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Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?
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Abstract
White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.
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“Even when given the same set of underlying streamlines, variability across protocols for bundle segmentation was found to be greater than all other sources of potential unevenness.”
From Superior Longitudinal Fasciculus: A Review of the Anatomical Descriptions With Functional Correlates (2022) · cites this paper as [69]
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Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.015 · Cited by 11,314
UMAP: Uniform Manifold Approximation and Projection
McInnes, L., Healy, J., Saul, N., & Großberger, L. (2018) · Journal of Open Source Software · doi:10.21105/joss.00861 · Cited by 9,826
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101
Avants, B., Epstein, C. L., Grossman, M., & Gee, J. C. (2007) · Medical Image Analysis · doi:10.1016/j.media.2007.06.004 · Cited by 5,924
Unbiased average age-appropriate atlases for pediatric studies
Fonov, V., Evans, A. C., Botteron, K., Almli, C. R., McKinstry, R. C., & Collins, D. L. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.033 · Cited by 2,290
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
Reproducibility of quantitative tractography methods applied to cerebral white matter
Wakana, S., Caprihan, A., Panzenboeck, M. M., Fallon, J. H., Perry, M., Gollub, R. L., Hua, K., Zhang, J., Jiang, H., Dubey, P., et al. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.02.049 · Cited by 1,686
A diffusion tensor imaging tractography atlas for virtual in vivo dissections.
CATANI, M., & THIEBAUTDESCHOTTEN, M. (2008) · Cortex · doi:10.1016/j.cortex.2008.05.004 · Cited by 1,642
Virtual in vivo interactive dissection of white matter fasciculi in the human brain
Catani, M., Howard, R. J., Pajevic, S., & Jones, D. K. (2002) · NeuroImage · doi:10.1006/nimg.2002.1136 · Cited by 1,637
(2002) · Cited by 1,635
Tractography-based connectomes are dominated by false-positive connections
Maier-Hein, K. H., Neher, P., Houde, J.-C., Côté, M.-A., Garyfallidis, E., Zhong, J., Chamberland, M., Yeh, F.-C., Lin, Y.-C., Ji, Q., et al. (2016) · doi:10.1101/084137 · Cited by 1,376
Self-citationDipy, a library for the analysis of diffusion MRI data
Garyfallidis, E., Brett, M., Amirbekian, B., Rokem, A., van der Walt, S., Descoteaux, M., Nimmo-Smith, I., & Contributors, D. (2014) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2014.00008 · Cited by 1,371
Self-citationThe Human Central Nervous System
Nieuwenhuys, R., Voogd, J., & van Huijzen, C. (2008) · doi:10.1007/978-3-540-34686-9 · Cited by 1,262
Smith, R. E., Tournier, J.-D., Calamante, F., & Connelly, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.005 · Cited by 1,216
Self-citationHofer, S., & Frahm, J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.05.044 · Cited by 1,197
Schmahmann, J. D., & Pandya, D. N. (2006) · doi:10.1093/acprof:oso/9780195104233.001.0001 · Cited by 1,157
Variability in the analysis of a single neuroimaging dataset by many teams
(2020) · doi:10.1038/s41586-020-2314-9 · Cited by 1,097
Self-citationThe Human Connectome Project's neuroimaging approach
Glasser, M. F., Smith, S. M., Marcus, D. S., Andersson, J. L. R., Auerbach, E. J., Behrens, T. E. J., Coalson, T. S., Harms, M. P., Jenkinson, M., Moeller, S., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4361 · Cited by 1,090
Schmahmann, J. D., Pandya, D. N., Wang, R., Dai, G., D'Arceuil, H. E., de Crespigny, A. J., & Wedeen, V. J. (2007) · Brain · doi:10.1093/brain/awl359 · Cited by 1,067
Tract profiles of white matter properties: automating fiber-tract quantification
Yeatman, J. D., Dougherty, R. F., Myall, N. J., Wandell, B. A., & Feldman, H. M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0049790 · Cited by 840
