Crossing fibres in tract-based spatial statistics

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

The 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

Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia

Song, 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

Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution

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

Connectome mapping with edge density imaging differentiates pediatric mild traumatic brain injury from typically developing controls: proof of concept

Raji, C. A., Wang, M. B., Nguyen, N.-N., Owen, J. P., Palacios, E. M., Yuh, E. L., & Mukherjee, P. (2020) · Pediatric Radiology · doi:10.1007/s00247-020-04743-9 · Cited by 24

Alterations of hippocampal projections in adult macaques with neonatal hippocampal lesions: A Diffusion Tensor Imaging study

Meng, Y., Payne, C. D., Li, L., Hu, X. P., Zhang, X., & Bachevalier, J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.08.059 · Cited by 23

Association of White Matter Integrity With Executive Function and Antidepressant Treatment Outcome in Patients With Late-Life Depression

He, X., Pueraro, E., Kim, Y., Garcia, C. M., Maas, B., Choi, J.-W., Egglefield, D. A., Schiff, S., Sneed, J. R., Brown, P. J., et al. (2021) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2021.01.004 · Cited by 21

Thalamic white matter macrostructure and subnuclei volumes in Parkinson’s disease depression

Bhome, R., Zarkali, A., Thomas, G. E. C., Iglesias, J., Cole, J., & Weil, R. (2021) · medRxiv · doi:10.1038/s41531-021-00270-y · Cited by 20

Elucidating the aberrant brain regions in bipolar disorder using T1-weighted/T2-weighted magnetic resonance ratio images

Ishida, T., Donishi, T., Iwatani, J., Yamada, S., Takahashi, S., Ukai, S., Shinosaki, K., Terada, M., & Kaneoke, Y. (2017) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2017.03.006 · Cited by 20

Fixel-Based Analysis of White Matter Degeneration in Patients With Progressive Supranuclear Palsy or Multiple System Atrophy, as Compared to Parkinson's Disease

Nguyen, T., Cheng, J.-S., Chen, Y.-L., Lin, Y.-C., Tsai, C.-C., Lu, C.-S., Weng, Y., Wu, Y.-M., Hoang, N., & Wang, J.-J. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.625874 · Cited by 20

Structural integrity of frontostriatal connections predicts longitudinal changes in self-esteem

Chavez, R. S., & Heatherton, T. F. (2016) · Social Neuroscience · doi:10.1080/17470919.2016.1164753 · Cited by 17

Differential associations between systemic markers of disease and cortical thickness in healthy middle-aged and older adults

Coutinho, A. M., Coutu, J., Lindemer, E., Rosas, H. D., Rosen, B. R., & Salat, D. H. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.021 · Cited by 18

Individualized Thalamic Parcellation Reveals Alterations in Shape and Microstructure of Thalamic Nuclei in Patients with Disorder of Consciousness

Zheng, W., Tan, X., Liu, T., Li, X., Gao, J., Hong, L., Zhang, X., Zhao, Z., Yu, Y., Zhang, Y., et al. (2021) · Cerebral Cortex Communications · doi:10.1093/texcom/tgab024 · Cited by 16

Neuroimaging and plasma evidence of early white matter loss in Parkinson’s disease with poor outcomes

Zarkali, A., Hannaway, N., McColgan, P., Heslegrave, A., Veleva, E., Laban, R., Zetterberg, H., Lees, A. J., Fox, N. C., & Weil, R. S. (2024) · Brain Communications · doi:10.1093/braincomms/fcae130 · Cited by 18

Evaluation of diffusion measurements reveals radial diffusivity indicative of microstructural damage following acute, mild traumatic brain injury

Mahan, M. Y., Rafter, D., Truwit, C. L., Oswood, M. C., & Samadani, U. (2020) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2020.12.012 · Cited by 17

Quantifying the brain's sheet structure with normalized convolution

Tax, C. M. W., Westin, C., Haije, T. D., Fuster, A., Viergever, M. A., Calabrese, E., Florack, L. M. J., & Leemans, A. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.03.007 · Cited by 16

Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture

Chad, J. A., Pasternak, O., & Chen, J. J. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.12.020 · Cited by 12

Wired for musical rhythm? A diffusion MRI-based study of individual differences in music perception

