2 papers
cs.CV2025
SSL-MedSAM2: A Semi-supervised Medical Image Segmentation Framework Powered by Few-shot Learning of SAM2
Zhendi Gong, Xin Chen
Despite the success of deep learning based models in medical image segmentation, most state-of-the-art (SOTA) methods perform fully-supervised learning, which commonly rely on larg…
cs.CV2025
MO-CTranS: A unified multi-organ segmentation model learning from multiple heterogeneously labelled datasets
Zhendi Gong, Susan Francis, Eleanor Cox +5
Multi-organ segmentation holds paramount significance in many clinical tasks. In practice, compared to large fully annotated datasets, multiple small datasets are often more access…