A localization-based Faster R-CNN with feature pyramid networks improves breast cancer screening exam classification to AUC 0.919 on a 229,426-exam dataset, a 23% relative error reduction over the authors' prior baseline.
maskrcnn-benchmark: Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch
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Improving localization-based approaches for breast cancer screening exam classification
A localization-based Faster R-CNN with feature pyramid networks improves breast cancer screening exam classification to AUC 0.919 on a 229,426-exam dataset, a 23% relative error reduction over the authors' prior baseline.