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Automatic Markerless Tracking for Computer-Assisted Orthopaedic Surgery

4 pagesPublished: September 26, 2020

Abstract

In computer assisted orthopaedic surgery, it is important to find the correct spatial lo- cation of the target in a predefined world coordinate, so that the model can be transformed accordingly onto the surgical site for surgeons’ reference. Current tracking systems mainly rely on the detection of optical markers inserted into the anatomy. The invasiveness of fixa- tion pins increases operating time and bone complications. Automatic markerless tracking is therefore preferred in practice. In this paper, we integrate an automatic RGBD-image based segmentation neural network and a fast markerless registration algorithm to achieve the markerless tracking purpose. An experimental test with a metal leg was designed. By forcing the alignment of the measured hip joint centre, the overall tracking was shown to be sub-degree in terms of orientation accuracy, which is clinically acceptable.

Keyphrases: Computer-assisted orthopaedic surgery, Markerless tracking, point cloud registration

In: Ferdinando Rodriguez Y Baena and Fabio Tatti (editors). CAOS 2020. The 20th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 4, pages 122--125

Links:
BibTeX entry
@inproceedings{CAOS2020:Automatic_Markerless_Tracking_for,
  author    = {Xue Hu and He Liu and Ferdinando M Rodriguez Y Baena},
  title     = {Automatic Markerless Tracking for Computer-Assisted Orthopaedic Surgery},
  booktitle = {CAOS 2020. The 20th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Ferdinando Rodriguez Y Baena and Fabio Tatti},
  series    = {EPiC Series in Health Sciences},
  volume    = {4},
  pages     = {122--125},
  year      = {2020},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {https://easychair.org/publications/paper/39fX},
  doi       = {10.29007/b6xt}}
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