60 citations
- ShanghaiTech UniversityCN3 papers
- United Imaging Healthcare (China)CN3 papers
- Shanghai Clinical Research CenterCN2 papers
- Ministry of Education of the People's Republic of ChinaCN1 paper
- Nanjing Medical UniversityCN1 paper
- Nanjing UniversityCN1 paper
- Nanjing University of Science and TechnologyCN1 paper
- Nankai UniversityCN1 paper
- Shandong University of Traditional Chinese MedicineCN1 paper
- Shanghai Jiao Tong UniversityCN1 paper
- Southeast UniversityCN1 paper
- Taishan UniversityCN1 paper
4 papers
Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis
Yonghao Li, Tao Zhou, Kelei He +2
Cross-modality magnetic resonance (MR) image synthesis can be used to generate missing modalities from given ones. Existing (supervised learning) methods often require a large numb…
RandStainNA: Learning Stain-Agnostic Features from Histology Slides by Bridging Stain Augmentation and Normalization
Yiqing Shen, Yulin Luo, Dinggang Shen +1
Stain variations often decrease the generalization ability of deep learning based approaches in digital histopathology analysis. Two separate proposals, namely stain normalization…
Semi-Cycled Generative Adversarial Networks for Real-World Face Super-Resolution
Hao Hou, Jun Xu, Yingkun Hou +3
Real-world face super-resolution (SR) is a highly ill-posed image restoration task. The fully-cycled Cycle-GAN architecture is widely employed to achieve promising performance on f…
Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning
Zheren Li, Zhiming Cui, Sheng Wang +7
Lesion detection is a fundamental problem in the computer-aided diagnosis scheme for mammography. The advance of deep learning techniques have made a remarkable progress for this t…