| Results of the 2020 fastMRI challenge for machine learning MR image reconstruction MJ Muckley, B Riemenschneider, A Radmanesh, S Kim, G Jeong, J Ko, ... IEEE transactions on medical imaging 40 (9), 2306-2317, 2021 | 304* | 2021 |
| Benchmarking MRI reconstruction neural networks on large public datasets Z Ramzi, P Ciuciu, JL Starck Applied Sciences 10 (5), 1816, 2020 | 59 | 2020 |
| NC-PDNet: A density-compensated unrolled network for 2D and 3D non-Cartesian MRI reconstruction Z Ramzi, GR Chaithya, JL Starck, P Ciuciu IEEE Transactions on Medical Imaging 41 (7), 1625-1638, 2022 | 57 | 2022 |
| XPDNet for MRI reconstruction: an application to the fastMRI 2020 brain challenge Z Ramzi, P Ciuciu, JL Starck | 41* | 2020 |
| Benchopt: Reproducible, efficient and collaborative optimization benchmarks T Moreau, M Massias, A Gramfort, P Ablin, PA Bannier, B Charlier, ... Advances in Neural Information Processing Systems 35, 25404-25421, 2022 | 38 | 2022 |
| PySAP: python sparse data analysis package for multidisciplinary image processing S Farrens, A Grigis, L El Gueddari, Z Ramzi, GR Chaithya, S Starck, ... Astronomy and Computing 32, 100402, 2020 | 34 | 2020 |
| SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models Z Ramzi, F Mannel, S Bai, JL Starck, P Ciuciu, T Moreau International Conference on Learning Representations (ICLR), 2022 | 29 | 2022 |
| Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction GR Chaithya, Z Ramzi, P Ciuciu 2021 29th European Signal Processing Conference (EUSIPCO), 960-964, 2021 | 22 | 2021 |
| Density compensated unrolled networks for non-cartesian MRI reconstruction Z Ramzi, JL Starck, P Ciuciu 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1443-1447, 2021 | 22 | 2021 |
| Wavelets in the Deep Learning ERA Z Ramzi, K Michalewicz, JL Starck, T Moreau, P Ciuciu Journal of Mathematical Imaging and Vision, 2022 | 21 | 2022 |
| Denoising score-matching for uncertainty quantification in inverse problems Z Ramzi, B Remy, F Lanusse, JL Starck, P Ciuciu arXiv preprint arXiv:2011.08698, 2020 | 21 | 2020 |
| Benchmarking deep nets MRI reconstruction models on the fastmri publicly available dataset Z Ramzi, P Ciuciu, JL Starck 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1441-1445, 2020 | 21 | 2020 |
| PySAP-MRI: A Python package for MR image reconstruction L El Gueddari, CG Radhakrishna, Z Ramzi, S Farrens, S Starck, A Grigis, ... ISMRM workshop on Data Sampling and Image Reconstruction, 2020 | 11 | 2020 |
| Benchmarking proximal methods acceleration enhancements for CS-acquired MR image analysis reconstruction Z Ramzi, P Ciuciu, JL Starck SPARS 2019-Signal Processing with Adaptive Sparse Structured Representations …, 2019 | 9 | 2019 |
| Probabilistic mapping of dark matter by neural score matching B Remy, F Lanusse, Z Ramzi, J Liu, N Jeffrey, JL Starck arXiv preprint arXiv:2011.08271, 2020 | 7 | 2020 |
| Hybrid learning of non-Cartesian k-space trajectory and MR image reconstruction networks GR Chaithya, Z Ramzi, P Ciuciu 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-5, 2022 | 6 | 2022 |
| MC-PDNET: Deep unrolled neural network for multi-contrast mr image reconstruction from undersampled k-space data K Pooja, Z Ramzi, GR Chaithya, P Ciuciu 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-5, 2022 | 6 | 2022 |
| Is good old GRAPPA dead? Z Ramzi, A Vignaud, JL Starck, P Ciuciu arXiv preprint arXiv:2106.00753, 2021 | 2 | 2021 |
| Test like you Train in Implicit Deep Learning Z Ramzi, P Ablin, G Peyré, T Moreau arXiv preprint arXiv:2305.15042, 2023 | 1 | 2023 |
| Advanced deep neural networks for MRI image reconstruction from highly undersampled data in challenging acquisition settings Z Ramzi Université Paris-Saclay, 2022 | 1 | 2022 |
Philippe CiuciuCEA Fellow & Research Director (CEA/NeuroSpin and Inria MIND)Email verificata su cea.fr