AdaSwitch3D: Reliability-Aware Human-in-the-Loop Artificial Intelligence for Breast Tumor Segmentation in Dynamic Contrast-Enhanced MRI Across Unseen Centers

Background/Objectives: Deep learning models for breast tumor segmentation in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) often lose accuracy at centers that did not contribute training data. We investigated whether case-wise routing between two low-resource adapted models, combined with an uncertainty-based review-prioritization signal, behaves consistently under severe cross-center domain shift.