Article

Diet-Seg: Dynamic Hardness-Aware Learning for Enhanced Brain Tumor Segmentation

2025-06-03

Abstract excerpt

Accurate brain tumor segmentation in magnetic resonance imaging (MRI) remains a critical challenge due to complex tumor heterogeneity, fuzzy boundaries, and significant inter-patient variability. In this study, we propose Diet-Seg (Difficulty-Informed Edge-enhanced Tiny Segmentation), a novel segmentation framework that integrates entropy-based pixel-wise hardness estimation into the training process via a dynami...

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Literature Corpus work: 7a513ff9-1f86-5a59-90fe-bb4305a42370
DOI: 10.1101/2025.05.31.657149

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