Rajan, A., Valla, J. M., Alappatt, J. A., Sharda, M., Shah, A., Ingalhalikar, M., & Singh, N. C. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01868-y · Cited by 16

Diffusion tensor-based analysis of white matter in the healthy aging canine brain

Barry, E. F., Loftus, J. P., Luh, W., de Leon, M. J., Niogi, S. N., & Johnson, P. J. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.04.021 · Cited by 15

The effect of gradient sampling schemes on diffusion metrics derived from probabilistic analysis and tract-based spatial statistics

Hope, T. R., Westlye, L. T., & Bjørnerud, A. (2012) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2011.11.003 · Cited by 14

Nonhuman primate meso-circuitry data: a translational tool to understand brain networks across species

Tang, W., Choi, E. Y., Heilbronner, S. R., & Haber, S. N. (2020) · Brain Structure and Function · doi:10.1007/s00429-020-02133-3 · Cited by 13

Fiber orientation distribution from diffusion MRI: Effects of inaccurate response function calibration

Guo, F., Tax, C. M. W., Luca, A. D., Viergever, M. A., Heemskerk, A. M., & Leemans, A. (2021) · Journal of Neuroimaging · doi:10.1111/jon.12901 · Cited by 11

Abnormal White Matter Microstructure in the Limbic System Is Associated With Tuberous Sclerosis Complex-Associated Neuropsychiatric Disorders

Sato, A., Tominaga, K., Iwatani, Y., Kato, Y., Wataya‐Kaneda, M., Makita, K., Nemoto, K., Taniike, M., & Kagitani‐Shimono, K. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.782479 · Cited by 13

Cross-subject Comparison of Local Diffusion MRI Parameters

Smith, S. M., & Kindlmann, G. (2009) · Elsevier eBooks · doi:10.1016/b978-0-12-374709-9.00008-0 · Cited by 13

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

Fixel-Based Diffusion Magnetic Resonance Imaging Reveals Novel Associations Between White Matter Microstructure and Childhood Aggressive Behavior

Grazioplene, R. G., Tseng, W., Cimino, K., Kalvin, C. B., Ibrahim, K., Pelphrey, K. A., & Sukhodolsky, D. G. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2019.12.018 · Cited by 13

Opposing white matter microstructure abnormalities in 22q11.2 deletion and duplication carriers

Seitz‐Holland, J., Lyons, M., Kushan, L., Lin, A., Villalón‐Reina, J. E., Cho, K. I. K., Zhang, F., Billah, T., Sylvain Bouix, A., Kubicki, M. R., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01703-1 · Cited by 12

Quantitative Histological Validation of Diffusion Tensor MRI with Two-Photon Microscopy of Cleared Mouse Brain

Kamagata, K., Kerever, A., Yokosawa, S., Otake, Y., Ochi, H., Hori, M., Kamiya, K., Tsuruta, K., Tagawa, K., Okazawa, H., et al. (2016) · Magnetic Resonance in Medical Sciences · doi:10.2463/mrms.bc.2015-0148 · Cited by 12

Mean kurtosis alterations of cerebral white matter in patients with schizophrenia revealed by diffusion kurtosis imaging

Narita, H., Tha, K. K., Hashimoto, N., Hamaguchi, H., Nakagawa, S., Shirato, H., & Kusumi, I. (2016) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2016.07.011 · Cited by 12

Multimodal MRI reveals structural connectivity differences in 22q11 deletion syndrome related to impaired spatial working memory

O’Hanlon, E., Howley, S., Prasad, S. E., McGrath, J., Leemans, A., McDonald, C., Garavan, H., & Murphy, K. C. (2016) · Human Brain Mapping · doi:10.1002/hbm.23337 · Cited by 12

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

MRI Diffusion Indices Sampled Along Streamline Trajectories: Quantitative Tractography Mapping

Pannek, K., Mathias, J. L., & Rose, S. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0040 · Cited by 10

White-matter crossing-fiber microstructure in adolescents prenatally exposed to cocaine

Morie, K. P., Yip, S. W., Zhai, Z. W., Xu, J., Hamilton, K. R., Sinha, R., Mayes, L. C., & Potenza, M. N. (2017) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2017.01.011 · Cited by 9

