Semi-Supervised CT Lesion Segmentation Using Uncertainty-Based Data Pairing and SwapMix
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DOI: 10.1109/tmi.2022.3232572
Abstract: Semi-supervised learning (SSL) methods show their powerful performance to deal with the issue of data shortage in the field of medical image segmentation. However, existing SSL methods still suffer from the problem of unreliable predictions… read more here.
Keywords: unannotated data; semi; semi supervised; uncertainty based ... See more keywords