural alterations in a mouse model of Down syndrome
Wu, D., Zhang, Y., Cheng, B., Mori, S., Reeves, R. H., & Gao, F. (2021) · Brain Communications · doi:10.1093/braincomms/fcab062 · Cited by 12
“based on diffusion tensor imaging (DTI)(4) or high angularresolution diffusion imaging.(5) Recently, the diffusiontime (td)-dependent dMRI technique has demonstrated unique advantages in depicting tissue microstructural information beyond the directional information.”
Background
Microstructural Tissue Changes in a Rat Model of Mild Traumatic Brain Injury
Chary, K., Narvaez, O., Salo, R., Molina, I. S. M., Tohka, J., Aggarwal, M., Gröhn, O., & Sierra, A. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.746214 · Cited by 12
“Recently, the introduction of more advanced techniques, such as high-angular-resolution diffusion imaging (HARDI) acquisitions (Tuch et al., 2002) in combination with higher-order diffusion modeling tools, such as constrained spherical deconvolution (CSD; Tournier et al.”
Background
The impact of levamisole and alcohol on white matter microstructure in adult chronic cocaine users
Michels, L., Moisa, M., Stämpfli, P., Hirsiger, S., Baumgartner, M. R., Surbeck, W., Seifritz, E., & Quednow, B. B. (2022) · Addiction Biology · doi:10.1111/adb.13149 · Cited by 13
Diffusion Tensor Imaging and Its Application to Traumatic Brain Injury: Basic Principles and Recent Advances
Yeh, P., Oakes, T. R., & Riedy, G. P. (2012) · Open Journal of Medical Imaging · doi:10.4236/ojmi.2012.24025 · Cited by 13
“Both Q-space imaging (spin propagator) and ADC mixture models with FOD commonly use a larger b-value than DT-MRI (b = 1000 s/mm(2) to b = 3000 s/mm(2)) to achieve sharper fiber peaks [146,147].”
MethodInfluential
A Note on the Validity of Statistical Bootstrapping for Estimating the Uncertainty of Tensor Parameters in Diffusion Tensor Images
Yuan, Y., Hongtu Zhu, B., Ibrahim, J. G., Lin, W., & Peterson, B. S. (2008) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.926069 · Cited by 13
Fiber Tractography in Diffusion Tensor Magnetic Resonance Imaging: A Survey and Beyond
Zhang, J., Ji, H., Ning, K., & Cao, N. (2005) · Cited by 13
A statistical framework for the classification of tensor morphologies in diffusion tensor images
Hongtu Zhu, B., Xu, D., Raz, A., Hao, X., Heping Zhang, D., Kangarlu, A., Bansal, R., & Peterson, B. S. (2006) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2006.01.004 · Cited by 13
“Evaluating the test statistics assuming the presence of fiber crossings— We further examined the performance of the three test statistics when modeling the presence of multiple fibers in a single voxel (as will occur when multiple fibers cross within the brain) [34–37], a situation in which the single DT model for Eq.”
Method
A Comparison of Methods for Recovering Intra-voxel White Matter Fiber Architecture from Clinical Diffusion Imaging Scans
Ramírez-Manzanares, A., Cook, P. A., & Gee, J. C. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-85988-8_37 · Cited by 13
“MDT [5].”
