104 citations · 146 across the 5 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
eess.IV2022★ 11 cited
One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis
Onat Dalmaz, Usama Mirza, Gökberk Elmas +5
Multi-institutional collaborations are key for learning generalizable MRI synthesis models that translate source- onto target-contrast images. To facilitate collaboration, federate…
eess.IV2022★ 2 cited
Federated Learning of Generative Image Priors for MRI Reconstruction
Gokberk Elmas, Salman UH Dar, Yilmaz Korkmaz +5
Multi-institutional efforts can facilitate training of deep MRI reconstruction models, albeit privacy risks arise during cross-site sharing of imaging data. Federated learning (FL)…