Toward global tractography

Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.

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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 · see citing works

Nonuniversal critical dynamics in Monte Carlo simulations

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The Human Connectome Project: A data acquisition perspective

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Axcaliber: A method for measuring axon diameter distribution from diffusion MRI

Assaf, Y., Blumenfeld‐Katzir, T., Yovel, Y., & Basser, P. J. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21577 · Cited by 849 · see citing works

Deterministic and probabilistic tractography based on complex fibre orientation distributions

Descoteaux, M., Deriche, R., Knosche, T. R., & Anwander, A. (2009) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.2004424 · Cited by 698 · see citing works

Tractography: Where Do We Go from Here?

Jbabdi, S., & Johansen-Berg, H. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0033 · Cited by 614 · see citing works

The Geometric Structure of the Brain Fiber Pathways

Wedeen, V. J., Rosene, D. L., Wang, R., Dai, G., Mortazavi, F., Hagmann, P., Kaas, J. H., & Tseng, W.-Y. I. (2012) · Science · doi:10.1126/science.1215280 · Cited by 445 · see citing works

Detection of linear features in SAR images: application to road network extraction

Florence Tupin, D., Maı̂tre, H., Mangin, J.-F., Nicolas, J., & Pechersky, E. A. (1998) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/36.662728 · Cited by 428 · see citing works

Regularization of Diffusion-Based Direction Maps for the Tracking of Brain White Matter Fascicles

Poupon, C., Clark, C., Frouin, V., Régis, J. M., Isabelle Bloch, A., Bihan, D. L., & Mangin, J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0607 · Cited by 426 · see citing works

Quantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom

Fillard, P., Descoteaux, M., Goh, A., Gouttard, S., Jeurissen, B., Malcolm, J., Ramirez-Manzanares, A., Reisert, M., Sakaie, K., Tensaouti, F., et al. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.032 · Cited by 418 · see citing works

Model-based analysis of multishell diffusion MR data for tractography: how to get over fitting problems

Jbabdi, S., Sotiropoulos, S. N., Savio, A. M., Graña, M., & Behrens, T. E. J. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24204 · Cited by 399 · see citing works

Global fiber reconstruction becomes practical

Reisert, M., Mader, I., Anastasopoulos, C., Weigel, M., Schnell, S., & Kiselev, V. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.09.016 · Cited by 312 · see citing works

Estimating distributed anatomical connectivity using fast marching methods and diffusion tensor imaging

Parker, G. J. M., Wheeler‐Kingshott, C. A. M. G., & Barker, G. J. (2002) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2002.1009386 · Cited by 303 · see citing works

A novel approach to the human connectome: Ultra-high resolution mapping of fiber tracts in the brain

Axer, M., Amunts, K., Gräßel, D., Palm, C., Dammers, J., Axer, H., Pietrzyk, U., & Zilles, K. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.075 · Cited by 280 · see citing works

Axon diameter mapping in the presence of orientation dispersion with diffusion MRI

Zhang, H. G., Cristinacce, P. L. H., Parker, G. J. M., & Alexander, D. C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.084 · Cited by 258 · see citing works

A Bayesian framework for global tractography

Jbabdi, S., Woolrich, M. W., Andersson, J., & Behrens, T. E. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.039 · Cited by 251 · see citing works

Clinical DT-MRI Estimation, Smoothing, and Fiber Tracking With Log-Euclidean Metrics

Fillard, P., Pennec, X., Arsigny, V., & Ayache, N. (2007) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2007.899173 · Cited by 249 · see citing works

Automatic fiber bundle segmentation in massive tractography datasets using a multi-subject bundle atlas

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 · see citing works

New diffusion phantoms dedicated to the study and validation of high‐angular‐resolution diffusion imaging (HARDI) models

Poupon, C., Rieul, B., Kezele, I., Perrin, M., Poupon, F., & Mangin, J. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21789 · Cited by 198 · see citing works

The future of the human connectome

Essen, D. C. V., & Uǧurbil, K. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.032 · Cited by 195 · see citing works

High-Resolution Fiber Tract Reconstruction in the Human Brain by Means of Three-Dimensional Polarized Light Imaging

