Deep learning-based low count whole-body positron emission tomography denoising incorporating computed tomography priors
Deep-learning-based LC PET denoising incorporating CT priors is more effective than conventional deep-learning-based denoising with single LC PET input, especially at lower dose levels.
Authors
- Fanwei Zhang (ORCID: https://orcid.org/0000-0002-6753-7430)
- Greta S. P. Mok (ORCID: https://orcid.org/0000-0002-2962-2087)
- Zhong‐Lin Lu (ORCID: https://orcid.org/0000-0002-7295-727X)
- Guichao Liu
- Zhengyu Peng (ORCID: https://orcid.org/0000-0002-5072-0765)
- Jingzhang Sun (ORCID: https://orcid.org/0000-0002-6961-6677)
- Han Jiang (ORCID: https://orcid.org/0000-0002-7023-1846)
- Ying Wang (ORCID: https://orcid.org/0000-0002-1407-2668)
- Yu Du
Institutions
- Fujian Medical University (CN)
- Sun Yat-sen University (CN)
- University of Macau (MO)
- Hainan University (CN)
- Fifth Affiliated Hospital of Sun Yat-sen University (CN)
- Union Hospital (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-12-01
- DOI
- https://doi.org/10.21037/qims-24-489
- Citations
- 2
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- Fundo para o Desenvolvimento das Ciências e da Tecnologia