Federated Learning Continual FL Privacy-preserving collaborative training of DL models that continue to learn and adapt to new data distributions or tasks. Cross-Domain FL Privacy-preserving collaborative training of DL models across different modalities, imaging protocols, and tasks. Efficient AI Data Curation Reducing burden of data curation using coresets, few-shot learning, and more. Data Annotation Reducing burden of data annotation using weakly supervised learning, foundation models, and more. Intelligent Streaming Resource-efficient high-throughput streaming of medical images for AI training and inference. AI Security, Fairness, and Bias Adversarial Bias Attacks Implication of adversarial bias attacks on DL models in the clinical environment. Algorithmic Bias Bias in medical imaging AI and how it may transfer across various DL paradigms like transfer learning, federated learning, and more.