Diffusion tensor-based analysis of white matter in dogs with idiopathic epilepsy

Beckmann, K. M., Wang‐Leandro, A., Steffen, F., Richter, H., Dennler, M., Bektas, R. N., Carrera, I., & Haller, S. (2023) · Frontiers in Veterinary Science · doi:10.3389/fvets.2023.1325521 · Cited by 9

Low Rank plus Sparse decomposition of ODFs for improved detection of group-level differences and variable correlations in white matter

Baete, S. H., Chen, J., Lin, Y., Wang, X., Otazo, R., & Boada, F. E. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.014 · Cited by 9

Cross-Subject Comparison of Local Diffusion MRI Parameters

Smith, S. M., Kindlmann, G., & Jbabdi, S. (2014) · Diffusion MRI · doi:10.1016/b978-0-12-396460-1.00010-x · Cited by 8

Association between white matter alterations on diffusion tensor imaging and incidence of frailty in older adults with cardiometabolic diseases

Tamura, Y., Shimoji, K., Ishikawa, J., Murao, Y., Yorikawa, F., Kodera, R., Oba, K., Toyoshima, K., Chiba, Y., Tokumaru, A. M., et al. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.912972 · Cited by 7

Diffusion MRI abnormalities detection with orientation distribution functions: A multiple sclerosis longitudinal study

Commowick, O., Maarouf, A., Ferré, J., Ranjeva, J., Edan, G., & Barillot, C. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.02.005 · Cited by 7

Estimation of diffusion properties in three-way fiber crossings without overfitting

Yang, J., Poot, D. H. J., A, L. J. V. V., & Vos, F. M. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/23/9123 · Cited by 6

Comparison of CPU and GPU bayesian estimates of fibre orientations from diffusion MRI

Kim, D. H. C., Williams, L. J., Hernández-Fernández, M., & Björnson, B. (2022) · PLoS ONE · doi:10.1371/journal.pone.0252736 · Cited by 6

Altered white matter connectivity associated with visual hallucinations following occipital stroke

Rafique, S. A., Richards, J. R., & Steeves, J. K. E. (2018) · Brain and Behavior · doi:10.1002/brb3.1010 · Cited by 6

Harmonizing multisite neonatal diffusion-weighted brain MRI data for developmental neuroscience

Bonthrone, A., Blesa-Cábez, M., Edwards, A. D., Hajnal, J., Counsell, S., & Boardman, J. P. (2024) · medRxiv · doi:10.1016/j.dcn.2024.101488 · Cited by 4

Reliable Dual Tensor Model Estimation in Single and Crossing Fibers Based on Jeffreys Prior

Yang, J., Poot, D. H. J., Caan, M. W. A., Su, T., Majoie, C. B. L. M., A, L. J. V. V., & Vos, F. M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0164336 · Cited by 5

The effect of written scripts’ dissimilarity over ventral and dorsal reading pathway: combined fMRI & DTI study

Kumar, U., & Padakannaya, P. (2019) · Reading and Writing · doi:10.1007/s11145-019-09952-9 · Cited by 5

Genetic variation in the G72 gene is associated with increased frontotemporal fiber tract integrity

Nickl‐Jockschat, T., Stöcker, T., Krug, A., Markov, V., Maximov, I. I., Huang, R., Schneider, F. W., Habel, U., Eickhoff, S. B., Zerres, K., et al. (2014) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-014-0516-6 · Cited by 5

The brain-derived neurotrophic factor Val66Met genotype does not influence the grey or white matter structures underlying recognition memory

McKay, N. S., Moreau, D., Henare, D., & Kirk, I. J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.03.072 · Cited by 5

Hierarchical modelling of crossing fibres in the white matter

Rafipoor, H., Lange, F. J., Arthofer, C., Cottaar, M., & Jbabdi, S. (2025) · Imaging Neuroscience · doi:10.1162/imag_a_00436 · Cited by 4

Lateralized cerebellar connectivity differentiates auditory pathways in echolocating and non-echolocating whales

Flem, S., Berns, G. S., Inglis, B. A., Niederhut, D., Montie, E. W., Deacon, T. W., Miller, K. L., Tyack, P. L., & Cook, P. F. (2025) · PLoS ONE · doi:10.1371/journal.pone.0323617 · Cited by 6

