Uncertainty estimation

Distills an ensemble of segmentation models into a single model to estimate uncertainty in retinal vessel segmentation, matching ensemble-level calibration at a fraction of the compute.

A quality-control and error-correction framework that selects the retinal-image patches most worth manually reviewing, using ensemble uncertainty to estimate the resulting Dice Score improvement.

Estimating uncertainties in Deep Neural Network for semantic Segmentation.