MethodInfluential
Correction: Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy
Yeh, F.-C. F., Verstynen, T., Wang, Y., Fernandez-Miranda, J. C., & Tseng, W. I. (2014) · PLoS ONE · doi:10.1371/annotation/0f3b12de-8b8b-4dda-9ff4-835b8631e1dc · Cited by 14
Effects of Alzheimer’s and Vascular Pathologies on Structural Connectivity in Early- and Late-Onset Alzheimer’s Disease
Lee, W. J., Yoon, C. W., Kim, S.-W., Jeong, H. J., Seo, S., Na, D. L., Noh, Y., & Seong, J.-K. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.606600 · Cited by 12
“High-order models such as high angular resolution diffusion tensor (HARDI) (Tuch et al., 2002) and diffusion spectrum imaging (DSI) (Wedeen et al., 2005) can further resolve the crossing fiber issues, but the number of gradient directions we used was low to form enough degrees Frontiers in Neuroscience | www.frontiers…”
Background
Using mesoscopic tract-tracing data to guide the estimation of fiber orientation distributions in the mouse brain from diffusion MRI
Liang, Z., Arefin, T. M., Lee, C. H., & Zhang, J. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119999 · Cited by 12
“Aided by increasingly sophisticated dMRI acquisition schemes and tractography methods (Behrens et al., 2007; Frank, 2001; Mori and van Zijl, 2002; Tournier et al., 2007; Tuch et al., 2002; Wedeen et al., 2012, 2008), dMRI tractography had gained the ability to resolve multiple axonal bundles within a voxel as well as…”
Method
Bayesian Rician Regression for Neuroimaging
Wegmann, B., Eklund, A., & Villani, M. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00586 · Cited by 11
“Using a larger b-value enables more advanced diffusion models, e.g., through HARDI (Tuch et al., 2002; Descoteaux et al., 2008; Gupta and Awate, 2017), which for example can be used to properly account for multiple fiber orientations in a single voxel.”
A Simplified Crossing Fiber Model in Diffusion Weighted Imaging
Yang, S., Ghosh, K., Sakaie, K., Sahoo, S. S., Carr, S. J. A., & Tatsuoka, C. M. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00492 · Cited by 12
“In order to handle the more complex situation of multiple crossing fibers within a voxel, a number of alternative models have been suggested, such as multiple tensor fitting (Tuch et al., 2002), Ball-and-Stick model (Behrens et al.”
Method
Characterizing White Matter Tract Organization in Polymicrogyria and Lissencephaly: A Multifiber Diffusion MRI Modeling and Tractography Study
Arrigoni, F., Peruzzo, D., Mandelstam, S. A., Amorosino, G., Redaelli, D., Romaniello, R., Leventer, R. J., Borgatti, R., Seal, M. L., & Yang, J. Y. (2020) · American Journal of Neuroradiology · doi:10.3174/ajnr.a6646 · Cited by 12
Connection between bilateral temporal regions: Tractography using human connectome data and diffusion spectrum imaging
Wei, P., Mao, Z., Fei, C., Wang, B., Ling, Z., Liang, S., & Yu, X. (2017) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2017.01.012 · Cited by 13
“Furthermore, the DSI and HARDI techniques provide more scan directions and higher angular resolution.”
Background
Theory of visual attention thalamic model for visual short-term memory capacity and top-down control: Evidence from a thalamo-cortical structural connectivity analysis
Menegaux, A., Napiórkowski, N., Neitzel, J., Ruiz‐Rizzo, A. L., Petersen, A., Müller, H. J., Sorg, C., & Finke, K. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.03.052 · Cited by 12
Fiber visualization for preoperative glioma assessment: Tractography versus local connectivity mapping
Schult, T., Hauser, T., Klose, U., Hurth, H. V., & Ehricke, H.-H. (2019) · PLoS ONE · doi:10.1371/journal.pone.0226153 · Cited by 12
“After a directional color-coding scheme [40] is applied, the glyphs depict local anisotropy directions.”
Method
Fast uncertainty quantification of tracer distribution in the brain interstitial fluid with multilevel and quasi Monte Carlo
Croci, M., Vinje, V., & Rognes, M. E. (2020) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.3412 · Cited by 12
“The effective diffusion coefficient of a solute (or tracer) and the velocity field are heterogeneous [41, 45, 66, 77] within the parenchyma and also vary from individual to individual.”
Background
Temporal Dynamics of Brain White Matter Plasticity in Sighted Subjects during Tactile Braille Learning: A Longitudinal Diffusion Tensor Imaging Study
Molendowska, M., Matuszewski, J., Kossowski, B., Bola, Ł., Banaszkiewicz, A., Paplińska, M., Jednoróg, K., Draganski, B., & Marchewka, A. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2242-20.2021 · Cited by 14
“Multiple reviews showed that FA-inferred information about microstructural anisotropy is significantly affected by underlying tissue characteristics, particularly crossing fibers (Tuch et al., 2002; Jbabdi et al., 2010; Vos et al., 2011).”
