Deep learning-based X-ray inpainting for improving spinal 2D-3D registration.

Journal: The international journal of medical robotics + computer assisted surgery : MRCAS
Published Date: Feb 15, 2021

Abstract

BACKGROUND: Two-dimensional (2D)-3D registration is challenging in the presence of implant projections on intraoperative images, which can limit the registration capture range. Here, we investigate the use of deep-learning-based inpainting for removing implant projections from the X-rays to improve the registration performance.

Authors

  • Hooman Esfandiari
    School of Biomedical Engineering, Surgical Technologies Lab, Centre for Hip Health and Mobility, University of British Columbia, Vancouver, British Columbia, Canada.
  • Simon Weidert
    Chirurgische Klinik und Poliklinik Innenstadt, München, Germany.
  • István Kövesházi
    Department for General, Trauma and Reconstructive Surgery, LMU Munich, Munich, Germany.
  • Carolyn Anglin
    Biomedical and Civil Engineering, University of Calgary, Calgary, Alberta, Canada.
  • John Street
    International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada.
  • Antony J Hodgson
    Department of Mechanical Engineering, School of Biomedical Engineering, Surgical Technologies Lab, University of British Columbia, Vancouver, British Columbia, Canada.

Keywords

External Resources

Popular Topics
Recent Journals