Deep learning image reconstruction and adaptive statistical iterative reconstruction on coronary artery calcium scoring in high risk population for coronary heart disease
CACS is a powerful tool for cardiovascular risk stratification, and DLIR can improve image quality without affecting CACS, making it widely applicable in clinical practice.
Authors
- Yun Shen (ORCID: https://orcid.org/0000-0002-9850-122X)
- Lijuan Zhu (ORCID: https://orcid.org/0000-0002-1409-7443)
- Xiaomeng Shi (ORCID: https://orcid.org/0000-0002-8511-3295)
- Lili Yang (ORCID: https://orcid.org/0000-0003-0333-1684)
- Li Tang (ORCID: https://orcid.org/0000-0001-5368-490X)
- Dazhi Chen (ORCID: https://orcid.org/0000-0003-0936-4778)
- Ming Ma (ORCID: https://orcid.org/0009-0009-1208-767X)
- Haruhiko Machida (ORCID: https://orcid.org/0000-0003-2865-536X)
- Ruoshui Ha
- Fang Wang (ORCID: https://orcid.org/0009-0000-3791-5544)
Institutions
- United Imaging Healthcare (China) (CN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-07-01
- DOI
- https://doi.org/10.1186/s12911-025-03049-w
- Citations
- 1
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Natural Science Foundation of Ningxia Province