Structured Reasoning Agentic Framework for Interpretable Critical View of Safety Assessment
Surgical scene understanding is critical for computer-assisted intervention, yet laparoscopic cholecystectomy remains challenged by the complex anatomy of the hepatocystic triangle and the risk of bile duct injury. Existing methods for Critical View of Safety (CVS) assessment typically treat it as a holistic prediction task, mapping visual features directly to criterion-level labels. This black-box paradigm lacks explicit reasoning about anatomical relationships, limiting both interpretability and compositional generalization. To address this, we propose ReasonCVS, a structured reasoning agentic framework empowered by Vision-Language Models (VLMs) that decomposes CVS assessment into expli...
| Authors | Qing Xu, Yuxiang Luo, Zhen Chen |
|---|---|
| Primary category | cs.CV |
| Published | 25 September 2026 |
| Last updated at source | 25 September 2026 |
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