3D dose prediction for Gamma Knife radiosurgery using deep learning and data modification.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PMID: 36724551

Abstract

PURPOSE: To develop a machine learning-based, 3D dose prediction methodology for Gamma Knife (GK) radiosurgery. The methodology accounts for cases involving targets of any number, size, and shape.

Authors

  • Binghao Zhang
    Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada. Electronic address: binghao.zhang@mail.utoronto.ca.
  • Aaron Babier
    Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, 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.
  • Mark Ruschin

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