LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation

Z Zhao, F Zhou, K Xu, Z Zeng, C Guan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
While deep learning methods hitherto have achieved considerable success in medical
image segmentation, they are still hampered by two limitations:(i) reliance on large-scale …
被引用次数：34 相关文章

LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation

Z Zhao, F Zhou, K Xu, Z Zeng, C Guan… - arXiv preprint arXiv …, 2022 - arxiv.org
While deep learning methods hitherto have achieved considerable success in medical
image segmentation, they are still hampered by two limitations:(i) reliance on large-scale …

LE-UDA: Label-Efficient Unsupervised Domain Adaptation for Medical Image Segmentation

Z Zhao, F Zhou, K Xu, Z Zeng… - IEEE transactions on …, 2023 - pubmed.ncbi.nlm.nih.gov
While deep learning methods hitherto have achieved considerable success in medical
image segmentation, they are still hampered by two limitations:(i) reliance on large-scale …

LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation

Z Zhao, F Zhou, K Xu, Z Zeng, C Guan… - arXiv e …, 2022 - ui.adsabs.harvard.edu
While deep learning methods hitherto have achieved considerable success in medical
image segmentation, they are still hampered by two limitations:(i) reliance on large-scale …

LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation.

Z Zhao, F Zhou, K Xu, Z Zeng, C Guan… - IEEE Transactions on …, 2022 - europepmc.org
While deep learning methods hitherto have achieved considerable success in medical
image segmentation, they are still hampered by two limitations:(i) reliance on large-scale …