Catani, M., & Mesulam, M. M. (2008) · Cortex · doi:10.1016/j.cortex.2008.04.002 · Cited by 790
Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results
Silberzahn, R., Uhlmann, E. L., Martin, D. P., Anselmi, P., Aust, F., Awtrey, E. C., Bahník, Š., Bai, F., Bannard, C., Bonnier, E., et al. (2018) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245917747646 · Cited by 773
Thomas, C., Ye, F. Q., Irfanoglu, M. O., Modi, P., Saleem, K. S., Leopold, D. A., & Pierpaoli, C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405672111 · Cited by 725
The Brain Connection: The Corpus Callosum Is Larger in Left-Handers
Witelson, S. F. (1985) · Science · doi:10.1126/science.4023705 · Cited by 689
Monkey to human comparative anatomy of the frontal lobe association tracts
Thiebaut de Schotten, M., Dell’Acqua, F., Valabregue, R., & Catani, M. (2012) · Cortex · doi:10.1016/j.cortex.2011.10.001 · Cited by 632
Smith, S. M., Johansen‐Berg, H., Jenkinson, M., Rueckert, D., Nichols, T. E., Miller, K. L., Robson, M. D., Jones, D. K., Klein, J. C., Bartsch, A. J., et al. (2007) · Nature Protocols · doi:10.1038/nprot.2007.45 · Cited by 582
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
Diffusion MRI at 25: exploring brain tissue structure and function
Le Bihan, D., & Johansen-Berg, H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.006 · Cited by 498
Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language
Dick, A. S., & Tremblay, P. (2012) · Brain · doi:10.1093/brain/aws222 · Cited by 470
Reveley, C., Seth, A. K., Pierpaoli, C., Silva, A. C., Yu, D., Saunders, R. C., Leopold, D. A., & Ye, F. Q. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1418198112 · Cited by 417
Donahue, C. J., Sotiropoulos, S. N., Jbabdi, S., Hernandez-Fernandez, M., Behrens, T. E., Dyrby, T. B., Coalson, T., Kennedy, H., Knoblauch, K., Van Essen, D. C., et al. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.0493-16.2016 · Cited by 380
Lawes, I. N. C., Barrick, T. R., Murugam, V., Spierings, N. M. K., Evans, D. R., Song, M., & Clark, C. A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.06.041 · Cited by 379
Self-citationInitialization is critical for preserving global data structure in both t-SNE and UMAP
Kobak, D., & Linderman, G. C. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-00809-z · Cited by 372
Nieuwenhuys, R., Voogd, J., van Huijzen, C., & Papa, M. (2010) · Springer eBooks · doi:10.1007/978-88-470-1140-3 · Cited by 364
Farrell, J. A. D., Landman, B. A., Jones, C. K., Smith, S. A., Prince, J. L., van Zijl, P. C. M., & Mori, S. (2007) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.21053 · Cited by 353
Self-citationSarubbo, S., De Benedictis, A., Maldonado, I. L., Basso, G., & Duffau, H. (2013) · Brain Structure and Function · doi:10.1007/s00429-011-0372-3 · Cited by 345
Towards quantitative connectivity analysis: reducing tractography biases
Girard, G., Whittingstall, K., Deriche, R., & Descoteaux, M. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.04.074 · Cited by 324
Self-citationMulti-parametric neuroimaging reproducibility: A 3-T resource study
Landman, B. A., Huang, A. J., Gifford, A., Vikram, D. S., Lim, I. A. L., Farrell, J. A. D., Bogovic, J., Hua, J., Chen, M., Jarso, S., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.047 · Cited by 302
Self-citationLandman, B. A., Farrell, J. A. D., Jones, C. K., Smith, S. A., Prince, J. L., & Mori, S. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.02.056 · Cited by 287
Self-citationMapping hV4 and ventral occipital cortex: The venous eclipse
Winawer, J. A., Horiguchi, H., Sayres, R., Amano, K., & Wandell, B. A. (2010) · Journal of Vision · doi:10.1167/10.5.1 · Cited by 270
Limits to anatomical accuracy of diffusion tractography using modern approaches
Schilling, K. G., Nath, V., Hansen, C., Parvathaneni, P., Blaber, J., Gao, Y., Neher, P., Aydogan, D. B., Shi, Y., Ocampo-Pineda, M., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.029 · Cited by 260
