Accelerated 3D whole-heart non-contrast-enhanced mDIXON coronary MR angiography using deep learning-constrained compressed sensing reconstruction
Current coronary MRA techniques are limited by scan time and the need for noise reduction. DL-CS reduced the scan time in coronary MR angiography. Deep learning achieved the highest image quality among the three methods. Deep learning-based coronary MR angiography demonstrated high performance compared to CT angiography.
Authors
- Xun Yue (ORCID: https://orcid.org/0000-0003-2539-4811)
- Lei Li (ORCID: https://orcid.org/0000-0001-8089-9164)
- Xian-Zheng Tan (ORCID: https://orcid.org/0000-0001-9319-1237)
- Xi Wu (ORCID: https://orcid.org/0000-0002-1248-3420)
- Pengfei Peng (ORCID: https://orcid.org/0000-0001-8381-551X)
- Feng Huang (ORCID: https://orcid.org/0000-0002-0740-9373)
- Xiaoyong Zhang (ORCID: https://orcid.org/0000-0002-2978-3892)
- Peng Liu (ORCID: https://orcid.org/0000-0003-2798-2932)
- Lei Cai (ORCID: https://orcid.org/0000-0002-3942-1414)
- Shuai He (ORCID: https://orcid.org/0000-0001-5048-5999)
- Jiayu Sun (ORCID: https://orcid.org/0000-0002-0920-5948)
Institutions
- Hunan Normal University (CN)
- Sichuan University (CN)
- Philips (China) (CN)
- West China Hospital of Sichuan University (CN)
- Hunan Provincial People's Hospital (CN)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1186/s13244-024-01797-3
- Citations
- 7
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.83