IMRT QA using machine learning: A multi-institutional validation.

Journal: Journal of applied clinical medical physics
Published Date: Aug 17, 2017

Abstract

PURPOSE: To validate a machine learning approach to Virtual intensity-modulated radiation therapy (IMRT) quality assurance (QA) for accurately predicting gamma passing rates using different measurement approaches at different institutions.

Authors

  • Gilmer Valdes
    Department of Radiation Oncology, University of California, San Francisco, California.
  • Maria F Chan
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States.
  • Seng Boh Lim
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Ryan Scheuermann
    Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Joseph O Deasy
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Timothy D Solberg
    U.S. Food and Drug Administration, Silver Spring, Maryland.

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