[Changes in FDG-PET Images of Small Lung and Liver Masses Caused by the Deep Learning-based Time-of-flight Processing].

Journal: Nihon Hoshasen Gijutsu Gakkai zasshi
PMID: 39617445

Abstract

PURPOSE: The deep learning time-of-flight (DL-ToF) aims to replicate the ToF effects through post-processing, applying deep learning-based enhancement to PET images. This study evaluates the effectiveness of DL-ToF using a chest-abdomen phantom that simulates human anatomical structures.

Authors

  • Yasuo Yamashita
    Department of Clinical Radiology, Kyushu University, Fukuoka, Japan.
  • Kazuya Hirakawa
    Department of Radiology, Division of Medical Technology, Kyushu University Hospital.
  • Satoshi Yoshidome
    Department of Radiology, Division of Medical Technology, Kyushu University Hospital.
  • Shinichi Awamoto
    Department of Radiology, Division of Medical Technology, Kyushu University Hospital.

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