Colin B. Hansen
Colin B. Hansen
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Limits to anatomical accuracy of diffusion tractography using modern approaches
KG Schilling, V Nath, C Hansen, P Parvathaneni, J Blaber, Y Gao, ...
Neuroimage 185, 1-11, 2019
Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?
KG Schilling, F Rheault, L Petit, CB Hansen, V Nath, FC Yeh, G Girard, ...
NeuroImage 243, 118502, 2021
Synthesized b0 for diffusion distortion correction (Synb0-DisCo)
KG Schilling, J Blaber, Y Huo, A Newton, C Hansen, V Nath, AT Shafer, ...
Magnetic resonance imaging 64, 62-70, 2019
A fiber coherence index for quality control of B-table orientation in diffusion MRI scans
KG Schilling, FC Yeh, V Nath, C Hansen, O Williams, S Resnick, ...
Magnetic resonance imaging 58, 82-89, 2019
Distortion correction of diffusion weighted MRI without reverse phase-encoding scans or field-maps
KG Schilling, J Blaber, C Hansen, L Cai, B Rogers, AW Anderson, S Smith, ...
PLoS One 15 (7), e0236418, 2020
PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images
LY Cai, Q Yang, CB Hansen, V Nath, K Ramadass, GW Johnson, ...
Magnetic resonance in medicine 86 (1), 456-470, 2021
Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results
L Ning, E Bonet-Carne, F Grussu, F Sepehrband, E Kaden, J Veraart, ...
Neuroimage 221, 117128, 2020
Deep learning reveals untapped information for local white-matter fiber reconstruction in diffusion-weighted MRI
V Nath, KG Schilling, P Parvathaneni, CB Hansen, AE Hainline, Y Huo, ...
Magnetic resonance imaging 62, 220-227, 2019
Inter-scanner harmonization of high angular resolution DW-MRI using null space deep learning
V Nath, P Parvathaneni, CB Hansen, AE Hainline, C Bermudez, ...
Computational Diffusion MRI: International MICCAI Workshop, Granada, Spain …, 2019
Fiber tractography bundle segmentation depends on scanner effects, vendor effects, acquisition resolution, diffusion sampling scheme, diffusion sensitization, and bundle …
KG Schilling, CMW Tax, F Rheault, C Hansen, Q Yang, FC Yeh, L Cai, ...
NeuroImage 242, 118451, 2021
Pandora: 4-D white matter bundle population-based atlases derived from diffusion MRI fiber tractography
CB Hansen, Q Yang, I Lyu, F Rheault, C Kerley, BQ Chandio, S Fadnavis, ...
Neuroinformatics 19, 447-460, 2021
MASiVar: Multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted MRI
LY Cai, Q Yang, P Kanakaraj, V Nath, AT Newton, HA Edmonson, J Luci, ...
Magnetic resonance in medicine 86 (6), 3304-3320, 2021
Phantom-based field maps for gradient nonlinearity correction in diffusion imaging
BP Rogers, J Blaber, AT Newton, CB Hansen, EB Welch, AW Anderson, ...
Medical Imaging 2018: Physics of Medical Imaging 10573, 945-949, 2018
Characterization and correlation of signal drift in diffusion weighted MRI
CB Hansen, V Nath, AE Hainline, KG Schilling, P Parvathaneni, ...
Magnetic resonance imaging 57, 133-142, 2019
Harmonizing 1.5 T/3T diffusion weighted MRI through development of deep learning stabilized microarchitecture estimators
V Nath, S Remedios, P Parvathaneni, CB Hansen, RG Bayrak, ...
Medical Imaging 2019: Image Processing 10949, 173-182, 2019
Aging and white matter microstructure and macrostructure: a longitudinal multi-site diffusion MRI study of 1218 participants
KG Schilling, D Archer, FC Yeh, F Rheault, LY Cai, C Hansen, Q Yang, ...
Brain Structure and Function 227 (6), 2111-2125, 2022
Empirical field mapping for gradient nonlinearity correction of multi-site diffusion weighted MRI
CB Hansen, BP Rogers, KG Schilling, V Nath, JA Blaber, O Irfanoglu, ...
Magnetic resonance imaging 76, 69-78, 2021
Enabling multi-shell b-value generalizability of data-driven diffusion models with deep SHORE
V Nath, I Lyu, KG Schilling, P Parvathaneni, CB Hansen, Y Huo, VA Janve, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
MASiVar: multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted magnetic resonance imaging
LY Cai, Q Yang, P Kanakaraj, V Nath, AT Newton, HA Edmonson, J Luci, ...
bioRxiv, 2020.12. 03.408567, 2020
Deep learning captures more accurate diffusion fiber orientations distributions than constrained spherical deconvolution
V Nath, KG Schilling, CB Hansen, P Parvathaneni, AE Hainline, ...
arXiv preprint arXiv:1911.07927, 2019
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