Image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance imaging.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PMID: 34139211

Abstract

INTRODUCTION: To develop an image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance (MR) imaging.

Authors

  • Bum-Sup Jang
    Department of Radiation Oncology, Seoul National University Hospital, Seoul, Korea.
  • Yu Jin Lim
    Department of Radiation Oncology, Kyung Hee University Medical Center, Kyung Hee University School of Medicine, Seoul, Republic of Korea.
  • Changhoon Song
    Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Seung Hyuck Jeon
    Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
  • Keun-Wook Lee
    Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Sung-Bum Kang
    Department of Surgery, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Yoon Jin Lee
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Korea.
  • Jae-Sung Kim
    Oral Biology Research Institute, College of Dentistry, Chosun University, Gwangju, Republic of Korea.

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