CLCS combines two-branch collaborative learning, class-adaptive curriculum thresholds, and a noise balance loss to train medical segmentation models from pixel-dependent noisy labels.
Provably end-to-end label-noise learning without anchor points,
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Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels
CLCS combines two-branch collaborative learning, class-adaptive curriculum thresholds, and a noise balance loss to train medical segmentation models from pixel-dependent noisy labels.