Fast and Stable Neonatal Brain MR Imaging Using Integrated Learned Subspace Model and Deep Learning
Fast and stable neonatal brain MR imaging can be achieved using subspace-assisted deep learning with sparse sampling. With further development, the proposed method may improve the practical utility of MRI in neonatal imaging applications.
Authors
- Tianyao Wang (ORCID: https://orcid.org/0000-0002-9349-8930)
- Jing‐Ya Ren (ORCID: https://orcid.org/0000-0002-3783-7926)
- Huixiang Zhuang
- Ziwen Ke (ORCID: https://orcid.org/0000-0003-3298-8220)
- Su‐Zhen Dong (ORCID: https://orcid.org/0000-0002-9519-3057)
- Yunpeng Zhang (ORCID: https://orcid.org/0000-0001-5144-3803)
- Yao Li (ORCID: https://orcid.org/0000-0001-5009-7443)
- Zhan‐Ling Cheng (ORCID: https://orcid.org/0000-0001-9475-2032)
- Yue Guan (ORCID: https://orcid.org/0000-0001-7773-4588)
Institutions
- Shanghai Jiao Tong University (CN)
- Shanghai Children's Medical Center (CN)
- Shanghai Sixth People's Hospital (CN)
Publication Details
- Journal
- IEEE Transactions on Biomedical Engineering
- Published
- 2025-03-12
- DOI
- https://doi.org/10.1109/tbme.2025.3541643
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00