Crossmark

Fully automated identification of brain abnormality from whole-body FDG-PET imaging using deep learning-based brain extraction and statistical parametric mapping

Crossref DOI link: https://doi.org/10.1186/s40658-021-00424-0

Published Online: 2021-11-14

Published Print: 2021-12

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

Authors

Whi, Wonseok

Choi, Hongyoon

Paeng, Jin Chul

Cheon, Gi Jeong

Kang, Keon Wook

Lee, Dong Soo
Funding

Funding for this research was provided by:

National Research Foundation of Korea (NRF-2019R1F1A1061412)

National Research Foundation of Korea (NRF-2019K1A3A1A14065446)

Ministry of Science, ICT and Future Planning (202011A06)

Seoul R&BD Program (BT200151)
License Information

Text and Data Mining valid from 2021-11-14

Version of Record valid from 2021-11-14
More Information

Article History

Received: 28 April 2021

Accepted: 29 October 2021

First Online: 14 November 2021

Declarations

:

: All procedures performed were in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards (SNUH IRB No. 2104-046-1209).

: Not applicable.

: The authors declare that they have no competing interests.

Document is current

Any future updates will be listed below