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author:

Hu, Y. (Hu, Y..) [1] | Zhu, M. (Zhu, M..) [2] | Wang, S. (Wang, S..) [3] | Li, D. (Li, D..) [4] | Meng, Y. (Meng, Y..) [5] | Yuan, F. (Yuan, F..) [6] | Shao, J. (Shao, J..) [7] | Yu, J. (Yu, J..) [8]

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Scopus

Abstract:

Oral localization is widely used in oral and maxillofacial surgery (OMS). Most existing navigation systems adopt stereo optical devices to track fiducial markers for oral localization. However, they still suffer from line-of-sight (LoS) occlusion and field-of-view (FoV) limitation. This article presents a robust oral localization system that utilizes multicamera tracking of self-identifying markers to address the above issue. A customized oral clip with self-identifying markers on its curved surface is designed, which is firmly fixed within the patient's oral cavity. Before surgery, an accurate method based on intraoral scanning is developed to register the patient's oral cavity with the markers, of which the registration error is less than 0.1 mm. Second, a cylindrical marker is applied for calibrating the converging multicamera system to avoid the blurry sight problem. During surgery, a multicamera tracking method, integrating nonlinear optimization and an extended Kalman filter (EKF), is proposed to localize the oral cavity. We establish a simulated environment to test the accuracy and robustness of the tracking method. Additionally, we set up a real platform using a phantom oral cavity to validate the feasibility of each proposed method. Results reveal that our system yields a closer trajectory (0.37 mm) to the ground truth than that of a stereo-camera tracking system (1.58 mm), and exhibits a certain robustness against camera occlusion.  © 1963-2012 IEEE.

Keyword:

Multicamera calibration multicamera tracking nonlinear optimization oral localization patient-image registration

Community:

  • [ 1 ] [Hu Y.]Peking University, State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Beijing, 100871, China
  • [ 2 ] [Zhu M.]Fuzhou University, Department of Mechanical Engineering, Fuzhou, 350000, China
  • [ 3 ] [Wang S.]Peking University, State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Beijing, 100871, China
  • [ 4 ] [Li D.]Peking University, State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Beijing, 100871, China
  • [ 5 ] [Meng Y.]Peking University, State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Beijing, 100871, China
  • [ 6 ] [Yuan F.]Peking University School and Hospital of Stomatology, National Engineering Laboratory for Digital and Material Technology of Stomatology, Center of Digital Dentistry, Beijing, 100190, China
  • [ 7 ] [Shao J.]Peking University, State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Beijing, 100871, China
  • [ 8 ] [Yu J.]Peking University, State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Beijing, 100871, China

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Source :

IEEE Transactions on Instrumentation and Measurement

ISSN: 0018-9456

Year: 2024

Volume: 73

Page: 1-11

5 . 6 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 1

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