A consensus-aware self-corrective loss weighting method improves noisy-label cell segmentation on one real and two simulated glomerular datasets, but the false-positive correction claim is not consistently supported.
Singr: Brain tumor segmentation via signed normalized geodesic transform regression
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CASC-AI: Consensus-aware Self-corrective Learning for Noise Cell Segmentation
A consensus-aware self-corrective loss weighting method improves noisy-label cell segmentation on one real and two simulated glomerular datasets, but the false-positive correction claim is not consistently supported.