fastMRI: An open dataset and benchmarks for accelerated MRI J Zbontar, F Knoll, A Sriram, T Murrell, Z Huang, MJ Muckley, A Defazio, ... arXiv preprint arXiv:1811.08839, 2018 | 776 | 2018 |
End-to-end variational networks for accelerated MRI reconstruction A Sriram, J Zbontar, T Murrell, A Defazio, CL Zitnick, N Yakubova, F Knoll, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 267 | 2020 |
Artificial intelligence for MR image reconstruction: an overview for clinicians DJ Lin, PM Johnson, F Knoll, YW Lui Journal of Magnetic Resonance Imaging 53 (4), 1015-1028, 2021 | 146 | 2021 |
Using deep learning to accelerate knee MRI at 3 T: results of an interchangeability study MP Recht, J Zbontar, DK Sodickson, F Knoll, N Yakubova, A Sriram, ... American Journal of Roentgenology 215 (6), 1421-1429, 2020 | 127 | 2020 |
Conditional generative adversarial network for 3D rigid‐body motion correction in MRI PM Johnson, M Drangova Magnetic resonance in medicine 82 (3), 901-910, 2019 | 88 | 2019 |
Improving the speed of MRI with artificial intelligence PM Johnson, MP Recht, F Knoll Seminars in musculoskeletal radiology 24 (01), 012-020, 2020 | 59 | 2020 |
Deep learning reconstruction enables highly accelerated biparametric MR imaging of the prostate PM Johnson, A Tong, A Donthireddy, K Melamud, R Petrocelli, P Smereka, ... Journal of Magnetic Resonance Imaging 56 (1), 184-195, 2022 | 36 | 2022 |
Deep learning reconstruction enables prospectively accelerated clinical knee MRI PM Johnson, DJ Lin, J Zbontar, CL Zitnick, A Sriram, M Muckley, JS Babb, ... Radiology 307 (2), e220425, 2023 | 31 | 2023 |
Motion correction in MRI using deep learning PM Johnson, M Drangova Proceedings of the ISMRM Scientific Meeting & Exhibition, Paris 4098, 1-4, 2018 | 27 | 2018 |
Design and evaluation of an MRI‐compatible linear motion stage MA Tavallaei, PM Johnson, J Liu, M Drangova Medical physics 43 (1), 62-71, 2016 | 27 | 2016 |
New-generation low-field magnetic resonance imaging of hip arthroplasty implants using slice encoding for metal artifact correction: first in vitro experience at 0.55 T and … I Khodarahmi, IM Brinkmann, DJ Lin, M Bruno, PM Johnson, F Knoll, ... Investigative radiology 57 (8), 517-526, 2022 | 24 | 2022 |
Retrospective 3D motion correction using spherical navigator echoes PM Johnson, J Liu, T Wade, MA Tavallaei, M Drangova Magnetic resonance imaging 34 (9), 1274-1282, 2016 | 22 | 2016 |
Rigid-body motion correction in hybrid PET/MRI using spherical navigator echoes PM Johnson, R Taylor, T Whelan, JD Thiessen, U Anazodo, M Drangova Physics in medicine & biology 64 (8), 08NT03, 2019 | 21 | 2019 |
Rapid mono and biexponential 3D-T1ρ mapping of knee cartilage using variational networks MVW Zibetti, PM Johnson, A Sharafi, K Hammernik, F Knoll, RR Regatte Scientific Reports 10 (1), 19144, 2020 | 17 | 2020 |
Evaluation of the robustness of learned MR image reconstruction to systematic deviations between training and test data for the models from the fastMRI challenge PM Johnson, G Jeong, K Hammernik, J Schlemper, C Qin, J Duan, ... Machine Learning for Medical Image Reconstruction: 4th International …, 2021 | 13 | 2021 |
Joint multi-anatomy training of a variational network for reconstruction of accelerated magnetic resonance image acquisitions PM Johnson, MJ Muckley, M Bruno, E Kobler, K Hammernik, T Pock, ... Machine Learning for Medical Image Reconstruction: Second International …, 2019 | 7 | 2019 |
FastMRI Prostate: A public, biparametric MRI dataset to advance machine learning for prostate cancer imaging R Tibrewala, T Dutt, A Tong, L Ginocchio, R Lattanzi, MB Keerthivasan, ... Scientific Data 11 (1), 404, 2024 | 4* | 2024 |
A Simulation Pipeline to Generate Realistic Breast Images for Learning DCE-MRI Reconstruction Z Huang, J Bae, PM Johnson, T Sood, L Heacock, J Fogarty, L Moy, ... Machine Learning for Medical Image Reconstruction: 4th International …, 2021 | 2 | 2021 |
Machine Learning for Medical Image Reconstruction: Third International Workshop, MLMIR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings F Deeba, P Johnson, T Würfl, JC Ye Springer Nature, 2020 | 2 | 2020 |
The deep route to low-field MRI with high potential PM Johnson, YW Lui Nature 623 (7988), 700-701, 2023 | 1 | 2023 |