Deep learning enables the differentiation between early and late stages of hip avascular necrosis.

Journal: European radiology
PMID:

Abstract

OBJECTIVES: To develop a deep learning methodology that distinguishes early from late stages of avascular necrosis of the hip (AVN) to determine treatment decisions.

Authors

  • Michail E Klontzas
    Department of Medical Imaging, Heraklion University Hospital, Crete, 70110, Greece; Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), N. Plastira 100, Vassilika Vouton 70013, Heraklion, Crete, Greece. Electronic address: miklontzas@ics.forth.gr.
  • Evangelia E Vassalou
    Department of Medical Imaging, University Hospital of Heraklion, Voutes, 71110, Crete, Greece.
  • Konstantinos Spanakis
    Department of Medical Imaging, University Hospital of Heraklion, Voutes, 71110, Crete, Greece.
  • Felix Meurer
    Musculoskeletal Radiology Section, TUM School of Medicine, Technical University of Munich, Ismaninger Str 22, 81675, Munich, Germany.
  • Klaus Woertler
    From the Department of Radiology (C.E.v.S., V.S.S., Y.L., F.G.G., S.C.F., F.T.G., M.R.M., K.W., A.S.G.), Department for Orthopedics and Orthopedic Sports Medicine (N.J.W., C.K., R.v.E., R.B.), and Institute of Pathology (C.M.), Klinikum Rechts der Isar, Technische Universität München, Ismaninger Str 22, 81675 Munich, Germany; and the Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, Freiburg, Germany (M.J., P.M.J., M.F.R.).
  • Aristeidis Zibis
    Department of Anatomy, Medical School, University of Thessaly, Biopolis, 41500, Larissa, Greece. Electronic address: ahzibis@uth.gr.
  • Kostas Marias
    Computational BioMedicine Laboratory, FORTH-ICS, Heraklion, Crete, Greece.
  • Apostolos H Karantanas
    Computational Biomedicine Laboratory (CBML), Foundation for Research and Technology Hellas (FORTH), 70013 Heraklion, Greece.