Dose image prediction for range and width verifications from carbon ion-induced secondary electron bremsstrahlung x-rays using deep learning workflow.

Journal: Medical physics
Published Date: May 25, 2020

Abstract

PURPOSE: Imaging of the secondary electron bremsstrahlung (SEB) x rays emitted during particle-ion irradiation is a promising method for beam range estimation. However, the SEB x-ray images are not directly correlated to the dose images. In addition, limited spatial resolution of the x-ray camera and low-count situation may impede correctly estimating the beam range and width in SEB x-ray images. To overcome these limitations of the SEB x-ray images measured by the x-ray camera, a deep learning (DL) approach was proposed in this work to predict the dose images for estimating the range and width of the carbon ion beam on the measured SEB x-ray images.

Authors

  • Mitsutaka Yamaguchi
    Takasaki Advanced Radiation Research Institute, Quantum Beam Science Research Directorate, National Institutes for Quantum and Radiological Science (QST), Takasaki, Japan.
  • Chih-Chieh Liu
    Department of Biomedical Engineering, University of California, Davis, CA, United States of America.
  • Hsuan-Ming Huang
  • Takuya Yabe
    Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Takashi Akagi
    Hyogo Ion Beam Medical Center, Tatsuno, Japan.
  • Naoki Kawachi
    Takasaki Advanced Radiation Research Institute, Quantum Beam Science Research Directorate, National Institutes for Quantum and Radiological Science (QST), Takasaki, Japan.
  • Seiichi Yamamoto
    Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.

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