TY - GEN
T1 - Robotic Craniomaxillofacial Osteotomy System Using Acoustic 3D Registration
AU - Zhu, Jiayu
AU - Han, Runzhe
AU - Yuan, Mengning
AU - Jie, Bimeng
AU - Du, Shanshan
AU - He, Yang
AU - Zhang, Runshi
AU - Wang, Junchen
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Osteotomy holds a pivotal position among the fundamental procedures in craniomaxillofacial (CMF) surgery. However, there are inherent challenges and risks associated with ensuring the recuperation of occlusion, safeguarding the facial nerves and blood vessels, as well as preserving facial aesthetics. In this study, a non-invasive image-to-patient registration method for navigation/robotic CMF surgery based on intraoperative freehand ultrasound (US) 3D reconstruction is proposed. Building upon this, a CMF osteotomy robotic system with compliant human-robot interaction and osteotomy trajectory planning was devised. In the freehand US 3D reconstruction and registration experiments, the registration errors for human volunteers and phantoms were consistently less than 1 mm. In robot osteotomy experiments based on the resulting registration, the average osteotomy error was below 1.5 mm. The proposed US 3D reconstruction based registration method is non-invasive and radiation-free, and shows the promising accuracy which is suitable for CMF robotic or navigation systems.
AB - Osteotomy holds a pivotal position among the fundamental procedures in craniomaxillofacial (CMF) surgery. However, there are inherent challenges and risks associated with ensuring the recuperation of occlusion, safeguarding the facial nerves and blood vessels, as well as preserving facial aesthetics. In this study, a non-invasive image-to-patient registration method for navigation/robotic CMF surgery based on intraoperative freehand ultrasound (US) 3D reconstruction is proposed. Building upon this, a CMF osteotomy robotic system with compliant human-robot interaction and osteotomy trajectory planning was devised. In the freehand US 3D reconstruction and registration experiments, the registration errors for human volunteers and phantoms were consistently less than 1 mm. In robot osteotomy experiments based on the resulting registration, the average osteotomy error was below 1.5 mm. The proposed US 3D reconstruction based registration method is non-invasive and radiation-free, and shows the promising accuracy which is suitable for CMF robotic or navigation systems.
UR - https://www.scopus.com/pages/publications/85202448837
U2 - 10.1109/ICRA57147.2024.10610887
DO - 10.1109/ICRA57147.2024.10610887
M3 - 会议稿件
AN - SCOPUS:85202448837
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 3554
EP - 3560
BT - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
Y2 - 13 May 2024 through 17 May 2024
ER -