Semi-supervised learning has made significant progress in medical image segmentation. However, existing methods primarily utilize information acquired from a single dimensionality (2D/3D), resulting in sub-optimal performance on challenging data, such as magnetic resonance imaging (MRI) scans with multiple objects and highly anisotropic resolution. To address this issue, we present a Hybrid Dual Mean-Teacher (HD-Teacher) model with hybrid, semi-supervised, and multi-task learning to achieve highly effective semi-supervised segmentation. HD-Teacher employs a 2D and a 3D mean-teacher network to produce segmentation labels and signed distance fields from the hybrid information captured in both dimensionalities. This hybrid learning mechanism allows HD-Teacher to combine the `best of both worlds', utilizing features extracted from either 2D, 3D, or both dimensions to produce outputs as it sees fit. Outputs from 2D and 3D teacher models are also dynamically combined, based on their individual uncertainty scores, into a single hybrid prediction, where the hybrid uncertainty is estimated. We then propose a hybrid regularization module to encourage both student models to produce results close to the uncertainty-weighted hybrid prediction. The hybrid uncertainty suppresses unreliable knowledge in the hybrid prediction, leaving only useful information to improve network performance further. Extensive experiments of binary and multi-class segmentation conducted on three MRI datasets demonstrate the effectiveness of the proposed framework. Code is available at https://github.com/ThisGame42/Hybrid-Teacher.

翻译：半监督学习在医学图像分割领域已取得显著进展。然而，现有方法主要利用单一维度（2D/3D）获取的信息，在处理具有多个对象及高度各向异性分辨率的磁共振成像（MRI）扫描等挑战性数据时表现欠佳。为解决该问题，我们提出混合双均值教师（HD-Teacher）模型，通过混合、半监督与多任务学习实现高效半监督分割。HD-Teacher采用2D与3D均值教师网络，从双维度捕获的混合信息中生成分割标签与有符号距离场。该混合学习机制使HD-Teacher能融合"双维度优势"，灵活提取2D、3D或双维度特征以生成适配输出。基于各自的不确定性得分，2D与3D教师模型的输出被动态融合为单一混合预测，并估计混合不确定性。我们进一步提出混合正则化模块，促使两个学生模型生成接近不确定性加权混合预测的结果。混合不确定性抑制了混合预测中的不可靠知识，仅保留有效信息以进一步优化网络性能。在三个MRI数据集上开展的二分类与多分类分割实验验证了所提框架的有效性。代码已开源：https://github.com/ThisGame42/Hybrid-Teacher。