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Towards deep-learning (DL) based fully automated target delineation for rectal cancer neoadjuvant radiotherapy using a divide-and-conquer strategy: a study with multicenter blind and randomized validation

Crossref DOI link: https://doi.org/10.1186/s13014-023-02350-0

Published Online: 2023-10-06

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

Authors

Geng, Jianhao

Zhu, Xianggao

Liu, Zhiyan

Chen, Qi

Bai, Lu

Wang, Shaobin

Li, Yongheng

Wu, Hao

Yue, Haizhen

Du, Yi
Funding

Funding for this research was provided by:

Natural Science Foundation of Beijing Municipality (1202009)

Natural Science Foundation of Beijing Municipality (1202009)

Natural Science Foundation of Beijing Municipality (1202009)

Natural Science Foundation of Beijing Municipality (1202009)
License Information

Text and Data Mining valid from 2023-10-06

Version of Record valid from 2023-10-06
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Article History

Received: 30 May 2023

Accepted: 13 September 2023

First Online: 6 October 2023

Declarations

:

: The authors declare no competing interests.

: The study was approved by the IRB of Peking University Cancer Hospital, China.

: All the authors reviewed the manuscript and approved the final submission to <i>Radiation Oncology</i>.

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