Enhancing photon-counting computed tomography reconstruction via subspace dictionary learning and spatial sparsity regularization
The experimental results indicate that the proposed algorithm effectively reduces computational costs while improving the accuracy of image reconstruction and material decomposition, showing promising advantages over the compared method.
Authors
- Zhizhong Zheng (ORCID: https://orcid.org/0000-0002-9470-6770)
- Ailong Cai (ORCID: https://orcid.org/0000-0001-6128-0876)
- Xing Qi (ORCID: https://orcid.org/0009-0004-0941-0134)
- Bin Yan (ORCID: https://orcid.org/0000-0001-8268-559X)
- Lei Li (ORCID: https://orcid.org/0000-0003-2882-2447)
Institutions
- PLA Information Engineering University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-12-31
- DOI
- https://doi.org/10.21037/qims-24-1248
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00