Tag: Medical Imaging
New EOSC-SIESTA publication: privacy-preserving Federated Learning in medical imaging
A new EOSC-SIESTA publication by IFCA-CSIC, INRIA, and TU Delft explores privacy protection in Federated Learning using sensitive medical imaging data. The study proposes a metric-privacy-inspired noise calibration strategy that improves global model accuracy while defending against Client Inference Attacks.