Efficient Bayesian Uncertainty Estimation for the State-of-the-Art nnU-Net Medical Image Segmentation Model

A novel and efficient Bayesian inference approximation method is proposed to estimate the uncertainty of the state-of-the-art nnU-Net model for medical image segmentation, without modifying the original nnU-Net architecture.