Automated landmarking for palatal shape analysis using geometric deep learning.

Journal: Orthodontics & craniofacial research
Published Date: Dec 1, 2021

Abstract

OBJECTIVES: To develop and evaluate a geometric deep-learning network to automatically place seven palatal landmarks on digitized maxillary dental casts.

Authors

  • Balder Croquet
    Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
  • Harold Matthews
    Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
  • Jules Mertens
    Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
  • Yi Fan
    Facial Science Research Group, Murdoch Children's Research Institute, Parkville, Australia.
  • Nele Nauwelaers
    Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
  • Soha Mahdi
    Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
  • Hanne Hoskens
    Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
  • Ahmed El Sergani
    Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Tianmin Xu
  • Dirk Vandermeulen
    Department of Electrical Engineering - ESAT/PSI, KU Leuven, Leuven, Belgium.
  • Michael Bronstein
    Department of Computing, Faculty of Engineering, Imperial College London, London, SW7 2AZ, UK.
  • Mary Marazita
    Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, Department of Human Genetics University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Seth Weinberg
    Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Peter Claes
    Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.

Keywords

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