4 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentation
Li Lin, Yixiang Liu, Jiewei Wu +4
Federated learning (FL) effectively mitigates the data silo challenge brought about by policies and privacy concerns, implicitly harnessing more data for deep model training. Howev…
eess.IV2023★ 1 cited
Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregation
Li Lin, Jiewei Wu, Yixiang Liu +2
Federated learning (FL) enables multiple sites to collaboratively train powerful deep models without compromising data privacy and security. The statistical heterogeneity (e.g., no…
eess.IV2021★ 4 cited
BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images
Li Lin, Zhonghua Wang, Jiewei Wu +5
Optical coherence tomography angiography (OCTA) is a novel non-invasive imaging technique that allows visualizations of vasculature and foveal avascular zone (FAZ) across retinal l…