Diffusion Tensor Imaging (DTI) and Tractography

Rüber, T., Elger, C. E., & Weber, B. (2016) · Studies in neuroscience, psychology and behavioral economics · doi:10.1007/978-3-642-35923-1_22 · Cited by 4

Tract-specific statistics based on diffusion-weighted probabilistic tractography

Reid, A., Camilleri, J. A., Hoffstaedter, F., & Eickhoff, S. B. (2022) · Communications Biology · doi:10.1038/s42003-022-03073-w · Cited by 4

Anatomical and Technical Preparations of the Human Brain for White Matter Fibers Dissection with Electromagnetic Neuronavigation Assistance Technical Nuances for Application

Bykanov, A., Pitskhelauri, D. I., Batalov, A. I., Trube, M. A., Danilov, G., & Golbin, D. A. (2022) · World Neurosurgery · doi:10.1016/j.wneu.2022.09.122 · Cited by 4

Missing the forest because of the trees: slower alternations during binocular rivalry are associated with lower levels of visual detail during ongoing thought

Ho, N. S. P., Baker, D. H., Karapanagiotidis, T., Seli, P., Wang, H. T., Leech, R., Bernhardt, B. C., Margulies, D. S., Jefferies, E., & Smallwood, J. (2020) · Neuroscience of Consciousness · doi:10.1093/nc/niaa020 · Cited by 4

A Reproducible Neurobiology of Depressive RuminationPreprint

Pisner, D. A., Shumake, J., Beevers, C. G., & Schnyer, D. M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/365759 · Cited by 4

Orientation Prior and Consistent Model Selection Increase Sensitivity of Tract-Based Spatial Statistics in Crossing-Fiber Regions

Arkesteijn, G. A. M., Poot, D. H. J., Ikram, M. A., Niessen, W. J., A, L. J. V. V., Vernooij, M. W., & Vos, F. M. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2922615 · Cited by 3

Unraveling multi-fixel microstructure with tractography and angular weighting

Delinte, N., Dricot, L., Macq, B. M. M., Gosse, C., Reybroeck, M. V., & Rensonnet, G. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1199568 · Cited by 5

White matter microstructure alterations in idiopathic restless legs syndrome: a study combining crossing fiber-based and tensor-based approaches

Xue, Y., Xie, S., Wang, X., Xi, X., & Liu, C. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1240929 · Cited by 3

FetDTIAlign: A deep learning framework for affine and deformable registration of fetal brain dMRI

Li, B., Zeng, Q., Warfield, S. K., & Karimi, D. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121190 · Cited by 3

DTI Image Registration under Probabilistic Fiber Bundles Tractography Learning

Guo, Z., Wang, Y., Lei, T., Fan, Y., & Zhang, X. (2016) · BioMed Research International · doi:10.1155/2016/4674658 · Cited by 3

The relationship between brain structure, motor performance, and early musical training

Steele, C. J. (2012) · Spectrum Research Repository (Concordia University) · Cited by 3

Substance‐use initiation moderates the effect of stress on white‐matter microstructure in adolescents

Zhai, Z. W., Yip, S. W., Morie, K. P., Sinha, R., Mayes, L. C., & Potenza, M. N. (2018) · American Journal on Addictions · doi:10.1111/ajad.12710 · Cited by 2

Distinguished Frontal White Matter Abnormalities Between Psychotic and Nonpsychotic Bipolar Disorders in a Pilot Study

Shiroyama, T., Maeda, M., Tanii, H., Motomura, E., & Okada, M. (2025) · Brain Sciences · doi:10.3390/brainsci15020108 · Cited by 2

Augmented reality intraoperative tractography for diffuse glioma resection adjacent to the corticospinal tract: a case series with preliminary results

Konovalov, A. N., Bykanov, A., Okishev, D. N., Artemyev, A. A., Knyazev, A., Иванов, В. М., Smirnov, A. Y., Strelkov, S., Pronin, I., Pavlova, G. V., et al. (2025) · Neurosurgical Review · doi:10.1007/s10143-025-03709-5 · Cited by 2

Tract-specific white matter microstructural alterations in subjects with schizophrenia and unaffected first-degree relatives

Xie, S., Zhuo, J., Song, M., Chu, C., Cui, Y. J., Chen, Y., Wang, H., Li, L., & Jiang, T. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00681-2 · Cited by 2

