Federated Learning and Differential Privacy for Medical Image Analysis

We conduct a case study of applying a differentially private federated learning framework for the analysis of histopathology images, the largest and perhaps most complex medical images. Our work indicates that differentially private federated learning is a viable and reliable framework for the collaborative development of machine learning models in medical image analysis.