Axer, M., Gräßel, D., Kleiner, M., Dammers, J., Dickscheid, T., Reckfort, J., Hütz, T., Eiben, B., Pietrzyk, U., Zilles, K., et al. (2011) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2011.00034 · Cited by 193 · see citing works

Flow-based fiber tracking with diffusion tensor and q-ball data: Validation and comparison to principal diffusion direction techniques

Campbell, J. S. W., Siddiqi, K., Rymar, V. V., Sadikot, A. F., & Pike, G. B. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.05.014 · Cited by 177 · see citing works

Surface based analysis of diffusion orientation for identifying architectonic domains in the in vivo human cortex

McNab, J. A., Polimeni, J. R., Wang, R., Augustinack, J. C., Fujimoto, K., Stevens, A. A., Janssens, T., Farivar, R., Folkerth, R. D., Vanduffel, W., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.11.065 · Cited by 158 · see citing works

Gibbs tracking: A novel approach for the reconstruction of neuronal pathways

Kreher, B., Mader, I., & Kiselev, V. G. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21749 · Cited by 157 · see citing works

A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography

Aganj, I., Lenglet, C., Jahanshad, N., Yacoub, E. S., Harel, N., Thompson, P. M., & Sapiro, G. (2011) · Medical Image Analysis · doi:10.1016/j.media.2011.01.003 · Cited by 143 · see citing works

Accurate Anisotropic Fast Marching for Diffusion‐Based Geodesic Tractography

Jbabdi, S., Bellec, P., Toro, R., Jean Daunizeau, A., Pélégrini‐Issac, M., & Benali, H. (2007) · International Journal of Biomedical Imaging · doi:10.1155/2008/320195 · Cited by 125 · see citing works

Towards inference of human brain connectivity from MR diffusion tensor data

Poupon, C., Mangin, J.-F., Clark, C., Frouin, V., Régis, J. M., Bihan, D. L., & Isabelle Bloch, A. (2001) · Medical Image Analysis · doi:10.1016/s1361-8415(00)00030-x · Cited by 111 · see citing works

A Novel Global Tractography Algorithm Based on an Adaptive Spin Glass Model

Fillard, P., Poupon, C., & Mangin, J. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04268-3_114 · Cited by 105 · see citing works

A pitfall in the reconstruction of fibre ODFs using spherical deconvolution of diffusion MRI data

Parker, G. D., Marshall, D., Rosin, P. L., Drage, N. A., Richmond, S., & Jones, D. K. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.022 · Cited by 104 · see citing works

Diffusion tensor magnetic resonance image regularization

Coulon, O., Alexander, D. C., & Arridge, S. (2003) · Medical Image Analysis · doi:10.1016/j.media.2003.06.002 · Cited by 96 · see citing works

Diffusion tractography of post-mortem human brains: Optimization and comparison of spin echo and steady-state free precession techniques

Miller, K. L., McNab, J. A., Jbabdi, S., & Douaud, G. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.054 · Cited by 86 · see citing works

Regularization of MR diffusion tensor maps for tracking brain white matter bundles

Poupon, C., Mangin, J., Frouin, V., Régis, J. M., Poupon, F., Pachot‐Clouard, M., Bihan, D. L., & Isabelle Bloch, A. (1998) · Lecture notes in computer science · doi:10.1007/bfb0056234 · Cited by 75 · see citing works

Orthonormal Vector Sets Regularization with PDE's and Applications

Tschumperlé, D., & Deriche, R. (2002) · International Journal of Computer Vision · doi:10.1023/a:1020870207168 · Cited by 74 · see citing works

A framework based on spin glass models for the inference of anatomical connectivity from diffusion‐weighted MR data – a technical review

Mangin, J., Poupon, C., Cointepas, Y., Rivière, D., Orfanos, D. P., Clark, C., Régis, J. M., & Bihan, D. L. (2002) · NMR in Biomedicine · doi:10.1002/nbm.780 · Cited by 73 · see citing works

Fiber Continuity: An Anisotropic Prior for ODF Estimation

Reisert, M., & Kiselev, V. G. (2011) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2011.2112769 · Cited by 65 · see citing works

