When Accuracy Meets Privacy: Two-Stage Federated Transfer Learning Framework in Classification of Medical Images on Limited Data: A COVID-19 Case Study. (arXiv:2203.12803v1 [eess.IV])

COVID-19 pandemic has spread rapidly and caused a shortage of global medical
resources. The efficiency of COVID-19 diagnosis has become highly significant.
As deep learning and convolutional neural network (CNN) has been widely
utilized and been verified in analyzing medical images, it has become a
powerful tool for computer-assisted diagnosis. However, there are two most
significant challenges in medical image classification with the help of deep
learning and neural networks, one of them is the difficulty of acquiring enough
samples, …

case classification covid data framework images medical privacy