MEDL combines class-aware evidential fusion from two networks with an uncertainty-ranked curriculum to generate pseudo-labels for semi-supervised medical segmentation, reporting gains on five datasets though with incomplete statistical reporting.
Mutual evidential deep learning for semi-supervised medical image segmentation,
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Mutual Evidential Deep Learning for Medical Image Segmentation
MEDL combines class-aware evidential fusion from two networks with an uncertainty-ranked curriculum to generate pseudo-labels for semi-supervised medical segmentation, reporting gains on five datasets though with incomplete statistical reporting.