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Development of in-house fully residual deep convolutional neural network-based segmentation software for the male pelvic CT

Published Online: 2021-07-22

Published Print: 2021-12

Authors

Hirashima, Hideaki

Nakamura, Mitsuhiro http://orcid.org/0000-0001-5007-8808
Baillehache, Pascal

Fujimoto, Yusuke

Nakagawa, Shota

Saruya, Yusuke

Kabasawa, Tatsumasa

Mizowaki, Takashi
Funding

Funding for this research was provided by:

japan society for the promotion of science (18H02766)

japan society for the promotion of science (18J14790)
License Information

Text and Data Mining valid from 2021-07-22

Version of Record valid from 2021-07-22
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Article History

Received: 15 June 2021

Accepted: 19 July 2021

First Online: 22 July 2021

Declarations

:

: This study followed all dictates of the Declaration of Helsinki and the Ethics Review Board of Kyoto University Hospital, and the Faculty of Medicine approved the research (approval number R1499). Written consent to participate was obtained from the patient.

: Written consent was obtained from the patients for publication of this report and any accompanying images.

: This work was performed in collaboration with Rist Inc.

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