A Novel Augmented Reality Assisted Orthopedic Surgical Robotic System With Bidirectional Surface Registration Algorithms
This paper presents a novel augmented reality (AR)-assisted orthopedic surgical robotic system based on Head-Mounted Display (HMD) devices. The proposed system can overlay the preoperative plans over the patient’s anatomy and provide useful guidance for surgeons during interventions, with integrated calibration and registration components. A novel bi-directional generalised point set registration algorithm that utilises robust features is developed to accurately align the pre-operative CT and intra-operative patient spaces, which has been demonstrated to outperform existing registration methods. The efficacy of the system is both qualitatively and quantitatively assessed with an in vitro study representing a total knee arthroplasty (TKA) procedure. The experimental results showed that 1) the system can successfully align the preoperative and intraoperative spaces, with the mean target registration error (TRE) being <inline-formula> <tex-math notation="LaTeX">$2.78 \; \pm \; 2.51$ </tex-math></inline-formula> mm; 2) the models can be properly overlaid to the physical scenarios with the mean AR visualization accuracy being <inline-formula> <tex-math notation="LaTeX">$6.97 \; \pm \; 1.57$ </tex-math></inline-formula> mm.
Authors
- Max Q.‐H. Meng (ORCID: https://orcid.org/0000-0002-5255-5898)
- Zhengyan Zhang (ORCID: https://orcid.org/0000-0002-4906-4481)
- Zhe Min (ORCID: https://orcid.org/0000-0002-8903-1561)
- Ang Zhang (ORCID: https://orcid.org/0000-0002-0749-5822)
- Yingying Wang (ORCID: https://orcid.org/0000-0002-3659-6139)
Institutions
- Hong Kong Polytechnic University (HK)
- Shandong University (CN)
- Southern University of Science and Technology (CN)
- Intelligent Systems Research (United States) (US)
Publication Details
- Journal
- IEEE Transactions on Medical Robotics and Bionics
- Published
- 2024-10-03
- DOI
- https://doi.org/10.1109/tmrb.2024.3472844
- Citations
- 8
- Primary Topic
- Soft Robotics and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.48
Funders
- National Natural Science Foundation of China