Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

Journal: Journal of applied clinical medical physics
Published Date: Sep 5, 2023

Abstract

PURPOSE: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation.

Authors

  • Skylar S Gay
    Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Kelly D Kisling
    University of California San Diego, San Diego, California, USA.
  • Brian M Anderson
  • Lifei Zhang
    Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
  • Dong Joo Rhee
  • Callistus Nguyen
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Tucker Netherton
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas.
  • Jinzhong Yang
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Kristy Brock
  • Anuja Jhingran
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Hannah Simonds
    Division of Radiation Oncology, Stellenbosch University, Tygerberg Academic Hospital, Cape Town, South Africa.
  • Ann Klopp
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Beth M Beadle
    Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
  • Laurence E Court
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Carlos E Cardenas
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas. Electronic address: cecardenas@mdanderson.org.

Keywords

External Resources

Popular Topics
Recent Journals