A hybrid network for fiber orientation distribution reconstruction employing multi‐scale information

Yu, H., Ai, L., Yao, R., & Li, J. (2024) · Medical Physics · doi:10.1002/mp.17505 · Cited by 2

Tract-Based Spatial Statistics and Other Approaches for Cross-Subject Comparison of Local Diffusion MRI Parameters

Smith, S. M., Kindlmann, G., & Jbabdi, S. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00316-x · Cited by 2

NVAM-Net: deep learning networks for reconstructing high-quality fiber orientation distributions

Li, J., Ai, L., & Yao, R. (2024) · Neuroradiology · doi:10.1007/s00234-024-03341-y · Cited by 2

Heritable cognitive and psychopathology factors in youth are predicted by brain fronto-temporal white matter pathwayPreprint

Alnæs, D., Kaufmann, T., Doan, N. T., Córdova-Palomera, A., Wang, Y.-P., Bettella, F., Moberget, T., Andreassen, O., & Westlye, L. (2017) · bioRxiv · doi:10.1101/172080 · Cited by 1

CL-TrackNet: A Hybrid CNN-LSTM Network for Tractography

Yao, Y., Ai, L., & Gu, W. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.130846 · Cited by 1

Recent Topics of Brain MRI : Arterial Spin Labeling and New Diffusion Analysis(<SPECIAL ISSUE>Neuroimaging Update)

Aoki, S., Hori, M., Kamagata, K., Hattori, T., Shimoji, K., Asahi, K., Nakanishi, A., & Hamazakii, N. (2011) · Japanese Journal of Neurosurgery · doi:10.7887/jcns.20.655 · Cited by 1

Voxel Based Analysis of Diffusion Indices in Patients with Primary Open-Angle Glaucoma Using Tract-Based Spatial Statistics

Schmidt, M. A. (2015) · Journal of Clinical & Experimental Ophthalmology · doi:10.4172/2155-9570.1000415 · Cited by 1

Glaucoma: an eye or a brain disease?

Hanekamp, S. (2017) · University of Groningen research database (University of Groningen / Centre for Information Technology) · Cited by 1

Diffusion MRI Changes in the Healthy Aging Canine BrainPreprint

Barry, E. F., Loftus, J. P., Luh, W., de Leon, M. J., Niogi, S. N., & Johnson, P. J. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.05.327205 · Cited by 1

Reconstructing White Matter Fiber from Brain DTI for Neuroimage Analysis

Li, G., Duan, Y., & Sun, Q. (2014) · Communications in computer and information science · doi:10.1007/978-3-662-46248-5_4

Cross-Subject Image Analysis in Diffusion Brain MRI

de Groot, M. (2014) · RePub (Erasmus University Rotterdam)

Traumatic brain injury: relationships between brain structural abnormalities and cognitive function

Kinnunen, K. M. (2011) · Goldsmiths (University of London)

Estimating diffusion properties in complex fiber configurations based on structure-adaptive multi-valued tensor-field filtering

Yang, J., Poot, D. H. J., Arkesteijn, G. A. M., Caan, M. W. A., A, L. J. V. V., & Vos, F. M. (2015) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2080759

Establishing The Method Of Dual-tensor For Tract Based Analysis (DTTA) And Investigating Human Brain Developmental Connectome With Diffusion MRI

Mishra, V. R. (2014) · UTA ResearchCommons (University of Texas Arlington)

Neurocognitive Plasticity: A Longitudinal Study of Memory Training and White Matter Microstructure

de Lange, & Glasø, A.-M. D. L. (2017)

Longitudinal analysis of diffusion-weighted MRI with a ball-and-sticks model

Arkesteijn, G. A. M., Poot, D. H. J., Niestijl, M., Vernooij, M. W., Niessen, W. J., A, L. J. V. V., & Vos, F. M. (2017) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2017.7950635

Missing the forest because of the trees: Slower alternations during binocular rivalry are associated with lower levels of visual detail during ongoing thoughtPreprint

Ho, N. S. P., Baker, D. H., Karapanagiotidis, T., Seli, P., Wang, H. T., Leech, R., Bernhardt, B. C., Margulies, D. S., Jefferies, E., & Smallwood, J. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.31.891853

Using Diffusion Tensor Imaging to examine brain structural plasticity and language experiencePreprint

