胸腰椎椎弓根螺钉置入路径规划数据集标注及质量控制专家共识

Expert Consensus on Data Annotation and Quality Control for Trajectory Planning of Thoracolumbar Pedicle Screw Placement

  • 摘要: 近年来,结合人工智能技术开发的椎弓根螺钉置入手术机器人系统展现出极大潜力,可提升术前路径规划的精度与效率,优化手术安全性。该类人工智能辅助规划系统能通过精准计算螺钉入点、止点及路径,有效避免伤害重要解剖结构,辅助医生制定合理的手术方案。然而,系统算法性能和临床适用性很大程度上依赖于具有高质量标注结果的数据集。为规范相关数据集建设,中国食品药品检定研究院联合相关单位制订专家共识,旨在为椎弓根螺钉置入路径规划数据集的建设提供标准化指导。

     

    Abstract: In recent years, surgical robot systems for pedicle screw placement developed with artificial intelligence (AI) technologies have demonstrated substantial potential, offering enhanced accuracy and efficiency in preoperative trajectory planning while optimizing surgical safety. Such AI-assisted planning systems can precisely calculate the entry point, endpoint, and trajectory of screws, effectively avoiding damage to critical anatomical structures and assisting surgeons in developing rational surgical strategies. However, the performance and clinical applicability of these algorithmic systems rely heavily on datasets with high-quality annotated results. To standardize the construction of related datasets, the National Institutes for Food and Drug Control (NIFDC), in collaboration with relevant institutions, has developed this expert consensus, aiming to provide standardized guidance for the establishment of pedicle screw placement trajectory planning datasets.

     

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