Self-citationEvaluation and statistical inference for human connectomes
Pestilli, F., Yeatman, J. D., Rokem, A., Kay, K. N., & Wandell, B. A. (2014) · Nature Methods · doi:10.1038/nmeth.3098 · Cited by 259
Self-citationWhere is 'Dorsal V4' in Human Visual Cortex? Retinotopic, Topographic and Functional Evidence
Tootell, R. B. H. (2001) · Cerebral Cortex · doi:10.1093/cercor/11.4.298 · Cited by 255
Essayed, W. I., Zhang, F., Unadkat, P., Cosgrove, G. R., Golby, A. J., & O’Donnell, L. J. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.06.011 · Cited by 249
Self-citationForkel, S. J., Thiebaut de Schotten, M., Kawadler, J. M., Dell'Acqua, F., Danek, A., & Catani, M. (2014) · Cortex · doi:10.1016/j.cortex.2012.09.005 · Cited by 248
The white matter query language: a novel approach for describing human white matter anatomy
Wassermann, D., Makris, N., Yogesh Rathi, A., Shenton, M. E., Kikinis, R., Kubicki, M. R., & Westin, C. (2016) · Brain Structure and Function · doi:10.1007/s00429-015-1179-4 · Cited by 235
Self-citationTractometer: Towards validation of tractography pipelines
Côté, M.-A., Girard, G., Boré, A., Garyfallidis, E., Houde, J.-C., & Descoteaux, M. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.03.009 · Cited by 228
Self-citationJones, D. K., Christiansen, K. F., Chapman, R. J., & Aggleton, J. P. (2013) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2012.11.018 · Cited by 223
Guevara, P., Duclap, D., Poupon, C., Marrakchi‐Kacem, L., Fillard, P., Bihan, D. L., Leboyer, M., Houenou, J., & Mangin, J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.071 · Cited by 210
Self-citationMakovski, T., Swallow, K. M., & Jiang, Y. V. (2010) · Journal of Vision · doi:10.1167/10.1.1 · Cited by 205
Heilbronner, S. R., & Haber, S. N. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.5459-13.2014 · Cited by 202
Self-citationTheaud, G., Houde, J., Boré, A., Rheault, F., Morency, F. C., & Descoteaux, M. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116889 · Cited by 200
Self-citationBastiani, M., Shah, N. J., Goebel, R., & Roebroeck, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.002 · Cited by 192
Mapping connectomes with diffusion MRI: deterministic or probabilistic tractography?
Sarwar, T., Ramamohanarao, K., & Zalesky, A. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27471 · Cited by 190
Pujol, S., Wells, W., Pierpaoli, C., Brun, C., Gee, J., Cheng, G., Vemuri, B., Commowick, O., Prima, S., Stamm, A., et al. (2015) · Journal of Neuroimaging · doi:10.1111/jon.12283 · Cited by 171
Self-citationQuantitative Comparison of Reconstruction Methods for Intra-Voxel Fiber Recovery From Diffusion MRI
Daducci, A., Canales-Rodríguez, E. J., Descoteaux, M., Garyfallidis, E., Gur, Y., Lin, Y., Mani, M., Merlet, S., Paquette, M., Ramírez-Manzanares, A., et al. (2013) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2285500 · Cited by 167
Self-citationBoccardi, M., Bocchetta, M., Apostolova, L. G., Barnes, J., Bartzokis, G., Corbetta, G., DeCarli, C. S., deToledo‐Morrell, L., Firbank, M., Ganzola, R., et al. (2014) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2014.02.009 · Cited by 166
The pyramidal tract recent investigations on its morphology and function
Wiesendanger, M. (2007) · Springer eBooks · doi:10.1007/bfb0111447 · Cited by 151
Challenges in diffusion MRI tractography – Lessons learned from international benchmark competitions
Schilling, K. G., Daducci, A., Maier-Hein, K. H., Poupon, C., Houde, J., Nath, V., Anderson, A. W., Landman, B. A., & Descoteaux, M. (2018) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2018.11.014 · Cited by 148
Self-citationBoccardi, M., Ganzola, R., Bocchetta, M., Pievani, M., Redolfi, A., Bartzokis, G., Camicioli, R. M., Csernansky, J. G., de Leon, M. J., deToledo‐Morrell, L., et al. (2011) · Journal of Alzheimer s Disease · doi:10.3233/jad-2011-0004 · Cited by 144
