AI RESEARCH
ARIADNE: A Perception-Reasoning Synergy Framework for Trustworthy Coronary Angiography Analysis
arXiv CS.AI
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ArXi:2603.19169v1 Announce Type: cross Conventional pixel-wise loss functions fail to enforce topological constraints in coronary vessel segmentation, producing fragmented vascular trees despite high pixel-level accuracy. We present ARIADNE, a two-stage framework coupling preference-aligned perception with RL-based diagnostic reasoning for topologically coherent stenosis detection.