Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis

The proposed method uses Weighted Boxes Fusion (WBF) algorithm to obtain the aggregated annotations with the implicit annotators' agreement as confidence scores. The estimated annotations are then used to train a deep learning detector with a re-weighted loss function that incorporates the confidence scores to localize abnormal findings.