Assessing the deep learning based image quality enhancements for the BGO based GE omni legend PET/CT

Assessing the deep learning based image quality enhancements for the BGO based GE omni legend PET/CT

Abstract Background This study investigates the integration of Artificial Intelligence (AI) in compensating the lack of time-of-flight (TOF) of the GE Omni Legend PET/CT, which utilizes BGO scintillation crystals. Methods The current study evaluates the image quality of the GE Omni Legend PET/CT usi...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Meysam Dadgar, Amaryllis Verstraete, Jens Maebe, Yves D’Asseler, Stefaan Vandenberghe
Format: Artykuł
Język:English
Wydane: SpringerOpen 2024-10-01
Seria:EJNMMI Physics
Hasła przedmiotowe:
Time of flight
Contrast recovery coefficient
Background variability
Contrast to noise ratio
Deep learning
GE Omni Legend
Dostęp online:https://doi.org/10.1186/s40658-024-00688-2

Internet

https://doi.org/10.1186/s40658-024-00688-2

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