Technical note: Minimizing CIED artifacts on a 0.35 T MRI-Linac using deep learning

Authors

Austen N Curcuru, Washington University School of Medicine in St. Louis
Deshan Yang, Duke University
Hongyu An, Washington University School of Medicine in St. Louis
Phillip S Cuculich, Washington University School of Medicine in St. Louis
Clifford G Robinson, Washington University School of Medicine in St. Louis
H Michael Gach, Washington University School of Medicine in St. Louis

Journal

Journal of applied clinical medical physics

Publication Date

3-1-2024

Volume

25

Issue

3

First Page

e14304

Document Type

Open Access Publication

DOI

10.1002/acm2.14304

Rights and Permissions

Curcuru AN, Yang D, An H, Cuculich PS, Robinson CG, Gach HM. Technical note: Minimizing CIED artifacts on a 0.35 T MRI-Linac using deep learning. J Appl Clin Med Phys. 2024; 25:e14304. https://doi.org/10.1002/acm2.14304 © 2024 The Authors. Journal of Applied Clinical Medical Physics is published by Wiley Periodicals, Inc. on behalf of The American Association of Physicists in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Recommended Citation

Curcuru, Austen N; Yang, Deshan; An, Hongyu; Cuculich, Phillip S; Robinson, Clifford G; and Gach, H Michael, "Technical note: Minimizing CIED artifacts on a 0.35 T MRI-Linac using deep learning." Journal of applied clinical medical physics. 25, 3. e14304 (2024).
https://digitalcommons.wustl.edu/oa_4/4387

Department

ICTS (Institute of Clinical and Translational Sciences)

Additional Links

Supplemental material is available for this article at publisher site.