通过重建手术室重演手术流程，生成可重复标注的手术数据集。
Surgical Re-enactment for Operating Room Workflow Datasets
- 基于专家咨询与流程建模，重建手术室并分角色训练人员重演手术。
- 实现全流程可重复录制，支持动作识别与手术流程建模。
- 适用于机器人辅助眼科手术，方法可迁移至其他外科领域。
新型技术如手术机器人的引入正推动智能手术室的发展。但要实现这一愿景，需深入理解手术流程，依赖于从手术室全景和术野视角捕捉所有人员行为的真实数据集。然而，在真实手术室中获取此类数据面临伦理审批、摄像头安装空间有限及无菌规范禁止使用追踪标记等挑战。本文提出一种分步重演手术过程的方法，可在重建的手术室中实现完整手术流程的重复性录制。该方法结合专家咨询、结构化流程建模、手术室重建、角色化培训、真实手术观察以及迭代拍摄与事后复盘，生成可用于训练动作识别模型、构建场景图和形式化手术流程模型的可标注数据集。本方法针对机器人辅助眼科手术开发，为其他研究团队提供可复用的实施建议。
原文摘要 · Abstract (English)
The introduction of new technologies, such as surgical robots, is driving the vision of a connected, smart operating room (OR). However, realizing this vision requires a deep understanding of surgical workflows, which relies on realistic datasets capturing the actions of all OR personnel from both full room and surgical field perspectives. Acquiring such data in real ORs is prohibitively challenging due to factors such as ethics committee approvals, limited space for camera installation, and sterility regulations preventing the use of tracking markers. We present a step-by-step methodology for re-enacting complete surgical procedures in a reconstructed OR. This approach enables the creation of repeatable and annotatable workflow datasets for training activity recognition models, generating scene graphs, and formalizing surgical process models. Developed for robot-assisted ophthalmic surgery, our methodology combines expert consultation, structured workflow formalization, OR reconstruction, role-based training, real OR observation, and iterative recording with post-take debriefing. We provide concrete recommendations to allow other research groups to seamlessly adopt this methodology for their own surgical domains.
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