UST-RUN improves mixed-domain semi-supervised medical image segmentation by generating diverse intermediate samples from reliable unlabeled data and refining training for unreliable samples.
Uncertainty-aware self-ensembling model for semi-supervised 3d left atrium segmentation,
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Unleashing the Power of Intermediate Domains for Mixed Domain Semi-Supervised Medical Image Segmentation
UST-RUN improves mixed-domain semi-supervised medical image segmentation by generating diverse intermediate samples from reliable unlabeled data and refining training for unreliable samples.