DOMINO: Domain-aware Model Calibration in Medical Image Segmentation. (arXiv:2209.06077v1 [eess.IV])

Model calibration measures the agreement between the predicted probability
estimates and the true correctness likelihood. Proper model calibration is
vital for high-risk applications. Unfortunately, modern deep neural networks
are poorly calibrated, compromising trustworthiness and reliability. Medical
image segmentation particularly suffers from this due to the natural
uncertainty of tissue boundaries. This is exasperated by their loss functions,
which favor overconfidence in the majority classes. We address these challenges
with DOMINO, a domain-aware model calibration method that leverages the
semantic confusability …

arxiv domino image medical segmentation