Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate Cancers.

Journal: JAMA network open
Published Date: Nov 2, 2020

Abstract

IMPORTANCE: Personalized radiotherapy planning depends on high-quality delineation of target tumors and surrounding organs at risk (OARs). This process puts additional time burdens on oncologists and introduces variability among both experts and institutions.

Authors

  • Ozan Oktay
  • Jay Nanavati
    Health Intelligence, Microsoft Research, Cambridge, United Kingdom.
  • Anton Schwaighofer
    Health Intelligence, Microsoft Research, Cambridge, United Kingdom.
  • David Carter
    Microsoft Research Cambridge, Cambridge, United Kingdom.
  • Melissa Bristow
    Health Intelligence, Microsoft Research, Cambridge, United Kingdom.
  • Ryutaro Tanno
    Centre for Medical Image Computing and Department of Computer Science, UCL, Gower Street, London WC1E 6BT, UK; Healthcare Intelligence, Microsoft Research Cambridge, UK. Electronic address: r.tanno@cs.ucl.ac.uk.
  • Rajesh Jena
    Health Intelligence, Microsoft Research, Cambridge, United Kingdom.
  • Gill Barnett
    Health Intelligence, Microsoft Research, Cambridge, United Kingdom.
  • David Noble
    Department of Oncology, Cambridge University Hospitals NHS Foundation Trust, United Kingdom.
  • Yvonne Rimmer
    Department of Oncology, Cambridge University Hospitals NHS Foundation Trust, United Kingdom.
  • Ben Glocker
    Kheiron Medical Technologies, London, UK.
  • Kenton O'Hara
    Health Intelligence, Microsoft Research, Cambridge, United Kingdom.
  • Christopher Bishop
    Health Intelligence, Microsoft Research, Cambridge, United Kingdom.
  • Javier Alvarez-Valle
    Health Intelligence, Microsoft Research, Cambridge, United Kingdom.
  • Aditya Nori
    Microsoft Research Cambridge, Cambridge, United Kingdom.

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