SSL4MIS:用于医学图像分割的半监督学习，文献综述和代码实现的集合-源码
医学图像分割的半监督学习。
近来，半监督图像分割已成为医学图像计算中的热门话题，不幸的是，由于隐私策略等原因，只有少数开源代码和数据集。为了便于评估和公平比较，我们正在尝试建立一个半监督医学图像分割基准，以促进医学影像计算社区中的半监督学习研究。如果您有兴趣，可以随时将实现或想法推送到此存储库。
该项目最初是为我们以前的工作开发的，如果您发现对您的研究有用，请考虑引用以下内容：
@article{luo2020urpc,
title={Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency},
author={Luo, Xiangde and Liao, Wen
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