Evaluation of the accuracy of automated segmentation based on deep learning for prostate cancer patients.

Journal: Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Published Date: Oct 8, 2024

Abstract

PURPOSE: This study evaluated the accuracy of a commercial deep learning (DL)-based algorithm for segmenting the prostate, seminal vesicles (SV), and organs at risk (OAR) in patients with prostate cancer.

Authors

  • Hideharu Miura
    Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan; Department of Radiation Oncology, Institute of Biomedical & Health Science, Hiroshima University, Hiroshima, Japan. Electronic address: miura@hiprac.jp.
  • Soichiro Ishihara
    Tada Tomohiro Institute of Gastroenterology and Proctology, Saitama, Japan; Surgery Department, Sanno Hospital, International University of Health and Welfare, Tokyo, Japan; Department of Surgical Oncology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Masahiro Kenjo
    Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan; Department of Radiation Oncology, Institute of Biomedical & Health Science, Hiroshima University, Hiroshima, Japan.
  • Minoru Nakao
    Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan; Department of Radiation Oncology, Institute of Biomedical & Health Science, Hiroshima University, Hiroshima, Japan.
  • Shuichi Ozawa
    Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan; Department of Radiation Oncology, Institute of Biomedical & Health Science, Hiroshima University, Hiroshima, Japan.
  • Masayuki Kagemoto
    Hiroshima High-Precision Radiotherapy Cancer Center, 3-2-2, Futabanosato, Higashi-ku Hiroshima 732-0057, Japan.

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