Deep Learning Reconstruction for 7T MP2RAGE and SPACE MRI: Improving Image Quality at High Acceleration Factors
DL-based reconstruction of 7T MRI significantly enhanced image quality compared with conventional reconstruction without introducing image artifacts. The achievable high acceleration factors have the potential to substantially improve image quality and resolution in 7T MRI.
Authors
- Hamed Mojahed
- Patrick Alexander Liebig (ORCID: https://orcid.org/0000-0001-7342-3715)
- Erin Westerhold (ORCID: https://orcid.org/0000-0002-0967-9297)
- Erik H. Middlebrooks (ORCID: https://orcid.org/0000-0002-4418-9605)
- Dominik M. Nickel (ORCID: https://orcid.org/0000-0002-0360-7233)
- Shengzhen Tao (ORCID: https://orcid.org/0000-0003-3019-3491)
- Thomas Yu (ORCID: https://orcid.org/0000-0002-5841-0198)
- Xiangzhi Zhou (ORCID: https://orcid.org/0000-0002-9214-4831)
- Vivek Gupta (ORCID: https://orcid.org/0000-0002-4298-7179)
- Vishal Patel (ORCID: https://orcid.org/0000-0002-8704-5169)
- Zeyu Liu (ORCID: https://orcid.org/0000-0001-9475-1582)
- Jun Ma (ORCID: https://orcid.org/0009-0008-0652-7424)
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- Medical Solutions (GB)
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
- Siemens Healthcare (United States) (US)
- Siemens Healthineers (Germany) (DE)
- École Polytechnique Fédérale de Lausanne (CH)
- University of Lausanne (CH)
Publication Details
- Journal
- American Journal of Neuroradiology
- Published
- 2025-05-20
- DOI
- https://doi.org/10.3174/ajnr.a8841
- Citations
- 2
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.72