Automatic 3D landmarking model using patch-based deep neural networks for CT image of oral and maxillofacial surgery.

Journal: The international journal of medical robotics + computer assisted surgery : MRCAS
Published Date: Mar 20, 2020

Abstract

BACKGROUND: Manual landmarking is a time consuming and highly professional work. Although some algorithm-based landmarking methods have been proposed, they lack flexibility and may be susceptible to data diversity.

Authors

  • Qingchuan Ma
    Department of Oral-Maxillofacial Surgery and Orthodontics, The University of Tokyo Hospital, Tokyo, Japan.
  • Etsuko Kobayashi
    Institute of Advanced BioMedical Engineering and Science, Tokyo Women's Medical University, Tokyo, Japan.
  • Bowen Fan
    Department of Precision Engineering, The University of Tokyo, Tokyo, Japan.
  • Keiichi Nakagawa
    Department of Radiology, University of Tokyo, Tokyo.
  • Ichiro Sakuma
    Department of Precision Engineering, The University of Tokyo, Tokyo, Japan.
  • Ken Masamune
    Faculty of Advanced Techno-Surgery, Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan.
  • Hideyuki Suenaga
    Department of Oral-Maxillofacial Surgery and Orthodontics, The University of Tokyo Hospital, Tokyo, Japan.

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