25 citations · 46 across the 8 of their papers we have counts for
5 papers · 1 filter
Lethe: How Hard Is It to Forget? A Benchmark for Federated Unlearning in Medical Imaging
Shengchao Chen, Ting Shu
Federated learning enables medical-imaging models to be trained across hospitals, and privacy law, most explicitly the GDPR ``right to be forgotten'', turns removing a hospital's,…
FM: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imaging
Shengchao Chen, Ting Shu
Building foundation models for medical imaging requires pooling data across institutions, yet privacy regulations prohibit centralized aggregation. Existing Federated Foundation Mo…
Boosting Sclera Segmentation through Semi-supervised Learning with Fewer Labels
Guanjun Wang, Lu Wang, Ning Niu +4
Sclera segmentation is crucial for developing automatic eye-related medical computer-aided diagnostic systems, as well as for personal identification and verification, because the…
Federated Distillation for Medical Image Classification: Towards Trustworthy Computer-Aided Diagnosis
Sufen Ren, Yule Hu, Shengchao Chen +1
Medical image classification plays a crucial role in computer-aided clinical diagnosis. While deep learning techniques have significantly enhanced efficiency and reduced costs, the…
MASK-CNN-Transformer For Real-Time Multi-Label Weather Recognition
Shengchao Chen, Ting Shu, Huan Zhao +1
Weather recognition is an essential support for many practical life applications, including traffic safety, environment, and meteorology. However, many existing related works canno…