Assessing the deep learning based image quality enhancements for the BGO based GE omni legend PET/CT
This study conducted a thorough evaluation of deep learning algorithms in the GE Omni Legend PET/CT scanner, demonstrating that these methods enhance image quality, with notable improvements in CRC and CNR, thereby optimizing lesion detectability and offering opportunities to reduce image acquisition time.
Authors
- Jens Maebe (ORCID: https://orcid.org/0000-0003-3991-7943)
- Stefaan Vandenberghe (ORCID: https://orcid.org/0000-0002-2377-3968)
- Alain Verstraete (ORCID: https://orcid.org/0000-0002-0956-3315)
- M. Dadgar (ORCID: https://orcid.org/0000-0002-7160-5715)
- Yves D'Asseler
Institutions
- Ghent University (BE)
Publication Details
- Journal
- EJNMMI Physics
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1186/s40658-024-00688-2
- Citations
- 10
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 4.04