Performance of deep-learning reconstruction combined with metal artifact reduction algorithm for dual-energy computed tomography angiography in intracranial aneurysm coil embolization
DLIR-H+MAR at 80 keV to 90 keV proved to be the optimal method for visualizing cerebral arteries and mitigating metal artifacts. Simultaneously, it significantly enhanced the efficacy assessment and complication detection of post-embolization aneurysm.
Authors
- Songwei Yue (ORCID: https://orcid.org/0000-0003-0691-2070)
- Lina Tao (ORCID: https://orcid.org/0009-0008-9492-201X)
- Limin Lei (ORCID: https://orcid.org/0000-0001-7304-2955)
- Yajie Wang (ORCID: https://orcid.org/0000-0001-7259-3886)
- Xiaoxu Guo (ORCID: https://orcid.org/0000-0002-5917-377X)
- Yuhan Zhou (ORCID: https://orcid.org/0000-0002-0250-7783)
- Yifan Guo (ORCID: https://orcid.org/0000-0003-1875-7821)
Institutions
- First Affiliated Hospital of Zhengzhou University (CN)
Publication Details
- Journal
- European Journal of Radiology Open
- Published
- 2025-12-12
- DOI
- https://doi.org/10.1016/j.ejro.2025.100715
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Key Scientific Research Project of Colleges and Universities in Henan Province