Comparison of accelerated T1-weighted whole-brain structural-imaging protocols. - Pavel Falkovskiy; Daniel Brenner; Thorsten Feiweier; Stephan A. R. Kannengiesser; Bénédicte Maréchal; Tobias Kober; Alexis Roche; Kaely Thostenson; Reto Meuli; Denise Reyes; Tony Stöcker; Matt A. Bernstein; et al. (NeuroImage, 2016)

Neuroimaging Harmonization Using cGANs: Image Similarity Metrics Poorly Predict Cross-Protocol Volumetric Consistency. - Veronica Ravano; Jean-François Démonet; Daniel Damian; Reto Meuli; Gian Franco Piredda; Till Huelnhagen; Bénédicte Maréchal; Jean-Philippe Thiran; Tobias Kober; Jonas Richiardi (MLCN@MICCAI, 2022)

Deep Learning for Ischemic Penumbra Segmentation from MR Perfusion Maps: Robustness to the Deconvolution Algorithm. - Theo Leuliet; Stefan Huwer; Bénédicte Maréchal; Veronica Ravano; Tobias Kober; Jonathan Rafael-Patino; Johannes Kaesmacher; Roland Wiest; Jonas Richiardi; Richard McKinley (BrainLes/SWITCH@MICCAI, 2023)

Federated Learning on Heterogeneous Diffusion-Weighted Imaging Data for Acute Stroke Infarct Segmentation. - Antoine Madrona; Sebastian Otálora; Elda Fischi Gomez; Veronica Ravano; Bénédicte Maréchal; Jean-Philippe Thiran; Tobias Kober; Roland Wiest; Richard McKinley; Jonas Richiardi; Jonathan Rafael-Patino (ISBI, 2023)

Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency. - Nataliia Molchanova; Bénédicte Maréchal; Jean-Philippe Thiran; Tobias Kober; Till Huelnhagen; Jonas Richiardi (CoRR, 2023)