PriUS enforces uncertainty estimates in segmentation models via evidential learning to match image contrast, corruption levels, and shape complexity, yielding more consistent uncertainty on ACDC, ISIC, and WHS datasets while preserving segmentation accuracy.
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
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Principle-Guided Supervision for Interpretable Uncertainty in Medical Image Segmentation
PriUS enforces uncertainty estimates in segmentation models via evidential learning to match image contrast, corruption levels, and shape complexity, yielding more consistent uncertainty on ACDC, ISIC, and WHS datasets while preserving segmentation accuracy.