9 citations · 9 across the 2 of their papers we have counts for
3 papers
eess.IV2024
Tri-Plane Mamba: Efficiently Adapting Segment Anything Model for 3D Medical Images
Hualiang Wang, Yiqun Lin, Xinpeng Ding +1
General networks for 3D medical image segmentation have recently undergone extensive exploration. Behind the exceptional performance of these networks lies a significant demand for…
cs.CV2022
Calibrating Label Distribution for Class-Imbalanced Barely-Supervised Knee Segmentation
Yiqun Lin, Huifeng Yao, Zezhong Li +2
Segmentation of 3D knee MR images is important for the assessment of osteoarthritis. Like other medical data, the volume-wise labeling of knee MR images is expertise-demanded and t…
cs.CV2022★ 9 cited
RSCFed: Random Sampling Consensus Federated Semi-supervised Learning
Xiaoxiao Liang, Yiqun Lin, Huazhu Fu +2
Federated semi-supervised learning (FSSL) aims to derive a global model by training fully-labeled and fully-unlabeled clients or training partially labeled clients. The existing ap…