| Stochastic primal-dual hybrid gradient algorithm with arbitrary sampling and imaging applications A Chambolle, MJ Ehrhardt, P Richtárik, CB Schönlieb SIAM Journal on Optimization 28 (4), 2783-2808, 2018 | 238 | 2018 |
| Joint reconstruction of PET-MRI by exploiting structural similarity MJ Ehrhardt, K Thielemans, L Pizarro, D Atkinson, S Ourselin, BF Hutton, ... Inverse Problems 31 (1), 015001, 2015 | 184 | 2015 |
| Multicontrast MRI Reconstruction with Structure-Guided Total Variation MJ Ehrhardt, MM Betcke SIAM Journal on Imaging Sciences 9 (3), 1084-1106, 2016 | 160 | 2016 |
| PET Reconstruction with an Anatomical MRI Prior using Parallel Level Sets. MJ Ehrhardt, P Markiewicz, M Liljeroth, A Barnes, V Kolehmainen, ... IEEE Transactions on Medical Imaging, 2016 | 131 | 2016 |
| Deep learning as optimal control problems: models and numerical methods M Benning, E Celledoni, MJ Ehrhardt, B Owren, CB Schönlieb Journal of Computational Dynamics 6 (2), 171-198, 2019 | 112 | 2019 |
| Learning the sampling pattern for MRI F Sherry, M Benning, JC De los Reyes, MJ Graves, G Maierhofer, ... IEEE Transactions on Medical Imaging, 2020 | 95 | 2020 |
| Vector-valued image processing by parallel level sets MJ Ehrhardt, SR Arridge IEEE Transactions on Image Processing 23 (1), 9-18, 2014 | 86 | 2014 |
| Sirf: Synergistic image reconstruction framework E Ovtchinnikov, R Brown, C Kolbitsch, E Pasca, C da Costa-Luis, ... Computer Physics Communications 249, 107087, 2020 | 76 | 2020 |
| Blind image fusion for hyperspectral imaging with the directional total variation L Bungert, DA Coomes, MJ Ehrhardt, J Rasch, R Reisenhofer, ... Inverse Problems 34 (4), 044003, 2018 | 74 | 2018 |
| Structure-preserving deep learning E Celledoni, MJ Ehrhardt, C Etmann, RI McLachlan, B Owren, ... European Journal of Applied Mathematics 32 (5), 888-936, 2021 | 67 | 2021 |
| NiftyPET: a high-throughput software platform for high quantitative accuracy and precision PET imaging and analysis PJ Markiewicz, MJ Ehrhardt, K Erlandsson, PJ Noonan, A Barnes, ... Neuroinformatics 16 (1), 95-115, 2018 | 63 | 2018 |
| Regularising inverse problems with generative machine learning models MAG Duff, NDF Campbell, MJ Ehrhardt Journal of Mathematical Imaging and Vision 66 (1), 37-56, 2024 | 58 | 2024 |
| Multi‐Dimensional Characterization of Battery Materials RF Ziesche, TMM Heenan, P Kumari, J Williams, W Li, ME Curd, ... Advanced Energy Materials 13 (23), 2300103, 2023 | 50 | 2023 |
| Faster PET reconstruction with non-smooth priors by randomization and preconditioning MJ Ehrhardt, PJ Markiewicz, CB Schönlieb Physics in Medicine & Biology, 2019 | 49 | 2019 |
| Equivariant neural networks for inverse problems E Celledoni, MJ Ehrhardt, C Etmann, B Owren, CB Schönlieb, F Sherry Inverse problems 37 (8), 085006, 2021 | 48 | 2021 |
| Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning D Chen, M Davies, MJ Ehrhardt, CB Schönlieb, F Sherry, J Tachella IEEE Signal Processing Magazine 40 (1), 134-147, 2023 | 45 | 2023 |
| Accelerating variance-reduced stochastic gradient methods D Driggs, MJ Ehrhardt, CB Schönlieb Mathematical Programming, 1-45, 2020 | 45 | 2020 |
| Fast Quasi-Newton Algorithms for Penalized Reconstruction in Emission Tomography and Further Improvements via Preconditioning YJ Tsai, A Bousse, MJ Ehrhardt, CW Stearns, S Ahn, BF Hutton, S Arridge, ... IEEE transactions on medical imaging 37 (4), 1000-1010, 2018 | 37 | 2018 |
| Inexact derivative-free optimization for bilevel learning MJ Ehrhardt, L Roberts Journal of Mathematical Imaging and Vision, 1-21, 2021 | 34 | 2021 |
| A geometric integration approach to smooth optimization: foundations of the discrete gradient method MJ Ehrhardt, ES Riis, T Ringholm, CB Schönlieb IMA Journal of Numerical Analysis, drae037, 2024 | 29 | 2024 |
Carola-Bibiane SchönliebDAMTP, University of CambridgeVerified email at cam.ac.uk
