A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation.

Journal: European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Published Date: Apr 11, 2020

Abstract

PURPOSE: The purpose of this study is to evaluate the performance of a novel deep learning (DL) tool for fully automated measurements of the sagittal spinopelvic balance from X-ray images of the spine in comparison with manual measurements.

Authors

  • Robert Korez
    Laboratory of Imaging Technologies, Faculty of Electrical Engineering, University of Ljubljana, Tržaška Cesta 25, 1000, Ljubljana, Slovenia.
  • Michael Putzier
    Charité University Hospital, Charitéplatz 1, 10117, Berlin, Germany.
  • Tomaž Vrtovec
    Laboratory of Imaging Technologies, Faculty of Electrical Engineering, University of Ljubljana, Tržaška Cesta 25, 1000, Ljubljana, Slovenia. tomaz.vrtovec@fe.uni-lj.si.

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