Unsupervised domain adaptation for medical imaging segmentation with self-ensembling

Recent advances in deep learning methods have redefined the state-of-the-art for many medical imaging applications, surpassing previous approaches and sometimes even competing with human judgment in several tasks. Those models, however, when trained to reduce the empirical risk on a single domain, f...

Ausführliche Beschreibung