Recurrent variational network: A deep learning inverse problem solver applied to the task of accelerated mri reconstruction G Yiasemis, JJ Sonke, C Sánchez, J Teuwen Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 52 | 2022 |
Multi-Coil MRI Reconstruction Challenge—Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil Configurations Y Beauferris, J Teuwen, D Karkalousos, N Moriakov, M Caan, G Yiasemis, ... Frontiers in Neuroscience 16, 919186, 2022 | 30* | 2022 |
Direct: Deep image reconstruction toolkit G Yiasemis, N Moriakov, D Karkalousos, M Caan, J Teuwen Journal of Open Source Software 7 (73), 4278, 2022 | 15* | 2022 |
On retrospective k-space subsampling schemes for deep MRI reconstruction G Yiasemis, CI Sánchez, JJ Sonke, J Teuwen Magnetic Resonance Imaging 107, 33-46, 2024 | 8 | 2024 |
Deep MRI reconstruction with radial subsampling G Yiasemis, C Zhang, CI Sánchez, JJ Sonke, J Teuwen Medical Imaging 2022: Physics of Medical Imaging 12031, 801-810, 2022 | 8 | 2022 |
Deep cardiac MRI reconstruction with ADMM G Yiasemis, N Moriakov, JJ Sonke, J Teuwen International Workshop on Statistical Atlases and Computational Models of …, 2023 | 4 | 2023 |
vSHARP: variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse-Problems G Yiasemis, N Moriakov, JJ Sonke, J Teuwen arXiv preprint arXiv:2309.09954, 2023 | 1 | 2023 |
The state-of-the-art in Cardiac MRI Reconstruction: Results of the CMRxRecon Challenge in MICCAI 2023 J Lyu, C Qin, S Wang, F Wang, Y Li, Z Wang, K Guo, C Ouyang, M Tänzer, ... arXiv preprint arXiv:2404.01082, 2024 | | 2024 |
End-to-end Adaptive Dynamic Subsampling and Reconstruction for Cardiac MRI G Yiasemis, JJ Sonke, J Teuwen arXiv preprint arXiv:2403.10346, 2024 | | 2024 |
JSSL: Joint Supervised and Self-supervised Learning for MRI Reconstruction G Yiasemis, N Moriakov, CI Sánchez, JJ Sonke, J Teuwen arXiv preprint arXiv:2311.15856, 2023 | | 2023 |