Confirmation of a gyral bias in diffusion MRI fiber tractography
Schilling, K. G., Gao, Y., Janve, V. A., Stepniewska, I., Landman, B. A., & Anderson, A. W. (2017) · Human Brain Mapping · doi:10.1002/hbm.23936 · Cited by 143
Self-citationHau, J., Sarubbo, S., Perchey, G., Crivello, F., Zago, L., Mellet, E., Jobard, G., Joliot, M., Mazoyer, B. M., Tzourio-Mazoyer, N., et al. (2016) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2016.00058 · Cited by 142
Self-citationValidation of q -ball imaging with a diffusion fibre-crossing phantom on a clinical scanner
Perrin, M., Poupon, C., Rieul, B., Leroux, P., Constantinesco, A., Mangin, J., & Bihan, D. L. (2005) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2005.1650 · Cited by 140
Self-citationThe improbable simplicity of the fusiform face area
Weiner, K. S., & Kalanit Grill-spector, A. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.03.003 · Cited by 138
Superficial white matter: A review on the dMRI analysis methods and applications
Guevara, M., Guevara, P., Román, C., & Mangin, J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116673 · Cited by 129
Self-citationValidation of tractography: Comparison with manganese tracing
Knösche, T. R., Anwander, A., Liptrot, M., & Dyrby, T. B. (2015) · Human Brain Mapping · doi:10.1002/hbm.22902 · Cited by 127
Hau, J., Sarubbo, S., Houde, J. C., Corsini, F., Girard, G., Deledalle, C., Crivello, F., Zago, L., Mellet, E., Jobard, G., et al. (2017) · Brain Structure and Function · doi:10.1007/s00429-016-1298-6 · Cited by 121
Self-citationMandonnet, E., Sarubbo, S., & Petit, L. (2018) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2018.00094 · Cited by 117
Self-citationCommon misconceptions, hidden biases and modern challenges of dMRI tractography
Rheault, F., Poulin, P., Caron, A. V., St‐Onge, E., & Descoteaux, M. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab6aad · Cited by 112
Self-citationThe role of the corticospinal tract in motor recovery in patients with a stroke: A review
Jang, S. H. (2009) · Neurorehabilitation · doi:10.3233/nre-2009-0480 · Cited by 110
Posterior parietal projections to the intraparietal sulcus of the rhesus monkey
Seltzer, B., & Pandya, D. Ν. (1986) · Experimental Brain Research · doi:10.1007/bf00236024 · Cited by 107
Makris, N., Preti, M. G., Wassermann, D., Yogesh Rathi, A., Papadimitriou, G., Yergatian, C., Dickerson, B. C., Shenton, M. E., & Kubicki, M. R. (2013) · Brain Imaging and Behavior · doi:10.1007/s11682-013-9235-2 · Cited by 106
Self-citationLi, L., Rilling, J. K., Preuss, T. M., Glasser, M. F., & Hu, X. P. (2011) · Human Brain Mapping · doi:10.1002/hbm.21332 · Cited by 102
A taxonomy of the brain’s white matter: twenty-one major tracts for the 21st century
Bullock, D. N., Hayday, E., Grier, M. D., Tang, W., Pestilli, F., & Heilbronner, S. R. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab500 · Cited by 99
Self-citationSchilling, K. G., Petit, L., Rheault, F., Remedios, S. W., Pierpaoli, C. M., Anderson, A. W., Landman, B. A., & Descoteaux, M. (2020) · Brain Structure and Function · doi:10.1007/s00429-020-02129-z · Cited by 96
Self-citationTractostorm: The what, why, and how of tractography dissection reproducibility
Rheault, F., BENEDICTIS, A. D., Daducci, A., Maffei, C., Tax, C. M. W., Romascano, D., Caverzasi, E., Morency, F. C., Corrivetti, F., Pestilli, F., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.24917 · Cited by 95
Self-citationDiffusion MRI and anatomic tracing in the same brain reveal common failure modes of tractography
Grisot, G., Haber, S. N., & Yendiki, A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118300 · Cited by 87
Girard, G., Caminiti, R., Battaglia-Mayer, A., St-Onge, E., Ambrosen, K. S., Eskildsen, S. F., Krug, K., Dyrby, T. B., Descoteaux, M., Thiran, J.-P., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117201 · Cited by 83
