Real-time markerless tumour tracking with patient-specific deep learning using a personalised data generation strategy: proof of concept by phantom study.

Journal: The British journal of radiology
Published Date:

Abstract

OBJECTIVE: For real-time markerless tumour tracking in stereotactic lung radiotherapy, we propose a different approach which uses patient-specific deep learning (DL) using a personalised data generation strategy, avoiding the need for collection of a large patient data set. We validated our strategy with digital phantom simulation and epoxy phantom studies.

Authors

  • Wataru Takahashi
    Department of Radiology, University of Tokyo, Tokyo.
  • Shota Oshikawa
    Technology Research Laboratory, Shimadzu Corporation, Kyoto, 619-0237, Japan.
  • Shinichiro Mori
    Research Center for Charged Particle Therapy, National Institute of Radiological Sciences, Inage-ku, Chiba 263-8555, Japan.. Electronic address: mori.shinichiro@qst.go.jp.