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Accelerating brain T2-weighted imaging using artificial intelligence–assisted compressed sensing combined with deep learning-based reconstruction: a feasibility study at 5.0T MRI

Crossref DOI link: https://doi.org/10.1186/s12880-025-01763-5

Published Online: 2025-07-01

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

Authors

Wen, Yun

Ma, Huan

Xiang, Shaoxin

Feng, Zhichao

Guan, Chuanjiang

Li, Xiang
Funding

Funding for this research was provided by:

Chongqing Key Medical Discipline (zdxk202116)

Science-Health Joint Medical Scientific Research Project of Chongqing (2025MSXM157)
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Text and Data Mining valid from 2025-07-01

Version of Record valid from 2025-07-01
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Article History

Received: 20 March 2025

Accepted: 3 June 2025

First Online: 1 July 2025

Declarations

:

: This study was approved by the ethics committee of Chongqing University Three Gorges Hospital (KS-2024157). All patient-related procedures performed in this study were in accordance with the local legislation. Informed consent was obtained from all participants.

: All data have been anonymized to adhere to ethical standards, with explicit consent obtained from the participants, and all authors have provided their consent for this manuscript’s publication.

: The authors declare no competing interests.

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