Crossmark

Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study

Crossref DOI link: https://doi.org/10.1007/s00330-022-09127-1

Published Online: 2022-09-17

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

Authors

Fukutomi, Akiyo

Sofue, Keitaro https://orcid.org/0000-0001-6132-1623
Ueshima, Eisuke

Negi, Noriyuki

Ueno, Yoshiko

Tsujita, Yushi

Yabe, Shinji

Yamaguchi, Takeru

Shimada, Ryuji

Kusaka, Akiko

Hori, Masatoshi

Murakami, Takamichi
License Information

Text and Data Mining valid from 2022-09-17

Version of Record valid from 2022-09-17
More Information

Article History

Received: 21 July 2022

Revised: 21 July 2022

Accepted: 19 August 2022

First Online: 17 September 2022

Declarations

:

: The scientific guarantor of this publication is Keitaro Sofue.

: The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

: No complex statistical methods were necessary for this paper.

: Written informed consent was waived by the Institutional Review Board.

: Institutional Review Board approval was obtained.

: • retrospective• observational/experimental• performed at one institution

Document is current

Any future updates will be listed below