Self-citationBajada, C. J., Ralph, M. A. L., & Cloutman, L. L. (2015) · Cortex · doi:10.1016/j.cortex.2015.05.011 · Cited by 82
Self-citationYeh, C., Smith, R. E., Liang, X., Calamante, F., & Connelly, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.047 · Cited by 81
Self-citationYang, J. Y.-M., Yeh, C.-H., Poupon, C., & Calamante, F. (2021) · Physics in Medicine & Biology · doi:10.1088/1361-6560/ac0d90 · Cited by 80
Self-citationAydogan, D. B., Jacobs, R., Dulawa, S., Thompson, S. L., Francois, M. C., Toga, A. W., Dong, H., Knowles, J. A., & Shi, Y. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1663-8 · Cited by 72
Self-citationNeher, P., Descoteaux, M., Houde, J., Stieltjes, B., & Maier-Hein, K. H. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.10.011 · Cited by 68
Self-citationProceedings of the 16th International Conference on Neural Information Processing Systems
Thrun, S., Saul, L. K., & Schölkopf, B. (2003) · Cited by 64
Toward a Common Terminology for the Gyri and Sulci of the Human Cerebral Cortex
ten Donkelaar, H. J., Tzourio‐Mazoyer, N., & Mai, J. K. (2018) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2018.00093 · Cited by 57
Nath, V., Schilling, K. G., Parvathaneni, P., Huo, Y., Blaber, J. A., Hainline, A. E., Baraković, M., Romascano, D., Rafael‐Patiño, J., Frigo, M., et al. (2019) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26794 · Cited by 52
Self-citationManual for clinical language tractography
Fekonja, L. S., Wang, Z., Bährend, I., Rosenstock, T., Rösler, J., Wallmeroth, L., Vajkoczy, P., & Picht, T. (2019) · Acta Neurochirurgica · doi:10.1007/s00701-019-03899-0 · Cited by 50
Self-citationSchilling, K. G., Gao, Y., Stepniewska, I., Janve, V. A., Landman, B. A., & Anderson, A. W. (2018) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2018.09.004 · Cited by 48
Self-citationSarubbo, S., Petit, L., BENEDICTIS, A. D., Chioffi, F., Ptito, M., & Dyrby, T. B. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01856-2 · Cited by 48
Self-citationMaffei, C., Jovicich, J., Benedictis, A. D., Corsini, F., Barbareschi, M., Chioffi, F., & Sarubbo, S. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1471-6 · Cited by 46
Self-citationValidation of structural brain connectivity networks: The impact of scanning parameters
Ambrosen, K. S., Eskildsen, S. F., Hinne, M., Krug, K., Lundell, H., Schmidt, M. N., van Gerven, M. A. J., Mørup, M., & Dyrby, T. B. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116207 · Cited by 42
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Vanderweyen, D., Theaud, G., Sidhu, J., Rheault, F., Sarubbo, S., Descoteaux, M., & Fortin, D. (2020) · Brain Structure and Function · doi:10.1007/s00429-020-02056-z · Cited by 41
Self-citationPoline, J., Strother, S. C., Dehaene‐Lambertz, G., Egan, G. F., & Lancaster, J. L. (2006) · Human Brain Mapping · doi:10.1002/hbm.20268 · Cited by 37
Altieri, R., Melcarne, A., Junemann, C. V., Zeppa, P., Zenga, F., Garbossa, D., Certo, F., & Barbagallo, G. M. V. (2019) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2019.07.039 · Cited by 35
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Jones, D. K., Chitnis, X. A., Job, D. E., Khong, P. L., Leung, L., Marenco, S., Smith, S. M., & Symms, M. R. (2007) · Cited by 26
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Smith, R. E., Calamante, F., & Connelly, A. (2019) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27916 · Cited by 20
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- Maier-Hein, 2017, The challenge of mapping the human connectome based on diffusion tractography, Nat. Commun., 8, 1349, 10.1038/s41467-017-01285-x · DOI
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Self-citation
Metadata
- Authors