A nonparametric Riemannian framework for processing high angular resolution diffusion images and its applications to ODF-based morphometry

Goh, A., Lenglet, C., Thompson, P. M., & Vidal, R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.053 · Cited by 49 · see citing works

Quantitative assessment of a framework for creating anatomical brain networks via global tractography

Li, L., Rilling, J. K., Preuss, T. M., Glasser, M. F., Damen, F. W., & Hu, X. P. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.071 · Cited by 41 · see citing works

Tractography-Based Parcellation of the Cortex Using a Spatially-Informed Dimension Reduction of the Connectivity Matrix

Roca, P., Rivière, D., Guevara, P., Poupon, C., & Mangin, J. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04268-3_115 · Cited by 32 · see citing works

3D Stochastic Completion Fields for Mapping Connectivity in Diffusion MRI

MomayyezSiahkal, P., & Kaleem Siddiqi, A. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.184 · Cited by 17 · see citing works

A Spin Glass Based Framework to Untangle Fiber Crossing in MR Diffusion Based Tracking

Cointepas, Y., Poupon, C., Bihan, D. L., & Mangin, J. (2002) · Lecture notes in computer science · doi:10.1007/3-540-45786-0_59 · Cited by 14 · see citing works

Inferring the Brain Connectivity from MR Diffusion Tensor Data

Poupon, C., Clark, C., Frouin, V., Bihan, D. L., Isabelle Bloch, A., & Mangin, J.-F. (1999) · Lecture notes in computer science · doi:10.1007/10704282_49 · Cited by 9 · see citing works

Angular smoothing and radial regularization of ODF fields: Application on deterministic crossing fiber tractography

Otto, K.-M., Ehricke, H.-H., Kumar, V., & Klose, U. (2011) · Physica Medica · doi:10.1016/j.ejmp.2011.10.002 · Cited by 7 · see citing works

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 1,361 · see citing works

Functional connectomics from resting-state fMRI

Smith, S. M., Vidaurre, D., Beckmann, C. F., Glasser, M. F., Jenkinson, M., Miller, K. L., Nichols, T. E., Robinson, E. C., Salimi-Khorshidi, G., Woolrich, M. W., et al. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.09.016 · Cited by 952 · see citing works

Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited

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 · see citing works

Diffusion MRI fiber tractography of the brain

Jeurissen, B., Descoteaux, M., Mori, S., & Leemans, A. (2019) · NMR in Biomedicine · doi:10.1002/nbm.3785 · Cited by 574 · see citing works

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 · see citing works

Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review

Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R. E., Yeh, C.-H., Zhao, T., & O’Donnell, L. J. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2021.118870 · Cited by 302 · see citing works

Evaluation 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 · see citing works

COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography

Daducci, A., Dal Palu, A., Lemkaddem, A., & Thiran, J.-P. (2015) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2014.2352414 · Cited by 255 · see citing works

White matter tractography for neurosurgical planning: A topography-based review of the current state of the art

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 · see citing works

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 176 · see citing works

The DTI Challenge: Toward Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery

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 · see citing works

Global tractography of multi-shell diffusion-weighted imaging data using a multi-tissue model

Christiaens, D., Reisert, M., Dhollander, T., Sunaert, S., Suetens, P., & Maes, F. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.08.008 · Cited by 152 · see citing works

Microstructure informed tractography: pitfalls and open challenges

Daducci, A., Dal Palú, A., Descoteaux, M., & Thiran, J.-P. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00247 · Cited by 138 · see citing works

Connectome imaging for mapping human brain pathways

Shi, Y., & Toga, A. W. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.92 · Cited by 131 · see citing works

Clarifying Human White Matter

Wandell, B. A. (2016) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070815-013815 · Cited by 112 · see citing works

Ensemble Tractography

Takemura, H., Caiafa, C. F., Wandell, B. A., & Pestilli, F. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004692 · Cited by 106 · see citing works

Does diffusion MRI tell us anything about the white matter? An overview of methods and pitfalls

O’Donnell, L. J., & Pasternak, O. (2014) · Schizophrenia Research · doi:10.1016/j.schres.2014.09.007 · Cited by 90 · see citing works

