Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy.

Journal: Radiation oncology (London, England)
Published Date: Oct 14, 2021

Abstract

PURPOSE: To study the performance of a proposed deep learning-based autocontouring system in delineating organs at risk (OARs) in breast radiotherapy with a group of experts.

Authors

  • Hwa Kyung Byun
    Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
  • Jee Suk Chang
    Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea. Electronic address: changjeesuk@yuhs.ac.
  • Min Seo Choi
    Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.
  • Jaehee Chun
    Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, 63110, USA.
  • Jinhong Jung
    Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, Republic of Korea.
  • Chiyoung Jeong
    Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, South Korea.
  • Jin Sung Kim
    Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.
  • Yongjin Chang
    CorelineSoft, Co, Ltd, Seoul, Korea.
  • Seung Yeun Chung
    Department of Radiation Oncology, Ajou University School of Medicine, Suwon, South Korea.
  • Seungryul Lee
    Yonsei University College of Medicine, Seoul, South Korea.
  • Yong Bae Kim
    Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea.

Keywords

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