Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning.

Journal: International journal of computer assisted radiology and surgery
PMID: 38573567

Abstract

PURPOSE: Three-dimensional (3D) preoperative planning has become the gold standard for orthopedic surgeries, primarily relying on CT-reconstructed 3D models. However, in contrast to standing radiographs, a CT scan is not part of the standard protocol but is usually acquired for preoperative planning purposes only. Additionally, it is costly, exposes the patients to high doses of radiation and is acquired in a non-weight-bearing position.

Authors

  • Tabitha Arn Roth
    Institute for Biomechanics, ETH Zurich, Zurich, Switzerland. tabitha.arn.roth@gmail.com.
  • Moritz Jokeit
    Institute for Biomechanics, ETH Zurich, Zurich, Switzerland.
  • Reto Sutter
    Department of Radiology, Balgrist University Hospital
  • Lazaros Vlachopoulos
    Department of Orthopedics, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
  • Sandro F Fucentese
    Faculty of Medicine, University of Zurich, Zurich, Switzerland.
  • Fabio Carrillo
    Research in Orthopedic Computer Science, University Hospital Balgrist, University of Zurich, Zurich, Switzerland.
  • Jess G Snedeker
    Institute for Biomechanics, ETH Zurich, Zurich, Switzerland.
  • Hooman Esfandiari
    School of Biomedical Engineering, Surgical Technologies Lab, Centre for Hip Health and Mobility, University of British Columbia, Vancouver, British Columbia, Canada.
  • Philipp Fürnstahl
    Research in Orthopedic Computer Science (ROCS), University Hospital Balgrist, University of Zurich, Balgrist Campus, 8008, Zurich, Switzerland.

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