2020
Disentangling Human Error from Ground Truth in Segmentation of Medical Images
NeurIPS 2020poster
Recent years have seen increasing use of supervised learning methods for segmentation tasks. However, the predictive performance of these algorithms depends on the quality of labels. This problem is particularly pertinent in the medical image domain, where both the annotation cost and inter-observer…