Anomaly detection in chest F-FDG PET/CT by Bayesian deep learning.

Journal: Japanese journal of radiology
Published Date: Jan 30, 2022

Abstract

PURPOSE: To develop an anomaly detection system in PET/CT with the tracer F-fluorodeoxyglucose (FDG) that requires only normal PET/CT images for training and can detect abnormal FDG uptake at any location in the chest region.

Authors

  • Takahiro Nakao
    Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan. tanakao-tky@umin.ac.jp.
  • Shouhei Hanaoka
    Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.
  • Yukihiro Nomura
    The University of Tokyo Hospital.
  • Naoto Hayashi
    The University of Tokyo Hospital.
  • Osamu Abe
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.

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