2 papers
eess.IV2026
++nnU-Net: Scaling nnU-Net with Prefix-Based Data Augmentation
Ana Sofia Santos, André Ferreira, Gijs Luijten +6
The nnU-Net has demonstrated continuous success in medical segmentation tasks, which heavily rely on the availability and diversity of annotated biomedical data. However, assemblin…
cs.CV2024
Real-World Federated Learning in Radiology: Hurdles to overcome and Benefits to gain
Markus R. Bujotzek, Ãnal Akünal, Stefan Denner +17
Objective: Federated Learning (FL) enables collaborative model training while keeping data locally. Currently, most FL studies in radiology are conducted in simulated environments…