Ba Hung Ngo

DynU-Net: Dynamic Uncertainty-Aware Multi-task U-Net for Joint Lesion Segmentation and Classification in Medical Imaging

A Dynamic Uncertainty-aware Network (DynU-Net) is proposed, a multi-task framework that adaptively balances segmentation and classification through learnable per-task uncertainty parameters that consistently outperforms both single-task and existing multi-task baselines.