English(EN) Taurus: LLM-in-the-Loop CT Annotation Matches Coding Agents at Half the Cost

Taurus LLM系统将CT标注成本减半，媲美专家代理

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-06 05:00

研究人员开发了Taurus系统，该系统利用大型语言模型（LLM）辅助计算断层扫描（CT）图像的标注，特别关注主动脉。在对公开数据集进行的盲测中，Taurus与Claude Opus 5.5结合使用，在标注质量上达到了与自由形式LLM代理和人类参考相当的水平。该系统通过自动化标注流程，使专家能够专注于检查错误而非绘制标签，从而将每例成本从自由形式代理的2.71美元降低到1.22美元，显著降低了成本。 AI

影响这项研究展示了一种经济高效的自动化医学图像标注方法，有望将专家时间解放出来用于质量保证，并加速研究。

排序理由该集群包含一篇arXiv预印本，详细介绍了一种用于AI辅助医学图像标注的新系统和方法论。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Bing Hu, Rishabh Sharma · 2026-11-06 05:00

Taurus：LLM-in-the-Loop CT标注成本减半，媲美编码代理

arXiv:2611.00247v2 Announce Type: replace Abstract: Dense labels of the aorta in CT are slow to draw, and the public aortic CT datasets that could stand in for them each label different structures under their own conventions. Large language model (LLM) agents can now write code a…

本文如何被排名

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Taurus：LLM-in-the-Loop CT标注成本减半，媲美编码代理

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