- Schilling, K. G., Rheault, F., Petit, L., Hansen, C. B., Nath, V., Yeh, F.-C., Girard, G., Barakovic, M., Rafael-Patino, J., Yu, T., Fischi-Gomez, E., Pizzolato, M., Ocampo-Pineda, M., Schiavi, S., Canales-Rodríguez, E. J., Daducci, A., Granziera, C., Innocenti, G., Thiran, J.-P., Mancini, L., Wastling, S., Cocozza, S., Petracca, M., Pontillo, G., Mancini, M., Vos, S. B., Vakharia, V. N., Duncan, J. S., Melero, H., Manzanedo, L., Sanz-Morales, E., Peña-Melián, Á., Calamante, F., Attyé, A., Cabeen, R. P., Korobova, L., Toga, A. W., Vijayakumari, A. A., Parker, D., Verma, R., Radwan, A., Sunaert, S., Emsell, L., De Luca, A., Leemans, A., Bajada, C. J., Haroon, H., Azadbakht, H., Chamberland, M., Genc, S., Tax, C. M. W., Yeh, P.-H., Srikanchana, R., Mcknight, C. D., Yang, J. Y.-M., Chen, J., Kelly, C. E., Yeh, C.-H., Cochereau, J., Maller, J. J., Welton, T., Almairac, F., Seunarine, K. K., Clark, C. A., Zhang, F., Makris, N., Golby, A., Rathi, Y., O'Donnell, L. J., Xia, Y., Aydogan, D. B., Shi, Y., Fernandes, F. G., Raemaekers, M., Warrington, S., Michielse, S., Ramírez-Manzanares, A., Concha, L., Aranda, R., Meraz, M. R., Lerma-Usabiaga, G., Roitman, L., Fekonja, L. S., Calarco, N., Joseph, M., Nakua, H., Voineskos, A. N., Karan, P., Grenier, G., Legarreta, J. H., Adluru, N., Nair, V. A., Prabhakaran, V., Alexander, A. L., Kamagata, K., Saito, Y., Uchida, W., Andica, C., Abe, M., Bayrak, R. G., Wheeler-Kingshott, C. A. M. G., D'Angelo, E., Palesi, F., Savini, G., Rolandi, N., Guevara, P., Houenou, J., López-López, N., Mangin, J.-F., Poupon, C., Román, C., Vázquez, A., Maffei, C., Arantes, M., Andrade, J. P., Silva, S. M., Calhoun, V. D., Caverzasi, E., Sacco, S., Lauricella, M., Pestilli, F., Bullock, D., Zhan, Y., Brignoni-Perez, E., Lebel, C., Reynolds, J. E., Nestrasil, I., Labounek, R., Lenglet, C., Paulson, A., Aulicka, S., Heilbronner, S. R., Heuer, K., Chandio, B. Q., Guaje, J., Tang, W., Garyfallidis, E., Raja, R., Anderson, A. W., Landman, B. A., & Descoteaux, M.
- Affiliations
- Vanderbilt University Medical Center (US)
- Université de Sherbrooke (CA)
- Centre National de la Recherche Scientifique (FR)
- Vanderbilt University (US)
- University of Pittsburgh (US)
- Centre d'Imagerie BioMedicale (CH)
- École Polytechnique Fédérale de Lausanne (CH)
- Technical University of Denmark (DK)
- University of Verona (IT)
- University of Basel (CH)
- Karolinska Institutet (SE)
- National Hospital for Neurology and Neurosurgery (GB)
- University of Naples Federico II (IT)
- University of Malta (MT)
- Brighton and Sussex Medical School (GB)
- University College London (GB)
- Epilepsy Society (GB)
- Universidad Complutense de Madrid (ES)
- Universidad Rey Juan Carlos (ES)
- The University of Sydney (AU)
- University of Southern California (US)
- Murdoch Children's Research Institute (AU)
- University of Pennsylvania (US)
- KU Leuven (BE)
- University Medical Center Utrecht (NL)
- Manchester Academic Health Science Centre (GB)
- Cardiff University (GB)
- Walter Reed National Military Medical Center (US)
- Royal Children's Hospital (AU)
- National Neuroscience Institute (SG)
- Université Côte d'Azur (FR)
- Brigham and Women's Hospital (US)
- University of Nottingham (GB)
- Maastricht University (NL)
- Mathematics Research Center (MX)
- Universidad Nacional Autónoma de México (MX)
- Centro de Investigación Científica y de Educación Superior de Ensenada (MX)
- Stanford University (US)
- Charité – Universitätsmedizin Berlin (DE)
- Centre for Addiction and Mental Health (CA)
- University of Wisconsin–Madison (US)
- University of Pavia (IT)
- Fondazione Istituto Neurologico Nazionale Casimiro Mondino (IT)
- University of Concepción (CL)
- Harvard University (US)
- Universidade do Porto (PT)
- Georgia Institute of Technology (US)
- University of California, San Francisco (US)
- The University of Texas at Austin (US)
- Chinese Academy of Sciences (CN)
- University of Calgary (CA)
- University of Minnesota (US)
- Inserm (FR)
- Indiana University Bloomington (US)
- University of Arkansas for Medical Sciences (US)
- Corresponding author
- Schilling, Kurt G.
