Sinogram‐characteristic‐informed network for efficient restoration of low‐dose SPECT projection data
Our proposed SCI-Net exhibits promising performance in the restoration of low-dose SPECT projection data. In the SCI-Net, we have implemented three mechanisms based on distinct forms, which are advantageous for the model to more effectively leverage the characteristics of sinograms and achieve commendable restoration outcomes.
Authors
- Ruifan Wu (ORCID: https://orcid.org/0000-0003-4917-5197)
- Lai Peng (ORCID: https://orcid.org/0000-0002-7464-1607)
- Haotian Liu (ORCID: https://orcid.org/0000-0003-2872-4740)
- Haiying Li (ORCID: https://orcid.org/0000-0002-8229-764X)
- Ying Jiang (ORCID: https://orcid.org/0000-0002-6448-103X)
- Woliang Yuan (ORCID: https://orcid.org/0009-0009-4998-0816)
Institutions
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1002/mp.17459
- Citations
- 1
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- Natural Science Foundation of Guangdong Province
- National Key Research and Development Program of China
- Special Project for Research and Development in Key areas of Guangdong Province