Visual interpretation of [F]Florbetaben PET supported by deep learning-based estimation of amyloid burden.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Apr 1, 2021

Abstract

PURPOSE: Amyloid PET which has been widely used for noninvasive assessment of cortical amyloid burden is visually interpreted in the clinical setting. As a fast and easy-to-use visual interpretation support system, we analyze whether the deep learning-based end-to-end estimation of amyloid burden improves inter-reader agreement as well as the confidence of the visual reading.

Authors

  • Ji-Young Kim
    Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Dongkyu Oh
    Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Kiyoung Sung
    Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
  • Hongyoon Choi
    Cheonan Public Health Center, 234-1 Buldang-Dong, Seobuk-Gu, Cheonan, Republic of Korea.
  • Jin Chul Paeng
    Department of Nuclear Medicine, Seoul National University, Seoul, Korea.
  • Gi Jeong Cheon
    Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Keon Wook Kang
    Seoul National University Hospital, Seoul, Republic of Korea.
  • Dong Young Lee
    Department of Neuropsychiatry, Seoul National University, Seoul, Korea.
  • Dong Soo Lee
    Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.

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