Deep learning-based auto-segmentation of organs at risk in high-dose rate brachytherapy of cervical cancer.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date: Apr 6, 2021

Abstract

BACKGROUND AND PURPOSE: Delineation of organs at risk (OARs), such as the bladder, rectum and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target owing to the steep gradient in high-dose rate brachytherapy (HDR-BT). In this work, we propose a deep convolutional neural network-based approach for fast and reproducible auto-contouring of OARs in HDR-BT.

Authors

  • Reza Mohammadi
    Department of Operation Management, Amsterdam Business School, University of Amsterdam, Amsterdam, Netherlands.
  • Iman Shokatian
    Department of Medical Physics, Iran University of Medical Sciences, Tehran, Iran.
  • Mohammad Salehi
    Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
  • Hossein Arabi
    Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland.
  • Isaac Shiri
    Biomedical and Health Informatics, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran.
  • Habib Zaidi
    Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland. habib.zaidi@hcuge.ch.

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