Technical Note: A deep learning-based autosegmentation of rectal tumors in MR images.

Journal: Medical physics
Published Date: May 3, 2018

Abstract

PURPOSE: Manual contouring of gross tumor volumes (GTV) is a crucial and time-consuming process in rectum cancer radiotherapy. This study aims to develop a simple deep learning-based autosegmentation algorithm to segment rectal tumors on T2-weighted MR images.

Authors

  • Jiazhou Wang
    Department of radiation oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Jiayu Lu
    Department of radiation oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Gan Qin
    Department of radiation oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Lijun Shen
    Department of radiation oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Yiqun Sun
    Department of radiation oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Hongmei Ying
    Department of radiation oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Zhen Zhang
    School of Pharmacy, Jining Medical University, Rizhao, Shandong, China.
  • Weigang Hu
    Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.

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