| A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density Noisier2Noise C Millard, M Chiew IEEE transactions on computational imaging, 2023 | 20* | 2023 |
| Approximate message passing with a colored aliasing model for variable density Fourier sampled images C Millard, AT Hess, B Mailhé, J Tanner IEEE Open Journal of Signal Processing 1, 146-158, 2020 | 16 | 2020 |
| An approximate message passing algorithm for rapid parameter-free compressed sensing MRI C Millard, AT Hess, B Mailhe, J Tanner 2020 IEEE International Conference on Image Processing (ICIP), 91-95, 2020 | 10 | 2020 |
| Clean self-supervised MRI reconstruction from noisy, sub-sampled training data with Robust SSDU C Millard, M Chiew arXiv preprint arXiv:2210.01696, 2023 | 3* | 2023 |
| Deep plug-and-play multi-coil compressed sensing MRI with matched aliasing: The denoising-P-VDAMP algorithm C Millard, A Hess, J Tanner, B Mailhe Proc. Annu. Meeting ISMRM, 1-9, 2022 | 3 | 2022 |
| Approximate message passing for compressed sensing magnetic resonance imaging C Millard University of Oxford, 2021 | 2 | 2021 |
| Tuning-free multi-coil compressed sensing MRI with parallel variable density approximate message passing (P-VDAMP) C Millard, M Chiew, J Tanner, AT Hess, B Mailhe arXiv preprint arXiv:2203.04180, 2022 | 1 | 2022 |
| A self-supervised method for recovering clean images from noisy, sub-sampled training examples C Millard Northern Lights Deep Learning Conference Abstracts 2024, 2023 | | 2023 |
| Reconstruction with magnetic resonance compressed sensing B Mailhe, C Millard, MS Nadar US Patent App. 17/303,790, 2022 | | 2022 |
| Image reconstruction using a colored noise model with magnetic resonance compressed sensing C Millard, B Mailhe, MS Nadar US Patent 11,035,919, 2021 | | 2021 |
| Near-optimal tuning-free multicoil compressed sensing MRI with Parallel Variable Density Approximate Message Passing C Millard, AT Hess, J Tanner, B Mailhe | | |
| Versatile Parameter-Free Compressed Sensing MRI with Approximate Message Passing C Millard, AT Hess, B Mailhé, J Tanner | | |
Boris MailhéSiemens HealthineersVerified email at siemens.com
