| Microscopy image restoration with deep wiener-kolmogorov filters V Pronina, F Kokkinos, DV Dylov, S Lefkimmiatis Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 35 | 2020 |
| Material Decomposition in Spectral CT using deep learning: A Sim2Real transfer approach JFPJ Abascal, N Ducros, V Pronina, S Rit, PA Rodesch, T Broussaud, ... IEEE Access 9, 25632-25647, 2021 | 34 | 2021 |
| Material Decomposition Problem in Spectral CT: A Transfer Deep Learning Approach J Abascal, N Ducros, V Pronina, S Bussod, A Hauptmannz, S Arridge, ... 2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI …, 2020 | 8 | 2020 |
| 3D denoised completion network for deep single-pixel reconstruction of hyperspectral images V Pronina, A Lorente Mur, JFPJ Abascal, F Peyrin, DV Dylov, N Ducros Optics Express 29 (24), 39559-39573, 2021 | 7 | 2021 |
| Deep Learning Framework For Mobile Microscopy A Kornilova, M Salnikov, O Novitskaya, M Begicheva, E Sevriugov, ... 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 324-328, 2021 | 5 | 2021 |
| Tracking induced pluripotent stem cells differentiation with a fluorescent genetically encoded epigenetic probe AI Stepanov, AA Shuvaeva, LV Putlyaeva, AA Galiakberova, V Pronina, ... | 1 | 2023 |
| A fast computational approach for high spectral resolution imaging L Mahieu-Williame, A Lorente-Mur, V Pronina, B Montcel, F Peyrin, ... Unconventional Optical Imaging III, PC121360F, 2022 | | 2022 |
| A convolutional neural network method for material decomposition in spectral CT J Abascal, V Pronina, N Ducros, S Bussod, S Arridge, A Hauptmann, ... | | |
