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Computational Diffusion MRI: International MICCAI Workshop, Granada, Spain, September 2018

1st ed. 2019., 2019

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The importance of correcting for signal drift in diffusion MRI

Magnetic resonance in medicine, 2017-01, Vol.77 (1), p.285-299

2017

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Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data

NeuroImage (Orlando, Fla.), 2014-02, Vol.86, p.67-80

2014

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Scanner invariant representations for diffusion MRI harmonization

Magnetic resonance in medicine, 2020-10, Vol.84 (4), p.2174-2189

2020

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Seeing More by Showing Less: Orientation-Dependent Transparency Rendering for Fiber Tractography Visualization

PloS one, 2015-10, Vol.10 (10), p.e0139434-e0139434

2015

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Methodological considerations on tract-based spatial statistics (TBSS)

NeuroImage (Orlando, Fla.), 2014-10, Vol.100, p.358-369

2014

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The dot-compartment revealed? Diffusion MRI with ultra-strong gradients and spherical tensor encoding in the living human brain

NeuroImage (Orlando, Fla.), 2020-04, Vol.210, p.116534-116534, Article 116534

2020

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Evaluating contextual processing in diffusion MRI: application to optic radiation reconstruction for epilepsy surgery

PloS one, 2014-07, Vol.9 (7), p.e101524-e101524

2014

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REKINDLE: Robust extraction of kurtosis INDices with linear estimation

Magnetic resonance in medicine, 2015-02, Vol.73 (2), p.794-808

2015

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Tractostorm: The what, why, and how of tractography dissection reproducibility

Human brain mapping, 2020-05, Vol.41 (7), p.1859-1874

2020

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Effects of tDCS on Language Recovery in Post-Stroke Aphasia: A Pilot Study Investigating Clinical Parameters and White Matter Change with Diffusion Imaging

Brain sciences, 2021-09, Vol.11 (10), p.1277

2021

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Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain

NeuroImage (Orlando, Fla.), 2019-10, Vol.200, p.89-100

2019

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Surface-based tracking for short association fibre tractography

NeuroImage (Orlando, Fla.), 2022-10, Vol.260, p.119423-119423, Article 119423

2022

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Macro- and micro-structural insights into primary dystonia: a UK Biobank study

Journal of neurology, 2024-03, Vol.271 (3), p.1416-1427

2024

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“MASSIVE” brain dataset: Multiple acquisitions for standardization of structural imaging validation and evaluation

Magnetic resonance in medicine, 2017-05, Vol.77 (5), p.1797-1809

2017

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Strong diffusion gradients allow the separation of intra- and extra-axonal gradient-echo signals in the human brain

NeuroImage (Orlando, Fla.), 2020-08, Vol.217, p.116793-116793, Article 116793

2020

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Automated characterization of noise distributions in diffusion MRI data

Medical image analysis, 2020-10, Vol.65, p.101758-101758, Article 101758

2020

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Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients

Frontiers in neuroscience, 2023-12, Vol.17, p.1258408-1258408

2023

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Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology

Frontiers in neuroscience, 2023-08, Vol.17, p.1209521-1209521

2023

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What’s new and what’s next in diffusion MRI preprocessing

NeuroImage (Orlando, Fla.), 2022-04, Vol.249, p.118830-118830, Article 118830

2022

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Computational Diffusion MRI: MICCAI Workshop, Québec, Canada, September 2017

1, 2018

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Sheet Probability Index (SPI): Characterizing the geometrical organization of the white matter with diffusion MRI

NeuroImage (Orlando, Fla.), 2016-11, Vol.142, p.260-279

2016

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Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data

Frontiers in radiology, 2024-06, Vol.4, p.1416672

2024

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Quantifying the brain's sheet structure with normalized convolution

Medical image analysis, 2017-07, Vol.39, p.162-177

2017

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Transferring principles of solid-state and Laplace NMR to the field of in vivo brain MRI

Magnetic Resonance : (Göttingen), 2020, Vol.1 (1), p.27-43

2020

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Computational Diffusion MRI: International MICCAI Workshop, Granada, Spain, September 2018

The importance of correcting for signal drift in diffusion MRI

Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data

Scanner invariant representations for diffusion MRI harmonization

Seeing More by Showing Less: Orientation-Dependent Transparency Rendering for Fiber Tractography Visualization

Methodological considerations on tract-based spatial statistics (TBSS)

The dot-compartment revealed? Diffusion MRI with ultra-strong gradients and spherical tensor encoding in the living human brain

Evaluating contextual processing in diffusion MRI: application to optic radiation reconstruction for epilepsy surgery

REKINDLE: Robust extraction of kurtosis INDices with linear estimation

Tractostorm: The what, why, and how of tractography dissection reproducibility

Effects of tDCS on Language Recovery in Post-Stroke Aphasia: A Pilot Study Investigating Clinical Parameters and White Matter Change with Diffusion Imaging

Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain

Surface-based tracking for short association fibre tractography

Macro- and micro-structural insights into primary dystonia: a UK Biobank study

“MASSIVE” brain dataset: Multiple acquisitions for standardization of structural imaging validation and evaluation

Strong diffusion gradients allow the separation of intra- and extra-axonal gradient-echo signals in the human brain

Automated characterization of noise distributions in diffusion MRI data

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients

Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology

What’s new and what’s next in diffusion MRI preprocessing

Computational Diffusion MRI: MICCAI Workshop, Québec, Canada, September 2017

Sheet Probability Index (SPI): Characterizing the geometrical organization of the white matter with diffusion MRI

Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data

Quantifying the brain's sheet structure with normalized convolution

Transferring principles of solid-state and Laplace NMR to the field of in vivo brain MRI

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