Knowledge-based automated planning with three-dimensional generative adversarial networks.

Journal: Medical physics
Published Date: Nov 29, 2019

Abstract

PURPOSE: To develop a knowledge-based automated planning pipeline that generates treatment plans without feature engineering, using deep neural network architectures for predicting three-dimensional (3D) dose.

Authors

  • Aaron Babier
    Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada.
  • Rafid Mahmood
    Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, ON, M5S 3G8, Canada.
  • Andrea L McNiven
    Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, ON, M5T 2M9, Canada.
  • Adam Diamant
    Schulich School of Business, York University, 111 Ian MacDonald Blvd, North York, ON, M3J 1P3, Canada.
  • Timothy C Y Chan
    Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5, Canada.

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