- ORCID
- Schilling, Kurt G.
- Rheault, François
- Petit, Laurent
- Hansen, Colin B.
- Nath, Vishwesh
- Yeh, Fang-Cheng
- Girard, Gabriel
- Yu, Thomas
- Pizzolato, Marco
- Schiavi, Simona
- Canales-Rodríguez, Erick J.
- Daducci, Alessandro
- Granziera, Cristina
- Thiran, Jean-Philippe
- Mancini, Laura
- Wastling, Stephen
- Cocozza, Sirio
- Petracca, Maria
- Pontillo, Giuseppe
- Mancini, Matteo
- Vos, Sjoerd B.
- Vakharia, Vejay N.
- Duncan, John S.
- Melero, Helena
- Peña-Melián, Ángel
- Calamante, Fernando
- Attyé, Arnaud
- Cabeen, Ryan P.
- Toga, Arthur W.
- Vijayakumari, Anupa Ambili
- Parker, Drew
- Verma, Ragini
- Radwan, Ahmed
- Sunaert, Stefan
- Emsell, Louise
- Leemans, Alexander
- Bajada, Claude J.
- Haroon, Hamied
- Chamberland, Maxime
- Genc, Sila
- Tax, Chantal M.W.
- Yeh, Ping-Hong
- Srikanchana, Rujirutana
- Mcknight, Colin D.
- Yang, Joseph Yuan-Mou
- Chen, Jian
- Kelly, Claire E.
- Yeh, Chun-Hung
- Maller, Jerome J.
- Welton, Thomas
- Almairac, Fabien
- Seunarine, Kiran K
- Clark, Chris A.
- Zhang, Fan
- Makris, Nikos
- Golby, Alexandra
- Xia, Yihao
- Aydogan, Dogu Baran
- Shi, Yonggang
- Fernandes, Francisco Guerreiro
- Raemaekers, Mathijs
- Warrington, Shaun
- Michielse, Stijn
- Ramírez-Manzanares, Alonso
- Concha, Luis
- Aranda, Ramón
- Fekonja, Lucius S.
- Calarco, Navona
- Joseph, Michael
- Nakua, Hajer
- Voineskos, Aristotle N.
- Karan, Philippe
- Legarreta, Jon Haitz
- Adluru, Nagesh
- Nair, Veena A.
- Prabhakaran, Vivek
- Alexander, Andrew L.
- Kamagata, Koji
- Saito, Yuya
- Uchida, Wataru
- Andica, Christina
- Abe, Masahiro
- Bayrak, Roza G.
- D'Angelo, Egidio
- Palesi, Fulvia
- Savini, Giovanni
- Rolandi, Nicolò
- Guevara, Pamela
- Houenou, Josselin
- López-López, Narciso
- Mangin, Jean-François
- Poupon, Cyril
- Román, Claudio
- Maffei, Chiara
- Arantes, Mavilde
- Andrade, José Paulo
- Silva, Susana Maria
- Calhoun, Vince D.
- Caverzasi, Eduardo
- Sacco, Simone
- Pestilli, Franco
- Bullock, Daniel
- Zhan, Yang
- Lebel, Catherine
- Reynolds, Jess E
- Labounek, René
- Lenglet, Christophe
- Paulson, Amy
- Heuer, Katja
- Chandio, Bramsh Qamar
- Guaje, Javier
- Tang, Wei
- Garyfallidis, Eleftherios
- Raja, Rajikha
- Anderson, Adam W.
- Landman, Bennett A.
