Deep learning reconstruction for accelerating synthetic magnetic resonance imaging of the breast: a comparative analysis of accelerated and standard protocols
Integrating DLR into accelerated SyMRI for breast imaging yielded a 37.46% reduction in scan time compared to that of the standard SyMRI while maintaining quantitative accuracy and image quality.
Authors
- Bo Zhang (ORCID: https://orcid.org/0000-0002-2033-9955)
- Huilou Liang (ORCID: https://orcid.org/0000-0002-6289-2767)
- Xinyu Lei (ORCID: https://orcid.org/0000-0002-0813-229X)
- Yitian Xiao (ORCID: https://orcid.org/0000-0003-2760-8158)
- Juan Huang (ORCID: https://orcid.org/0000-0003-1477-2602)
- Wei Zhang (ORCID: https://orcid.org/0000-0002-1326-6700)
- Yu Jiang (ORCID: https://orcid.org/0009-0002-5487-1701)
- Fan Yang (ORCID: https://orcid.org/0000-0002-7261-2642)
- Jiayu Sun
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-09-24
- DOI
- https://doi.org/10.21037/qims-2024-2972
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00