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Updated: May 26, 2026
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Designing CAD/CAM Surgical Guides for Maxillary Reconstruction Using an In-house Approach
Published on: August 24, 2018
Robot-Assisted Osteotomy and Reconstruction with AR Guidance in Maxillofacial Reconstructive Surgery.
Sifan Cao1, Jingfan Fan1,2, Long Shao1,2
1Beijing Key Laboratory for Surgical Navigation Robots with Augmented Reality, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China.
Cyborg and Bionic Systems (Washington, D.C.)
|May 25, 2026
Summary
This study introduces a novel robot-assisted osteotomy and augmented reality-guided reconstruction (ARR) system for maxillofacial tumor treatment. The system enhances surgical accuracy and consistency in complex osteotomies and reconstructions.
Area of Science:
- Medical Engineering
- Surgical Robotics
- Medical Imaging
Background:
- Maxillofacial tumor treatment demands precise resection and reconstruction.
- Conventional methods risk tissue injury and have limited reconstruction accuracy.
- Challenges include achieving consistent alignment in titanium plate-based reconstructions.
Purpose of the Study:
- To propose and validate a novel maxillofacial tumor treatment system (RAMRS).
- To integrate robot-assisted osteotomy and augmented reality-guided reconstruction (ARR).
- To improve accuracy and consistency in maxillofacial surgery.
Main Methods:
- Developed a robot-assisted osteotomy module with hand-eye calibration and optical probe registration.
- Implemented an augmented reality-guided reconstruction (ARR) module using rotating-caliper calibration and quick-response markers.
- Validated the system on cadaveric and ex vivo specimens.
Main Results:
- Demonstrated favorable accuracy in osteotomy and reconstruction alignment.
- Achieved low 2-dimensional fusion error for augmented reality visualization.
- Validated the feasibility of the proposed workflow in preclinical settings.
Conclusions:
- The proposed RAMRS system, integrating robot-assisted osteotomy and ARR, shows promise for maxillofacial tumor treatment.
- The system offers improved accuracy and intuitive intraoperative guidance.
- Further preclinical validation supports its potential clinical application.
