… Recent advances in deep learning methods have redefined the state-of-the-art for many …
same imaging modality. In this work, we extend the method of unsupervised domain adaptation …

… with unsupervised deep domain adaptation. The coverage of UDA, especially deep learning-…
proposed to achieve semi-supervised domain adaptation for medical image segmentation. …

… We aim to summarize recent advances, highlighting the motivation, challenges, and …
Unsupervised domain adaptation in brain lesion segmentation with adversarial networks. In…

… recent advances of domain adaptation methods in medical … in machine learning based
medical image analysis [22], [32]–[34]. … unsupervised domain adaptation methods [11], [12] for …

… the deep learning methods that have been designed for unsupervised domain adaptation
[152… 272], or they focus on tasks such as activity recognition [45] or reinforcement learning [128…

… deep learning methods hitherto have achieved considerable success in medical image …
Finally, our LEUDA further advances dual-domain adversarial learning into self-ensembling …

… Recent advances in deep learning-based medical image segmentation studies achieve …
expensive and laborious in medical imaging fields. Unsupervised domain adaptation (UDA) can …

… Abstract—Recent advances in deep learning have led to the … , medical imaging, and
autonomous navigation by introducing them to the problem, and familiarizing them with the current …

… Recent advances in deep learning-based medical image segmentation studies achieve …
sive and laborious in medical imaging fields. Unsupervised domain adaptation can alleviate this …

… Deep learning models trained on medical images from a source domain (\( eg \) imaging …
With recent significant advancement of generative adversarial networks (GAN), distances …