Bidirectional dynamic frame prediction network for total-body [68Ga]Ga-PSMA-11 and [68Ga]Ga-FAPI-04 PET images
In this work, we propose a bidirectional dynamic frame prediction network for total-body <sup>68</sup>Ga-PSMA and <sup>68</sup>Ga-FAPI PET imaging with a reduced scan duration. Visual and quantitative analyses demonstrated that our approach performed well when it was used to predict one-hour dynamic PET images. https://github.com/OPMZZZ/BDF-NET .
Authors
- Zhenxing Huang (ORCID: https://orcid.org/0000-0001-5012-1992)
- Hairong Zheng (ORCID: https://orcid.org/0000-0002-8558-5102)
- Zhanli Hu (ORCID: https://orcid.org/0000-0003-0618-6240)
- Xinlan Yang
- Ruohua Chen (ORCID: https://orcid.org/0009-0007-9944-4320)
- Wenjie Zhao (ORCID: https://orcid.org/0000-0002-2872-599X)
- Zixiang Chen (ORCID: https://orcid.org/0000-0002-9042-4477)
- Wenbo Li (ORCID: https://orcid.org/0000-0002-0199-1534)
- Yunlong Gao (ORCID: https://orcid.org/0009-0005-4858-3545)
- Yongfeng Yang (ORCID: https://orcid.org/0000-0003-1642-6631)
- Dong Liang (ORCID: https://orcid.org/0000-0001-6257-0875)
- Qianyi Yang
- Jianjun Liu (ORCID: https://orcid.org/0000-0001-5195-9535)
Institutions
- Shanghai Jiao Tong University (CN)
- Chinese Academy of Sciences (CN)
- Renji Hospital (CN)
- United Imaging Healthcare (China) (CN)
- Shenzhen Institutes of Advanced Technology (CN)
- Northeastern University (CN)
Publication Details
- Journal
- EJNMMI Physics
- Published
- 2024-11-04
- DOI
- https://doi.org/10.1186/s40658-024-00698-0
- Citations
- 1
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province