Background
Investigating secondary white matter degeneration following ischemic stroke by modelling affected fiber tracts
Kancheva, I. K., Buma, F. E., Kwakkel, G., Kancheva, A. K., Ramsey, N. F., & Raemaekers, M. A. H. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.102945 · Cited by 13
“It should be outlined that the tensor model provides a simplified description of the diffusion process compared to the underlying histology (Alexander et al., 2002; Tuch et al., 2002).”
Grundlagen und Technik der diffusionsgewichteten MR‑Bildgebung und der Diffusions‑Tensor‑Bildgebung
Backens, M. (2015) · Der Radiologe · doi:10.1007/s00117-015-0004-7 · Cited by 12
“Beim High-angularresolution-diffusion-imaging(HARDI)Verfahren [27] werden MR-Sequenzen mit hoher Winkelauflösung eingesetzt, die mehr als hundert verschiedene Diffusionsrichtungen messen.”
Background
HARDI Denoising: Variational Regularization of the Spherical Apparent Diffusion Coefficient sADC
Kim, Y., Thompson, P. M., Toga, A. W., Vese, L. A., & Zhan, L. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02498-6_43 · Cited by 12
“[39,40]), diffusion spectrum imaging [43], and q-ball imaging (Tuch et al.”
Background
Combining Functional Studies with Intraoperative MRI in Glioma Surgery
Krivosheya, D., & Prabhu, S. S. (2017) · Neurosurgery Clinics of North America · doi:10.1016/j.nec.2017.05.004 · Cited by 12
Cognition and connectomes in nondementia idiopathic Parkinson’s disease
Colón-Pérez, L. M., Tanner, J. J., Couret, M., Goicochea, S., Mareci, T. H., & Price, C. C. (2017) · Network Neuroscience · doi:10.1162/netn_a_00027 · Cited by 12
“In the current work, we used high angular-resolution diffusion imaging to increase the angular resolution and enable better estimation of the fiber orientation on each voxel (Jian et al., 2007; Tuch et al., 2002).”
Large Deformation Diffeomorphic Metric Mapping of Orientation Distribution Functions
Du, J. T., Goh, A., & Qiu, A. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-22092-0_37 · Cited by 12
“High angular resolution diffusion imaging (HARDI) [25] addresses this well-known limitation of DTI.”
Background
Diffusion Tensor Imaging (DTI)☆
Meoded, A., Poretti, A., Mori, S., & Zhang, J. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-809324-5.02472-x · Cited by 12
Crossing fibers, diffractions and nonhomogeneous magnetic field: correction of artifacts by bipolar gradient pulses
Bar‐Shir, A., & Cohen, Y. (2008) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2008.01.051 · Cited by 12
“For example, Lin et al. [32] have used a 50-μm phantom of crossing fibers to compare orientational uncertainty in DTI and DSI.”
Method
Variational Regularization of Multiple Diffusion Tensor Fields
Pasternak, O., Sochen, N., & Assaf, Y. (2006) · Mathematics and visualization · doi:10.1007/3-540-31272-2_9 · Cited by 12
The Role of the Corpus Callosum (Micro)Structure in Bimanual Coordination: A Literature Review Update
Pauwels, L., & Gooijers, J. (2023) · Journal of Motor Behavior · doi:10.1080/00222895.2023.2221985 · Cited by 11
“, high angular resolution diffusion imaging (Tuch et al., 2002), diffusion MRI with multiple diffusion weightings (multi-shell MR imaging), diffusion weighted STimulated Echo Acquisition Mode (STEAM (De Santis et al.”
Background
Functional network modules overlap and are linked to interindividual connectome differences during human brain development
Lei, T., Liao, X., Liang, X., Sun, L., Xia, M., Xia, Y., Zhao, T., Chen, X., Men, W., Wang, Y., et al. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002653 · Cited by 13
“The use of multiple gradient directions allows more accurate detection of diffusion variations along different directions [83,84], thus resolving multiple fiber orientations within a single voxel and improving the accuracy of tractography.”
