Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning.
Zhenxing HuangWenbo LiYaping WuNannan GuoLin YangNa ZhangZhifeng PangYongfeng YangYun ZhouYue ShangHairong ZhengDong LiangMeiyun WangZhanli HuPublished in: European journal of nuclear medicine and molecular imaging (2023)
The findings demonstrate the potential of the proposed technique for improving the image quality of a PET scanner with a 320 mm or even shorter AFOV. Furthermore, this study explored the potential of utilizing uEXPLORER to achieve improved short-axis PET image quality at a limited economic cost, and computer-aided diagnosis systems that are related can help patients and radiologists.
Keyphrases
- patient safety
- image quality
- computed tomography
- quality improvement
- positron emission tomography
- deep learning
- pet ct
- dual energy
- end stage renal disease
- pet imaging
- magnetic resonance imaging
- artificial intelligence
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- prognostic factors
- contrast enhanced
- machine learning
- magnetic resonance
- risk assessment
- climate change