Ex-vivo microbleed detection in community-based older adults using confidence aware learning

Detection of cerebral microbleeds (CMBs) on ex-vivo gradient echo MR images is an important task in MRI-pathology studies in older adults. The goal of this study was to develop a confidence-aware ex-vivo CMB detection algorithm that outputs interpretable probabilities and ranking of CMB candidates on brain MRI scans of community-based older adults. The present study demonstrates that training an ex-vivo CMB detection model with confidence-aware deep learning, a technique for improving confidence estimation and ordinal ranking of examples in classification models, improves detection performance and prediction interpretability.