发表机构
Dalian University of Technology; The University of Tokyo（大连理工大学; 东京大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对机器人开颅手术问题，提出受人类启发的闭环框架，集成术前规划与术中执行。采用自适应双轮廓融合算法生成轨迹，利用多模态网络融合信号实现突破检测，通过原位投影策略调整轨迹，实验验证该框架能实现安全自主且高效闭环控制的开颅手术。
AI 中文摘要
手动开颅手术是一种高风险、依赖技能的手术，存在外科医生疲劳和潜在硬脑膜损伤问题。虽然机器人手术提高了安全性，但现有开环系统仅依赖术前图像，无法补偿术中配准误差或组织变形。为此，我们提出了一个受人类启发的闭环机器人开颅框架，将术前规划与术中执行智能集成。采用自适应双轮廓融合算法生成符合复杂颅骨几何形状的轨迹，同时保持工具-骨相对姿态一致。术中感知方面，多模态两阶段跨模态注意力块（CMA）-时间卷积网络（TCN）-Transformer网络结合自适应贝叶斯滤波器融合力和声学信号，在不同骨条件下实现可靠的突破检测。检测到后，基于原位投影的轨迹调整策略动态补偿深度偏差，实现安全的残余骨分离。牛肋骨实验显示突破预测准确率为97%，检测延迟为0.048±0.097秒，最大超调量为0.29毫米。所有四个离体颅骨实验均成功完成，无硬脑膜损伤。结果表明，所提出的控制论框架通过高效的闭环控制实现了安全自主的开颅手术。
英文摘要
Manual craniotomy is a high-risk, skill-dependent procedure associated with surgeon fatigue and potential dural injury. While robotic approaches have improved safety, existing open-loop systems rely solely on preoperative images and cannot compensate for intraoperative registration errors or tissue deformation. To address this, we propose a human-inspired closed-loop robotic craniotomy framework that intelligently integrates preoperative planning with intraoperative execution. An adaptive dual-contour fusion algorithm is employed to generate trajectories that conform to complex cranial geometries while maintaining a consistent tool-bone relative pose. For intraoperative perception, a multimodal two-stage cross-modal attention block (CMA)-temporal convolutional network (TCN)-Transformer network combined with an adaptive Bayesian filter fuses force and acoustic signals to achieve robust breakthrough detection under varying bone conditions. Upon detection, an in-situ projection-based trajectory adjustment strategy dynamically compensates for depth deviations, enabling safe residual bone isolation. Experiments on bovine ribs show a breakthrough prediction accuracy of 97%, a detection latency of 0.048 +/- 0.097 s, and a maximum overshoot of 0.29 mm. All four ex vivo cranial experiments were successfully completed without dural injury. These results demonstrate that the proposed cybernetic framework enables safe and autonomous craniotomy with highly effective closed-loop control.
