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- Chinese University of Hong KongHK36 papers
- Shanghai Artificial Intelligence LaboratoryCN17 papers
- University of Hong KongHK17 papers
- The University of SydneyAU16 papers
- University of Electronic Science and Technology of ChinaCN16 papers
- Shanghai Jiao Tong UniversityCN15 papers
- Tsinghua UniversityCN15 papers
- Nanyang Technological UniversitySG14 papers
- Zhejiang UniversityCN9 papers
- Beihang UniversityCN8 papers
- Beijing Academy of Artificial IntelligenceCN7 papers
- Chinese Academy of SciencesCN7 papers
4 papers · 2 filters
Annotation-Efficient Learning for Medical Image Segmentation based on Noisy Pseudo Labels and Adversarial Learning
Lu Wang, Dong Guo, Guotai Wang +1
Despite that deep learning has achieved state-of-the-art performance for medical image segmentation, its success relies on a large set of manually annotated images for training tha…
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation
Ran Gu, Guotai Wang, Tao Song +6
Accurate medical image segmentation is essential for diagnosis and treatment planning of diseases. Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance f…
Automatic Ischemic Stroke Lesion Segmentation from Computed Tomography Perfusion Images by Image Synthesis and Attention-Based Deep Neural Networks
Guotai Wang, Tao Song, Qiang Dong +3
Ischemic stroke lesion segmentation from Computed Tomography Perfusion (CTP) images is important for accurate diagnosis of stroke in acute care units. However, it is challenged by…
Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices
Guotai Wang, Michael Aertsen, Jan Deprest +3
Segmentation of the fetal brain from stacks of motion-corrupted fetal MRI slices is important for motion correction and high-resolution volume reconstruction. Although Convolutiona…