Deep Learning-Based Delineation of Head and Neck Organs at Risk: Geometric and Dosimetric Evaluation.

Journal: International journal of radiation oncology, biology, physics
Published Date: Jul 1, 2019

Abstract

PURPOSE: Organ-at-risk (OAR) delineation is a key step in treatment planning but can be time consuming, resource intensive, subject to variability, and dependent on anatomical knowledge. We studied deep learning (DL) for automated delineation of multiple OARs; in addition to geometric evaluation, the dosimetric impact of using DL contours for treatment planning was investigated.

Authors

  • Ward van Rooij
    Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiation Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands. Electronic address: w.vanrooij@vumc.nl.
  • Max Dahele
    Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
  • Hugo Ribeiro Brandao
    Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiation Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands.
  • Alexander R Delaney
    Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
  • Berend J Slotman
    Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiation Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands.
  • Wilko F Verbakel
    Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiation Oncology, Cancer Center Amsterdam, Amsterdam, the Netherlands.

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