Tractostorm: 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 87 · see citing works

Quantitative streamlines tractography: methods and inter-subject normalisation

Smith, R. E., Raffelt, D. A., Tournier, J., & Connelly, A. (2022) · Aperture Neuro · doi:10.52294/apertureneuro.2022.2.neod9565 · Cited by 90 · see citing works

Bundle‐specific tractography with incorporated anatomical and orientational priors

Rheault, F., St-Onge, E., Sidhu, J., Maier-Hein, K. H., Tzourio-mazoyer, N., Petit, L., & Descoteaux, M. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.11.018 · Cited by 87 · see citing works

Tractography and machine learning: current state and open challenges

Poulin, P., Jörgens, D., Jodoin, P.-M., & Descoteaux, M. (2019) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2019.04.013 · Cited by 84 · see citing works

The visual white matter: The application of diffusion MRI and fiber tractography to vision science

Rokem, A., Takemura, H., Bock, A. S., Scherf, K. S., Behrmann, M., Wandell, B. A., Fine, I., Bridge, H., & Pestilli, F. (2017) · Journal of Vision · doi:10.1167/17.2.4 · Cited by 84 · see citing works

Dynamic Multi-Coil Technique (DYNAMITE) Shimming for Echo-Planar Imaging of the Human Brain at 7 Tesla

Juchem, C., Umesh Rudrapatna, S., Nixon, T. W., & de Graaf, R. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.011 · Cited by 74 · see citing works

When tractography meets tracer injections: a systematic study of trends and variation sources of diffusion-based connectivity

Aydogan, 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 · see citing works

Diffusion MRI-based cortical connectome reconstruction: dependency on tractography procedures and neuroanatomical characteristics

Sinke, M. R. T., Otte, W. M., Christiaens, D., Schmitt, O., Leemans, A., van der Toorn, A., Sarabdjitsingh, R. A., Joëls, M., & Dijkhuizen, R. M. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1628-y · Cited by 70 · see citing works

Fiber tractography using machine learning

Neher, P. F., Côté, M.-A., Houde, J.-C., Descoteaux, M., & Maier-Hein, K. H. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.028 · Cited by 68 · see citing works

Longitudinal decline in structural networks predicts dementia in cerebral small vessel disease

Lawrence, A. J., Zeestraten, E., Benjamin, P., Lambert, C., Morris, R. G., Barrick, T. R., & Markus, H. S. (2018) · Neurology · doi:10.1212/wnl.0000000000005551 · Cited by 58 · see citing works

Merits and Limits of Tractography Techniques for the Uninitiated

Nimsky, C., Bopp, M. H. A., & Carl, B. (2015) · Advances and technical standards in neurosurgery · doi:10.1007/978-3-319-21359-0_2 · Cited by 56 · see citing works

The tract terminations in the temporal lobe: Their location and associated functions

Bajada, C. J., Haroon, H. A., Azadbakht, H., Parker, G. J. M., Ralph, M. A. L., & Cloutman, L. L. (2016) · Cortex · doi:10.1016/j.cortex.2016.03.013 · Cited by 56 · see citing works

Human connectomics — What will the future demand?

Johansen‐Berg, H. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.082 · Cited by 51 · see citing works

TractoInferno - A large-scale, open-source, multi-site database for machine learning dMRI tractography

Poulin, P., Theaud, G., Rheault, F., St‐Onge, E., Boré, A., Renauld, E., Beaumont, L. D., Guay, S., Jodoin, P., & Descoteaux, M. (2022) · Scientific Data · doi:10.1038/s41597-022-01833-1 · Cited by 45 · see citing works

Track-to-Learn: A general framework for tractography with deep reinforcement learning

Théberge, A., Desrosiers, C., Descoteaux, M., & Jodoin, P. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102093 · Cited by 43 · see citing works

Multidimensional encoding of brain connectomes

Caiafa, C. F., & Pestilli, F. (2017) · Scientific Reports · doi:10.1038/s41598-017-09250-w · Cited by 42 · see citing works

The Emerging Role of Tractography in Deep Brain Stimulation: Basic Principles and Current Applications

Rodrigues, N. B., Mithani, K., Meng, Y., Lipsman, N., & Hamani, C. (2018) · Brain Sciences · doi:10.3390/brainsci8020023 · Cited by 37 · see citing works

A new compression format for fiber tracking datasets

Presseau, C., Jodoin, P., Houde, J., & Descoteaux, M. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.058 · Cited by 36 · see citing works

Preserved white matter microstructure in young patients with anorexia nervosa?

