Accelerated Chemical Exchange Saturation Transfer Imaging With Deep Unrolling Networks and Synthetic Brain Tumor Datasets
The proposed MoDL-ADMM, trained with the BraTS-CEST synthetic dataset, effectively reconstructed high-quality CEST source images and APTw maps from undersampled multi-channel data.
Authors
- Kannie W. Y. Chan (ORCID: https://orcid.org/0000-0002-7315-1550)
- Yi‐Cheng Hsu (ORCID: https://orcid.org/0000-0002-9504-8757)
- Jianping Xu (ORCID: https://orcid.org/0000-0003-2872-8274)
- Yi Zhang (ORCID: https://orcid.org/0000-0001-8738-1851)
- Junjie Wen (ORCID: https://orcid.org/0009-0002-6629-434X)
- Zhechuan Dai
- Yuyan Wang (ORCID: https://orcid.org/0009-0005-7049-3351)
Institutions
- City University of Hong Kong (HK)
- Siemens Healthcare (United States) (US)
- Siemens (China) (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2025-11-05
- DOI
- https://doi.org/10.1002/mrm.70172
- Primary Topic
- Lanthanide and Transition Metal Complexes
- Type
- article
- Field-Weighted Citation Impact
- 0.00