Background
The Duke Mouse Brain Atlas: MRI and light sheet microscopy stereotaxic atlas of the mouse brain
Mansour, H., Azrak, R., Cook, J. J., Hornburg, K. J., Qi, Y., Tian, Y., Williams, R. W., Yeh, F.-C., White, L. E., & Johnson, G. A. (2025) · Science Advances · doi:10.1126/sciadv.adq8089 · Cited by 11
“We have used the GQI algorithm because it addresses this challenge through the use of high angular resolution diffusion imaging ( 21 ).”
Elevating tensor rank increases anisotropy in brain areas associated with intra‐voxel orientational heterogeneity (IVOH): a generalised DTI (GDTI) study
Minati, L., Banasik, T., Brzezinski, J., Mandelli, M. L., Bizzi, A., Bruzzone, M. G., Konopka, M., & Jasiński, A. H. (2007) · NMR in Biomedicine · doi:10.1002/nbm.1143 · Cited by 10
“At the millimetre-scale resolution that is typical of present-day studies, intra-voxel orientational heterogeneity (IVOH) is expected to be abundant due to the complex patterns formed by intersecting pathways, such as projection and association fibres, and due to partial volume effects (10).”
BackgroundMethodResultInfluential
Saturn: A software application of tensor utilities for research in neuroimaging
Cárdenes, R., Muñoz‐Moreno, E., Tristán‐Vega, A., & Martín‐Fernández, M. (2009) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2009.09.007 · Cited by 11
“This situation is difficult to solve, but it can be alleviated using a more sophisticated method, such as High Angular Resolution Diffusion Imaging (HARDI) [12], Q-Ball Imaging (QBI) [13] or Q-Space Imaging (QSI) [14].”
Method
New Insights into the Developing Rabbit Brain Using Diffusion Tensor Tractography and Generalized q-Sampling MRI
Lim, S. Y., Tyan, Y., Chao, Y.-P., Nien, F.-Y., & Weng, J.-C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0119932 · Cited by 13
“Based on the data acquired through the HARDI scheme, Tuch proposed q-ball imaging (QBI) to estimate the diffusion ODF of the diffusion propagators using the Funk-Radon transformation [20].”
MethodInfluential
Measure-Valued Variational Models with Applications to Diffusion-Weighted Imaging
Vogt, T., & Lellmann, J. (2018) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-018-0827-8 · Cited by 11
“Consequently, HARDI data is a particularly interesting target for post-processing in terms of denoising and regularization in the sense of contextual processing.”
BackgroundInfluential
Multi-Shell D-MRI Reconstruction via Residual Learning utilizing Encoder-Decoder Network with Attention (MSR-Net)
Jha, R. R., Nigam, A., Bhavsar, A. V., Pathak, S., Schneider, W., & Rathish, K. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9175455 · Cited by 11
The future of neuroimaging and gut-brain axis research for substance use disorders
Colón-Pérez, L. M., Montesinos, J. S., & Monsivais, M. (2022) · Brain Research · doi:10.1016/j.brainres.2022.147835 · Cited by 11
Reading-related Brain Function Restored to Normal After Articulation Training in Patients with Cleft Lip and Palate: An fMRI Study
Sun, L., Zhang, W., Wang, M., Wang, S., Li, Z., Zhao, C., Lin, M., Si, Q., Li, X., Liang, Y., et al. (2022) · Neuroscience Bulletin · doi:10.1007/s12264-022-00918-6 · Cited by 11
“However, if we want to study crossing fiber tracts, acquisition sequences with more directions and higher b values such as high angular resolution diffusion imaging are required [56].”
Background
D-BRAIN: Anatomically Accurate Simulated Diffusion MRI Brain Data
Perrone, D., Jeurissen, B., Aelterman, J., Roine, T., Sijbers, J., Pižurica, A., Leemans, A., & Philips, W. R. (2016) · PLoS ONE · doi:10.1371/journal.pone.0149778 · Cited by 11
“In fact at the voxel level, the WM diffusivity profile is geometrically very complex, which has resulted in the development of many model-based [12] or model-free [13–16] methods.”
