| How can spherical CNNs benefit ML-based diffusion MRI parameter estimation? T Goodwin-Allcock, J McEwen, R Gray, P Nachev, H Zhang arXiv preprint arXiv:2207.00572, 2022 | 9 | 2022 |
| Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies S Aja-Fernández, C Martín-Martín, Á Planchuelo-Gómez, A Faiyaz, ... NeuroImage: Clinical 39, 103483, 2023 | 6 | 2023 |
| Patch-CNN: Training data-efficient deep learning for high-fidelity diffusion tensor estimation from minimal diffusion protocols T Goodwin-Allcock, T Gong, R Gray, P Nachev, H Zhang arXiv preprint arXiv:2307.01346, 2023 | 1 | 2023 |
| How can spherical-CNNs improve ML-based diffusion MRI parameter estimation? T Goodwin-Allcock, J McEwen, R Gray, P Nachev, H Zhang | | 2022 |
| Spherical-CNN based diffusion MRI parameter estimation is robust to gradient schemes and equivariant to rotation T Goodwin-Allcock, R Gray, P Nachev, J McEwan, H Zhang | | |
| Patch-CNN-DTI: Data-efficient high-fidelity tensor recovery from 6 direction diffusion weighted imaging. T Goodwin-Allcock, T Gong, R Gray, P Nachev, H Zhang | | |
