Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

•A unified framework for semi-supervised medical image segmentation and domain adaptation.•A co-training type algorithm that enforces multi-view consistency as additional supervision.•Uncertainty for each view is estimated and weighted to generate reliable pseudo labels.•Superior semi-supervised segmentation performance on pancreas and multi-organ datasets.•Improve unsupervised domain adaptation results with and without source domain data.