Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization Haoliang Li1Y uFei Wang 1 Renjie Wan 1 Shiqi Wang 2

Recently, we have witnessed great progress in the field of medical imaging classification by adopting deep neural networks. However, the recent advanced models still require accessing sufficiently large and representative datasets for training, which is often unfeasible in clinically realistic environments.