手术室工作流程数据集的手术重演
Surgical Re-enactment for Operating Room Workflow Datasets
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中文总结 AI 辅助
针对获取手术室工作流程真实数据集的难题，提出在重建手术室中重演手术程序的方法，结合多种方式创建可重复注释的数据集，用于训练模型等，还为其他团队提供采用建议。
中文摘要 AI 辅助
新技术如手术机器人的引入推动了互联智能手术室的愿景。然而，实现这一愿景需要深入了解手术工作流程，这依赖于从整个手术室和手术视野角度捕捉所有手术室人员行动的真实数据集。在实际手术室获取此类数据具有诸多挑战。我们提出一种在重建的手术室中逐步重演完整手术程序的方法，该方法能创建可重复和可注释的工作流程数据集，用于训练活动识别模型等。此方法结合了专家咨询等多种方式，还给出了让其他研究团队采用该方法的建议。
英文摘要
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.
发表机构
- TUM University Hospital（慕尼黑工业大学附属医院）
- TUM School of Medicine and Health（慕尼黑工业大学医学与健康学院）
- TUM School of Computation, Information, and Technology（慕尼黑工业大学计算、信息与技术学院）
- University of Alberta（阿尔伯塔大学）
机构由 AI 辅助整理，请以论文原文为准。