Method
Distortion correction for high‐resolution single‐shot EPI DTI using a modified field‐mapping method
Xiong, Y., Li, G., Dai, E., Wang, Y., Zhang, Z., & Guo, H. (2019) · NMR in Biomedicine · doi:10.1002/nbm.4124 · Cited by 11
“Therefore, the proposed method can help high‐resolution SS‐EPI DTI to be fast and reliable in clinical DTI and advanced diffusion techniques such as DSI(13) and HARDI.(14)”
Method
Resolving intravoxel white matter structures in the human brain using regularized regression and clustering
Hart, A., Smith, B., Smith, S. M. C., Sales, E., Hernandez-Camargo, J., Garcia, Y. M., Zhan, F., Griswold, L., Dunkelberger, B., Schwob, M. R., et al. (2019) · Journal Of Big Data · doi:10.1186/s40537-019-0223-2 · Cited by 11
Inferring Microstructural Information of White Matter from Diffusion MRI
Assaf, Y., & Cohen, Y. (2009) · Elsevier eBooks · doi:10.1016/b978-0-12-374709-9.00007-9 · Cited by 11
Structural correlates of the audiological and emotional components of chronic tinnitus
Ahmed, S., Mohan, A., Yoo, H. B., To, W. T., Kovacs, S., Sunaert, S. G., Ridder, D. D., & Vanneste, S. (2021) · Progress in brain research · doi:10.1016/bs.pbr.2021.01.030 · Cited by 11
“The pure tone hearing threshold was determined for eight different frequencies (0.125, 0.250, 0.5, 1, 2, 4, 6, 8kHz) presented unilaterally and randomly via a stepwise procedure (Ulmer et al., 1998).”
MethodInfluential
Widespread effects of dMRI data quality on diffusion measures in children
Koirala, N., Kleinman, D., Perdue, M. V., Su, X., Villa, M., Grigorenko, E. L., & Landi, N. (2021) · Human Brain Mapping · doi:10.1002/hbm.25724 · Cited by 10
Two-Tensor Tractography Using a Constrained Filter
Malcolm, J. G., Shenton, M. E., & Yogesh Rathi, A. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04268-3_110 · Cited by 11
“Following the experimental method of generating multi-compartment synthetic data found in [2,8,15], we averaged the eigenvalues of the 300 voxels with highest fractional anisotropy (FA) in our real data set: {1200, 100, 100}μm2/msec.”
BackgroundMethodInfluential
A Riemannian Scalar Measure for Diffusion Tensor Images
Fuster, A., Astola, L., & Florack, L. M. J. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-03767-2_51 · Cited by 11
Inferring multiple maxima in intravoxel white matter fiber distribution
Canales-Rodríguez, E. J., Melie‐García, L., Iturria‐Medina, Y., Martínez‐Montes, E., Alemán‐Gómez, Y., & Lin, C. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21673 · Cited by 11
“[10] is the inverse of the normalization constant of the Gamma distribution Ga *, * (see Appendix A).”
Background
A full bi-tensor neural tractography algorithm using the unscented Kalman filter
Lienhard, S., Malcolm, J. G., Westin, C., & Yogesh Rathi, A. (2011) · EURASIP Journal on Advances in Signal Processing · doi:10.1186/1687-6180-2011-77 · Cited by 11
“Our implementation also supports one or three tensors but several studies have shown that a two-fiber model performs best in our environment with b = 1000 s mm[4,6,28,39,7,13].”
