ConFiG: Contextual Fibre Growth to generate realistic axonal packing for diffusion MRI simulation R Callaghan, DC Alexander, M Palombo, H Zhang Neuroimage 220, 117107, 2020 | 20 | 2020 |
Contextual fibre growth to generate realistic axonal packing for diffusion MRI simulation R Callaghan, DC Alexander, H Zhang, M Palombo International Conference on Information Processing in Medical Imaging, 429-440, 2019 | 4 | 2019 |
Comparative analysis of signal models for microscopic fractional anisotropy estimation using q-space trajectory encoding L Kerkelä, F Nery, R Callaghan, F Zhou, NG Gyori, F Szczepankiewicz, ... NeuroImage 242, 118445, 2021 | 2 | 2021 |
Generation of realistic white matter substrates with controllable morphology for diffusion MRI simulations R Callaghan UCL (University College London), 2022 | | 2022 |
Impact of within-voxel heterogeneity in fibre geometry on spherical deconvolution R Callaghan, DC Alexander, M Palombo, H Zhang arXiv preprint arXiv:2103.08237, 2021 | | 2021 |
Effect of cell complexity and size on diffusion MRI signal: a simulation study A Ianus, R Callaghan, D Alexander, M Palombo | | 2019 |
Towards a more realistic and flexible white matter numerical phantom generator for diffusion MRI simulation R Callaghan, N Shemesh, D Alexander, H Zhang, M Palombo | | 2019 |
Improved contextual fibre growth for generating white matter numerical phantoms with realistic microstructure R Callaghan, DC Alexander, M Palombo, H Zhang | | |
Comparing MEGA editing techniques for in-vivo measurement of 2-hydroxyglutarate R Callaghan, B Solanky, S Bisdas, H Zhang, E De Vita | | |