Artificial intelligence-based joint attenuation and scatter correction strategies for multi-tracer total-body PET.
Hao SunYanchao HuangDebin HuXiaotong HongYazdan SalimiWenbing LvHongwen ChenHabib ZaidiHubing WuLijun LuPublished in: EJNMMI physics (2024)
CZ-ASC, DL-ASC and FT-ASC demonstrated the feasibility of providing accurate and robust ASC for multi-tracer total-body PET, thereby reducing the radiation hazards to patients from redundant CT examinations. CZ-ASC and FT-ASC could outperform DL-ASC for cross-tracer total-body PET AC.
Keyphrases
- positron emission tomography
- nlrp inflammasome
- artificial intelligence
- pet imaging
- computed tomography
- pet ct
- end stage renal disease
- machine learning
- chronic kidney disease
- ejection fraction
- deep learning
- newly diagnosed
- magnetic resonance imaging
- peritoneal dialysis
- prognostic factors
- dual energy
- magnetic resonance
- radiation induced
- patient reported