Weakly Supervised Deep Learning for Prostate Cancer Detection in MRI: Achieving High Performance with Limited Annotations and Generalization to Unseen Domains

This research paper introduces a weakly supervised deep learning model that achieves comparable performance to fully supervised models in detecting clinically significant prostate cancer (csPCa) from multiparametric MRI, using significantly fewer annotations and demonstrating robustness to domain shifts.