Robotic Craniomaxillofacial Osteotomy System Using Acoustic 3D Registration *
Jiayu Zhu, Runzhe Han, Mengning Yuan, Bimeng Jie, Shanshan Du, Yang He, Runshi Zhang, Junchen Wang
Abstract
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.
BibTeX
@inproceedings{icra2024_roboticcraniomax,
title = {Robotic Craniomaxillofacial Osteotomy System Using Acoustic 3D Registration *},
author = {Jiayu Zhu and Runzhe Han and Mengning Yuan and Bimeng Jie and Shanshan Du and Yang He and Runshi Zhang and Junchen Wang},
booktitle = {ICRA 2024},
year = {2024}
}