Luk, G., & Pliatsikas, C. (2019) · doi:10.31234/osf.io/468xa

Unraveling Shared Pathways: A Comprehensive Systematic Review of Common Fiber Tracts in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia using Diffusion Tensor ImagingPreprint

Alruwaili, A. R., Devine, M. S., & McCombe, P. (2023) · medRxiv · doi:10.1101/2023.11.09.23298318

Augmented Reality Intraoperative Tractography for diffuse glioma microsurgical resectionPreprint

Коновалов, А. Н., Bykanov, A., Okishev, D. N., Artemyev, A. A., Knyazev, A., Иванов, В. М., Smirnov, A., Strelkov, S., Pronin, I., Pavlova, G. V., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-5444302/v1

White Matter Integrity Differences in 2‐Year‐Old Children Treated With ECMO: A Diffusion‐Weighted Imaging Study

Ruttorf, M., Filip, J., Schaible, T., Weis, M., & Zöllner, F. G. (2025) · European Journal of Neuroscience · doi:10.1111/ejn.70026

Effect of glucocorticoid therapy on brain white matter microstructure in thyroid-associated ophthalmopathy: a longitudinal diffusion kurtosis imaging study

Wu, Q., Lu, J., Zhou, J., Pu, X., Chen, H., Wu, F., Xu, X., & Hu, H. (2025) · Brain Imaging and Behavior · doi:10.1007/s11682-025-01025-6

Microstructural Plasticity

Camacho, P., Wilcox, R. R., Barbey, A. K., & Sutton, B. P. (2025) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780197677131.013.11

The independent prognostic value of brain diffusion tensor imaging in comatose patients after cardiac arrest

Jia, X., Shao, R., Li, Y., Jia, X., Tang, Z., & Yang, Q. (2025) · Brain Informatics · doi:10.1186/s40708-025-00284-9

Structural and Connectivity Alterations of the Premotor Cortex in Autistic Children: Implications for Affective Motor Impairments

Carapelli, C., Gerbella, M., Tambuscio, F., & Cesare, G. D. (2026) · Brain Sciences · doi:10.3390/brainsci16050446

Gray Matter Microstructure Measured Using Diffusion Imaging as a Biomarker of Severity in Lewy Body Diseases

Zarkali, A., Dobreva, I., Hannaway, N., Bhome, R., Thomas, G. E. C., Carrera, S., Heslegrave, A., Veleva, E., Zetterberg, H., & Weil, R. S. (2026) · Movement Disorders · doi:10.1002/mds.70355

Alexithymia mediates white-matter microstructure and substance use escalation in trauma-exposed individuals

Luster, C. B., Morie, K. P., Legido, J., Mayes, L. C., Potenza, M. N., & Zhai, Z. W. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.122185

Substance use involvement moderates the effect of cortisol response on white-matter microstructure longitudinally

Smith, C. E., Luster, C. B., Kimmel, S. E., Reynolds, M., Potenza, M. N., & Zhai, Z. W. (2026) · Dialogues in Clinical Neuroscience · doi:10.1080/19585969.2026.2719512

Hierarchical modelling of crossing fibres in the white matter

Rafipoor, H., Lange, F. J., Arthofer, C., Cottaar, M., & Jbabdi, S. (2025) · Imaging Neuroscience · doi:10.1162/imag_a_00436 · Cited by 4

Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging

Jeurissen, B., Leemans, A., Tournier, J., Jones, D. K., & Sijbers, J. (2013) · Human Brain Mapping · doi:10.1002/hbm.22099 · Cited by 1,088

Multivariate group-wise genetic analysis of white matter integrity using orientation distribution functions

Leporé, N., Brun, C., Descoteaux, M., Lee, A. D., Marina Barysheva, A., Chou, Y., de Zubicaray, G. I., McMahon, K. L., Wright, M. J., Martin, N. G., et al. (2010) · Cited by 3

Detection of crossing white matter fibers with high-order tensors and

Jiao, F., Gur, Y., Johnson, C. R., & Joshi, S. C. (2012)

Modified Method for Classifying Crossing and Non-crossing Voxels in Fiber Reconstruction

Wang, M., Wei, G., Zhao, X. W., Liu, H., & Li, D. (2005) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2005.1617126