3 papers
cs.CV2023
3D Medical Image Segmentation with Sparse Annotation via Cross-Teaching between 3D and 2D Networks
Heng Cai, Lei Qi, Qian Yu +2
Medical image segmentation typically necessitates a large and precisely annotated dataset. However, obtaining pixel-wise annotation is a labor-intensive task that requires signific…
cs.CV2023
Orthogonal Annotation Benefits Barely-supervised Medical Image Segmentation
Heng Cai, Shumeng Li, Lei Qi +3
Recent trends in semi-supervised learning have significantly boosted the performance of 3D semi-supervised medical image segmentation. Compared with 2D images, 3D medical volumes i…
cs.CV2022
CYBORGS: Contrastively Bootstrapping Object Representations by Grounding in Segmentation
Renhao Wang, Hang Zhao, Yang Gao
Many recent approaches in contrastive learning have worked to close the gap between pretraining on iconic images like ImageNet and pretraining on complex scenes like COCO. This gap…