- Descoteaux, Maxime
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 243
- Pages
- 118502
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC8855321
- OpenAlex
- W3091774503
- Cited by
- 182
- References
- 101
- Citations by year
- 2026: 24 · 2025: 31 · 2024: 38 · 2023: 27 · 2022: 45 · 2021: 15
- FWCI
- 16.51
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by-nc-nd)
- Repository@Nottingham (University of Nottingham) (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- IRIS Research product catalog (Sapienza University of Rome) (submittedVersion, cc-by)
- Lirias (submittedVersion, cc-by-nc-nd)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by-nc-nd)
- HAL (submittedVersion, other-oa)
- Aaltodoc (Aalto University) (submittedVersion, cc-by)
- Communities in ADDI (Universidad del Pais Vasco) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- IRIS (submittedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by-nc-nd)
- Research Explorer (The University of Manchester) (submittedVersion)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, cc-by)
- SERVAL (Université de Lausanne) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- Research Publications (Maastricht University) (submittedVersion, cc-by-nc-nd)
- Greater South Information System
- Funders
- National Science Foundation (1916518, T32EB001628, 1636893, 1912270, P30 NS076408, P41 EB027061, P41EB015898, 785907, UL1 RR024975-01, 1734853, MH103213)
- Vanderbilt University (UL1 RR024975-01, UL1 RR024975, VR3029, ViSE/VICTR VR3029)
- Vanderbilt Institute for Clinical and Translational Research (VR3029, RR024975, UL1 RR024975-01, UL1 RR024975)
- Waisman Center (HD090256, U54 HD090256)
- Université de Sherbrooke
- Wellcome Trust (17331, 215944, 213722, MR/N013913/1, 215944/Z/19/Z, 213722/Z/18/Z)
- Children’s Hospital of Wisconsin Research Institute
- Children's Hospital Foundation
- Compute Canada
- Murdoch Children's Research Institute
- Royal Children's Hospital Foundation (RCH-1000)
- National Institute for Health and Care Research (NF-SI-0515-10000)
- European Commission (HORIZON2020, 785907, 215944, 754462, HBP SGA2, 945539)
- University of Nottingham
- Deutsche Forschungsgemeinschaft (785907, EXC 2025, 945539)
- Agence Nationale de la Recherche (ANR-19-CE45-0022, 785907, 945539)
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (213722, PZ00P2, 185814, 215944)
- University of Melbourne
- Consejo Nacional de Ciencia y Tecnología (FB0008)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (17331, U54 HD090256, 785907, 215944/Z/19/Z)
- Ministry of Science and Technology, Taiwan (MOST 109, 001-MY3, MOST109-2222-E182-001-MY3)
- State Government of Victoria (RCH 1000)
- Agencia Nacional de Investigación y Desarrollo (1190701, FB0008, FONDECYT 1190701)
- National Institutes of Health (1734853, 785907, 945539, VR3029, ViSE/VICTR VR3029, HD090256, RR024975, EB027061, NS076408)
- Intellectual and Developmental Disabilities Research Center
- Natural Sciences and Engineering Research Council of Canada (EB027061, P41EB015902)
- Medical Research Council (1957092, MR/N013913/1, 785907, 945539)
- Australian Research Council (DP170101815)
- National Health and Medical Research Council (1117724, 1091593)
- Japan Society for the Promotion of Science (20F20113)
- Fundação para a Ciência e a Tecnologia (UID/IC/4255/2013)
- National Institute on Aging (P30AG066530)
- National Institute of Mental Health (K24MH116366, R01MH111917, 945539, MH103213, R01MH119222, NIMH T32, 1734853, T32MH103213)
- National Institute of Neurological Disorders and Stroke (P30NS076408)
- National Institute of Biomedical Imaging and Bioengineering (1734853, P41EB015902, VR3029, R01EB029272, R01EB017230, EB027061, P41EB015922, P41EB015898, T32EB001628, P41EB028741, P41EB027061)
- National Institute of Child Health and Human Development (HD090256)
- National Center for Research Resources (215944/Z/19/Z, Grant UL1 RR024975-01, RR024975, P41RR013218, UL1RR024975, RR024975‐01, 17331)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD090256, P50HD103537)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- tractography, virtual dissection, diffusion MRI, reproducibility, human brain white matter
- MeSH terms
- Algorithms, Dissection, Humans, Image Processing, Computer-Assisted, Neural Pathways, Diffusion Tensor Imaging, White Matter
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