Fast and accurate dose predictions for novel radiotherapy treatments in heterogeneous phantoms using conditional 3D‐UNet generative adversarial networks-Reference-Cited by-同舟云学术

Fast and accurate dose predictions for novel radiotherapy treatments in heterogeneous phantoms using conditional 3D‐UNet generative adversarial networks

Published:2022-03-03 Issue:5 Volume:49 Page:3389-3404
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Mentzel Florian¹,Kröninger Kevin¹,Lerch Michael²³,Nackenhorst Olaf¹,Paino Jason²³,Rosenfeld Anatoly²³,Saraswati Ayu⁴,Tsoi Ah Chung⁴,Weingarten Jens¹,Hagenbuchner Markus⁴,Guatelli Susanna³⁴

Affiliation:

1. Department of Physics TU Dortmund University Dortmund Germany

2. Centre for Medical Radiation Physics University of Wollongong Wollongong New South Wales Australia

3. Illawarra Health and Medical Research Institute University of Wollongong Wollongong New South Wales Australia

4. School of Computing and Information Technology University of Wollongong Wollongong New South Wales Australia

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15555

Reference47 articles.