Pfuhl, G., King, J. A., Geisler, D., Roschinski, B., Ritschel, F., Seidel, M., Bernardoni, F., Müller, D. K., White, T. J. H., Roessner, V., et al. (2016) · Human Brain Mapping · doi:10.1002/hbm.23296 · Cited by 33 · see citing works

Diffusion MRI: Assessment of the Impact of Acquisition and Preprocessing Methods Using the BrainVISA-Diffuse Toolbox

Brun, L., Pron, A., Sein, J., Deruelle, C., & Coulon, O. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00536 · Cited by 30 · see citing works

Connectivity of the Superficial Muscles of the Human Perineum: A Diffusion Tensor Imaging-Based Global Tractography Study

Zifan, A., Reisert, M., Sinha, S., Ledgerwood-Lee, M. M., Cory, E., Sah, R. L., & Mittal, R. K. (2018) · Scientific Reports · doi:10.1038/s41598-018-36099-4 · Cited by 27 · see citing works

FIESTA: Autoencoders for accurate fiber segmentation in tractography

Dumais, F., Legarreta, J. H., Lemaire, C., Poulin, P., Rheault, F., Petit, L., Baraković, M., Magon, S., Descoteaux, M., & Jodoin, P. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120288 · Cited by 26 · see citing works

Probing the reproducibility of quantitative estimates of structural connectivity derived from global tractography

Schumacher, L. V., Reisert, M., Nitschke, K., Egger, K. E., Urbach, H., Hennig, J., Weiller, C., & Kaller, C. P. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.086 · Cited by 25 · see citing works

Shape analysis of the cingulum, uncinate and arcuate fasciculi in patients with bipolar disorder

Sun, Z. Y., Houenou, J., Duclap, D., Sarrazin, S., Linke, J. O., Daban, C., Hamdani, N., d’Albis, M.-A., Corvoisier, P. L., Guevara, P., et al. (2016) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.150291 · Cited by 24 · see citing works

Diffusion MRI with machine learning

Karimi, D., & Warfield, S. K. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00353 · Cited by 23 · see citing works

Towards deep learning for connectome mapping: A block decomposition framework

Sarwar, T., Seguin, C., Ramamohanarao, K., & Zalesky, A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116654 · Cited by 21 · see citing works

Optimization and validation of diffusion MRI-based fiber tracking with neural tracer data as a reference

Gutierrez, C. E., Skibbe, H., Nakae, K., Tsukada, H., Liénard, J., Watakabe, A., Hata, J., Reisert, M., Woodward, A., Yamaguchi, Y., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-78284-4 · Cited by 21 · see citing works

Repeatability Analysis of Global and Local Metrics of Brain Structural Networks

Andreotti, J., Jann, K., Melie‐García, L., Giezendanner, S., Dierks, T., & Federspiel, A. (2014) · Brain Connectivity · doi:10.1089/brain.2013.0202 · Cited by 20 · see citing works

Predicting planning performance from structural connectivity between left and right mid-dorsolateral prefrontal cortex: moderating effects of age during postadolescence and midadulthood.

Kaller, C., Reisert, M., Katzev, M., Umarova, R., Mader, I., Hennig, J., Weiller, C., & Köstering, L. (2015) · Cerebral Cortex · doi:10.1093/cercor/bht276 · Cited by 20 · see citing works

Modeling topographic regularity in structural brain connectivity with application to tractogram filtering

Wang, J., Aydogan, D. B., Varma, R., Toga, A. W., & Shi, Y. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.07.068 · Cited by 20 · see citing works

Tractography of Association Fibers Associated with Language Processing

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CTtrack: A CNN+Transformer-based framework for fiber orientation estimation & tractography

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