Fast Deformable Image Registration for Real-Time Target Tracking During Radiation Therapy Using Cine MRI and Deep Learning.

Journal: International journal of radiation oncology, biology, physics
Published Date: Oct 26, 2022

Abstract

PURPOSE: We developed a deep learning (DL) model for fast deformable image registration using 2-dimensional sagittal cine magnetic resonance imaging (MRI) acquired during radiation therapy and evaluated its potential for real-time target tracking compared with conventional image registration methods.

Authors

  • Brady Hunt
    Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, 03755.
  • Gobind S Gill
    Dartmouth Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.
  • Daniel A Alexander
    University of Pennsylvania, Philadelphia, Pennsylvania.
  • Samuel S Streeter
    Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire.
  • David J Gladstone
    Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire; Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire; Dartmouth Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.
  • Gregory A Russo
    Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire; Dartmouth Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.
  • Bassem I Zaki
    Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire; Dartmouth Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.
  • Brian W Pogue
    Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin.
  • Rongxiao Zhang

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