A convolution neural network for higher resolution dose prediction in prostate volumetric modulated arc therapy.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Published Date: Apr 1, 2020

Abstract

PURPOSE: This study aims to investigate the feasibility of using convolutional neural networks to predict an accurate and high resolution dose distribution from an approximated and low resolution input dose.

Authors

  • Iori Sumida
    Department of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, Osaka, Japan.
  • Taiki Magome
    Department of Radiological Sciences, Faculty of Health Sciences, Komazawa University, 1-23-1 Komazawa, Setagaya-ku, Tokyo, Japan.
  • Indra J Das
    Department of Radiation Oncology, New York University Langone Medical Center, Laura & Isaac Perlmutter Cancer Center, 160 E 34th Street, New York, NY, USA.
  • Hajime Yamaguchi
    Department of Radiation Oncology, NTT West Osaka hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka, Japan.
  • Hisao Kizaki
    Department of Radiation Oncology, NTT West Osaka hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka, Japan.
  • Keiko Aboshi
    Department of Radiation Oncology, NTT West Osaka hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka, Japan.
  • Hiroko Yamaguchi
    Department of Radiation Oncology, Daini Osaka Police Hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka 543-8922 Japan.
  • Yuji Seo
    Department of Carbon Ion Radiotherapy, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
  • Fumiaki Isohashi
    Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
  • Kazuhiko Ogawa
    Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.

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