AI RESEARCH
DGRNet: Disagreement-Guided Refinement for Uncertainty-Aware Brain Tumor Segmentation
arXiv CS.CV
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ArXi:2603.21086v1 Announce Type: new Accurate brain tumor segmentation from MRI scans is critical for diagnosis and treatment planning. Despite the strong performance of recent deep learning approaches, two fundamental limitations remain: (1) the lack of reliable uncertainty quantification in single-model predictions, which is essential for clinical deployment because the level of uncertainty may impact treatment decision-making, and (2) the under-utilization of rich information in radiology reports that can guide segmentation in ambiguous regions.