3 papers
cs.LG2024
From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare
Ming Li, Pengcheng Xu, Junjie Hu +2
Federated learning holds great potential for enabling large-scale healthcare research and collaboration across multiple centres while ensuring data privacy and security are not com…
cs.CV2023
Where to Begin? From Random to Foundation Model Instructed Initialization in Federated Learning for Medical Image Segmentation
Ming Li, Guang Yang
In medical image analysis, Federated Learning (FL) stands out as a key technology that enables privacy-preserved, decentralized data processing, crucial for handling sensitive medi…
eess.IV2023
Data-Free Distillation Improves Efficiency and Privacy in Federated Thorax Disease Analysis
Ming Li, Guang Yang
Thorax disease analysis in large-scale, multi-centre, and multi-scanner settings is often limited by strict privacy policies. Federated learning (FL) offers a potential solution, w…