Deep learning dose prediction for IMRT of esophageal cancer: The effect of data quality and quantity on model performance.

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)
Published Date: Mar 10, 2021

Abstract

PURPOSE: To investigate the effect of data quality and quantity on the performance of deep learning (DL) models, for dose prediction of intensity-modulated radiotherapy (IMRT) of esophageal cancer.

Authors

  • Ana M Barragán-Montero
    Molecular Imaging, Radiotherapy and Oncology (MIRO), UCLouvain, Brussels, Belgium.
  • Melissa Thomas
    KU Leuven - Department of Oncology - Laboratory of Experimental Radiotherapy, Leuven, Belgium; University Hospitals Leuven, Department of Radiation Oncology, 3000 Leuven, Belgium.
  • Gilles Defraene
    KU Leuven - Department of Oncology - Laboratory of Experimental Radiotherapy, Leuven, Belgium.
  • Steven Michiels
    Molecular Imaging, Radiation and Oncology (MIRO) Laboratory, UCLouvain, Belgium.
  • Karin Haustermans
    KU Leuven - Department of Oncology - Laboratory of Experimental Radiotherapy, Leuven, Belgium; University Hospitals Leuven, Department of Radiation Oncology, 3000 Leuven, Belgium.
  • John A Lee
    Molecular Imaging, Radiation and Oncology (MIRO) Laboratory, UCLouvain, Belgium.
  • Edmond Sterpin
    Center of Molecular Imaging, Radiotherapy and Oncology (MIRO), UCLouvain, Brussels, Belgium.

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