Converting Multi-Shell and Diffusion Spectrum Imaging to High Angular Resolution Diffusion Imaging
Yeh, F.-C. F., & Verstynen, T. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00418 · Cited by 10
“…such as diffusion tensor imaging (DTI) (Basser et al., 1994; Basser and Pierpaoli, 1996) and high angular resolution diffusion imaging (HARDI) (Tuch et al., 2002; Tuch, 2004) remain the most popular diffusion MRI acquisition approaches, whereas multi-shell (Sotiropoulos et al., 2013) and…”
Background
Altered white matter connectivity in children with congenital heart disease with single ventricle physiology
Williamson, B. J., Barnes‐Davis, M. E., Vannest, J. J., Anixt, J. S., Heydarian, H. C., Kuan, L., Laue, C. S., Pratap, J. “., Schapiro, M. B., Tseng, S. Y., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-28634-9 · Cited by 12
Current perspectives on tractography-guided deep brain stimulation for the treatment of mood disorders
Chan, J. L., Carpentier, A. V., Middlebrooks, E. H., Okun, M. S., & Wong, J. K. (2023) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2023.2289573 · Cited by 12
“High angular resolution diffusion imaging (HARDI) [103] acquires images using a larger number of gradient directions to increase angular resolution and facilitates improved tract modeling.”
Background
Connectivity related to major brain functions in Alzheimer disease progression: microstructural properties of the cingulum bundle and its subdivision using diffusion-weighted MRI
Ricchi, M., Campani, G., Nagmutdinova, A., Bortolotti, V., Greco, D., Golini, C., Grist, J. T., Brizi, L., & Testa, C. M. (2025) · European Radiology Experimental · doi:10.1186/s41747-025-00570-5 · Cited by 10
Triple visual hemifield maps in a case of optic chiasm hypoplasia
Ahmadi, K., Fracasso, A., Puźniak, R. J., Gouws, A. D., Yakupov, R., Speck, O., Kaufmann, J., Pestilli, F., Dumoulin, S. O., Morland, A. B., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116822 · Cited by 10
“, 2013); high angular resolution granted by 128 unique gradient directions (Tuch et al., 2002)] and analyzed with the methods ensuring the optimal discrimination between separate fiber populations, such as the Multi-Tissue constrained spherical deconvolution (Jeurissen et al.”
Extracting Quantitative Measures from EAP: A Small Clinical Study Using BFOR
Hosseinbor, A. P., Chung, M. K., Wu, Y., Fleming, J. O., Field, A. S., & Alexander, A. L. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33418-4_35 · Cited by 9
“Many HARDI techniques [7, 11] seek to extract the orientation distribution function (ODF), a probability density function describing the angular distribution of water molecules during diffusion.”
Influential
Analysis of the pyramidal tract in tumor patients using diffusion tensor imaging
Cárdenes, R., Muñoz‐Moreno, E., Sarabia-Herrero, R., Rodríguez‐Velasco, M., Fuertes-Alija, J. J., & Martín‐Fernández, M. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.032 · Cited by 10
“Also, more complex methods such as High Angular Resolution Diffusion Imaging (HARDI) (Tuch et al., 2002), Q-Ball Imaging (QBI) (Tuch, 2004) or Q-Space Imaging (QSI) (Callaghan et al.”

Authors: Tuch, D. S., Reese, T. G., Wiegell, M. R., Makris, N., Belliveau, J. W., & Wedeen, V. J.
Affiliations: Massachusetts General Hospital (US)
Corresponding author: Wedeen, Van J.
ORCID: Reese, Timothy G.
Makris, Nikos
Venue: Magnetic Resonance in Medicine
Publisher: Wiley
Published: 2002-09-26
Volume: 48
Issue: 4
Pages: 577-582
ISSN: 0740-3194 (ISSN-L)
1522-2594
DOI: 10.1002/mrm.10268
OpenAlex: W2080198834
Cited by: 1,548
References: 27
Citations by year: 2026: 20 · 2025: 43 · 2024: 39 · 2023: 52 · 2022: 59 · 2021: 65 · 2020: 65 · 2019: 82 · 2018: 76 · 2017: 84 · 2016: 84 · 2015: 115 · 2014: 93 · 2013: 95 · 2012: 79
FWCI: 23.23
Type: journal article
Language: en
Open access: closed
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Magnetic Resonance in Medicine (publishedVersion)
PubMed (publishedVersion)
Funders: Sol Goldman Charitable Trust
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords: high angular resolution diffusion imaging
MeSH terms: Brain, Computer Simulation, Humans, Image Processing, Computer-Assisted, Male, Nerve Fibers, Anisotropy, Diffusion Magnetic Resonance Imaging

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

High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks