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## Literature reviews of semi-supervised learning approach for medical image segmentation (**SSL4MIS**).
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|Date|The First and Last Authors|Title|Code|Reference|
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|---|---|---|---|---|
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|2023-03|Y. Zhu and R. Zhang|Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation|[Code](https://github.com/zhuye98/ICL)|[MIDL2023](https://arxiv.org/pdf/2303.14175.pdf)|
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|2023-03|C. Xu and S. Zhao|Dual Uncertainty-guided Mixing Consistency for Semi-Supervised 3D Medical Image Segmentation|[Code](https://github.com/yang6277/DUMC)|[TBD2023](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10075508)|
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|2023-03|K. Chaitanya and E. Konukoglu|Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation|[Code](https://github.com/krishnabits001/pseudo_label_contrastive_training)|[MedIA2023](https://www.sciencedirect.com/science/article/pii/S1361841523000531?via%3Dihub)|
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|2023-03|J. Zhu and E. Meijering|Hybrid Dual Mean-Teacher Network With Double-Uncertainty Guidance for Semi-Supervised Segmentation of MRI Scans|[Code](https://github.com/ThisGame42/Hybrid-Teacher)|[Arxiv](https://arxiv.org/pdf/2303.05126.pdf)|
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