Comparison of respiratory-gated and breath‑hold accelerated T2-weighted sequences for liver MRI with deep learning reconstruction
Respiratory-gated and breath-hold deep learning T2WI exhibited satisfactory image quality. Respiratory curve traits variably impact T2WI quality, guiding personalized imaging workflows. Respiratory-gated deep learning-reconstructed T2WI benefits patients with breath-holding difficulties in liver MRI.
Authors
- Hualing Li (ORCID: https://orcid.org/0000-0002-9416-7770)
- Qiufeng Liu
- Yanping Luo
- Chenglin Hu
- Xuemei Hu
- Runyu Tang
- Gen Chen
- Zhen Li
- Yang Yang
- Qiuxia Wang
Institutions
- Tianjin University (CN)
- United Imaging Healthcare (China) (CN)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- European Radiology Experimental
- Published
- 2026-02-23
- DOI
- https://doi.org/10.1186/s41747-026-00679-1
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Tongji University
- Health and Family Planning Commission of Hubei Province