| 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 | 108 | 2015 |
| 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 | 86 | 2018 |
| Multicontrast MRI Reconstruction with Structure-Guided Total Variation MJ Ehrhardt, MM Betcke SIAM Journal on Imaging Sciences 9 (3), 1084-1106, 2016 | 71 | 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 | 66 | 2016 |
| Vector-valued image processing by parallel level sets MJ Ehrhardt, SR Arridge IEEE Transactions on Image Processing 23 (1), 9-18, 2014 | 60 | 2014 |
| 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 | 22 | 2018 |
| 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 | 18 | 2019 |
| 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 | 17 | 2018 |
| Choose your path wisely: gradient descent in a Bregman distance framework M Benning, MM Betcke, MJ Ehrhardt, CB Schönlieb arXiv preprint arXiv:1712.04045, 2017 | 17 | 2017 |
| Learning the sampling pattern for MRI F Sherry, M Benning, JC De los Reyes, MJ Graves, G Maierhofer, ... IEEE Transactions on Medical Imaging, 2020 | 14 | 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 | 14 | 2018 |
| Incorporating structural prior information and sparsity into EIT using parallel level sets V Kolehmainen, MJ Ehrhardt, SR Arridge Inverse Problems & Imaging 13 (2), 285, 2019 | 13 | 2019 |
| Sirf: Synergistic image reconstruction framework E Ovtchinnikov, R Brown, C Kolbitsch, E Pasca, C da Costa-Luis, ... Computer Physics Communications 249, 107087, 2020 | 10 | 2020 |
| Faster PET reconstruction with non-smooth priors by randomization and preconditioning MJ Ehrhardt, PJ Markiewicz, CB Schönlieb Physics in Medicine & Biology, 2019 | 8 | 2019 |
| Enhancing joint reconstruction and segmentation with non-convex Bregman iteration V Corona, M Benning, MJ Ehrhardt, LF Gladden, R Mair, A Reci, ... Inverse Problems 35 (5), 055001, 2019 | 8 | 2019 |
| Faster PET Reconstruction with a Stochastic Primal-Dual Hybrid Gradient Method MJ Ehrhardt, P Markiewicz, A Chambolle, P Richtárik, J Schott, ... Wavelets and Sparsity XVII 10394, 103941O, 2017 | 8 | 2017 |
| Evaluation of decomposition tools for sea floor pressure data: a practical comparison of modern and classical approaches MJ Ehrhardt, H Villinger, S Schiffler Computers & Geosciences 45, 4-12, 2012 | 8 | 2012 |
| A geometric integration approach to nonsmooth, nonconvex optimisation ES Riis, MJ Ehrhardt, GRW Quispel, CB Schönlieb arXiv preprint arXiv:1807.07554, 2018 | 7 | 2018 |
| A geometric integration approach to smooth optimisation: Foundations of the discrete gradient method MJ Ehrhardt, ES Riis, T Ringholm, CB Schönlieb arXiv preprint arXiv:1805.06444, 2018 | 7 | 2018 |
| Performance evaluation of MAP algorithms with different penalties, object geometries and noise levels YJ Tsai, A Bousse, MJ Ehrhardt, BF Hutton, S Arridge, K Thielemans 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC …, 2015 | 7 | 2015 |
Simon ARRIDGEUniversity College LondonVerified email at cs.ucl.ac.uk
