A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation.

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: Aug 1, 2022

Abstract

PURPOSE: To propose a fully automated deep learning (DL) framework for the vertebral morphometry and Cobb angle measurement from three-dimensional (3D) computed tomography (CT) images of the spine, and validate the proposed framework on an external database.

Authors

  • Danis Alukaev
    AI Lab, Innopolis University, Universitetskaya St 1, 420500, Innopolis, Republic of Tatarstan, Russian Federation.
  • Semen Kiselev
    Institute of Data Science and Artificial Intelligence, Innopolis University, Innopolis, Russia.
  • Tamerlan Mustafaev
  • Ahatov Ainur
    Barsmed Diagnostic Center, Daurskaya 12, 42000, Kazan, Republic of Tatarstan, Russian Federation.
  • Bulat Ibragimov
    Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California, 94305, USA.
  • 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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