An Empirical Study of Federated Brain Tumor Classification Under IID and Non-IID Client Distributions with DP-Inspired Local Perturbation
Federated learning (FL) is an approach to protect privacy during medical image analysis due to the possibility to jointly train the model without sharing data between institutions. In this study, we provide a comparative analysis of federated brain tumor classification performance in case of IID and non-IID clients wit...