Contrastive adversarial mix-up learning for unsupervised cross-modality image segmentation
Background Unsupervised domain adaptation (UDA) has been extensively investigated in terms of its ability to address the performance degradation caused by distribution shifts between labeled source-domain images and unlabeled target-domain images. In radiotherapy, this problem is particularly relevant for the transfer...