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Synthetic contrast-enhanced computed tomography generation using a deep convolutional neural network for cardiac substructure delineation in breast cancer radiation therapy: a feasibility study

Crossref DOI link: https://doi.org/10.1186/s13014-022-02051-0

Published Online: 2022-04-22

Published Print: 2022-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Chun, Jaehee

Chang, Jee Suk

Oh, Caleb

Park, InKyung

Choi, Min Seo

Hong, Chae-Seon

Kim, Hojin

Yang, Gowoon

Moon, Jin Young

Chung, Seung Yeun

Suh, Young Joo

Kim, Jin Sung https://orcid.org/0000-0003-1415-6471
Funding

Funding for this research was provided by:

Ministry of Science and ICT (2020R1A4A101661911)
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Text and Data Mining valid from 2022-04-22

Version of Record valid from 2022-04-22
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Article History

Received: 27 October 2021

Accepted: 11 April 2022

First Online: 22 April 2022

Declarations

:

: The study was approved by the Institutional Review Board of Yonsei Cancer Center (4-2020-0429). Informed consent was waived.

: All authors have approved the manuscript and agree with submission to Radiation Oncology.

: The authors declare that they have no competing interests.

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