Investigation of PET image quality with acquisition time/bed and enhancement of lesion quantification accuracy through deep progressive learning.
Hongxing YangShihao ChenMing QiWen ChenQing KongJianping ZhangShaoli SongPublished in: EJNMMI physics (2024)
The DPL algorithm dramatically enhanced the quality of PET images and enabled more accurate quantification of sub-centimeters lesions in patients and lesions in overweight or obese patients. This is particularly beneficial for overweight or obese patients who usually have lower image quality due to the increased attenuation.
Keyphrases
- image quality
- obese patients
- computed tomography
- weight loss
- bariatric surgery
- end stage renal disease
- positron emission tomography
- deep learning
- gastric bypass
- roux en y gastric bypass
- dual energy
- pet ct
- physical activity
- ejection fraction
- chronic kidney disease
- multiple sclerosis
- adipose tissue
- weight gain
- machine learning
- metabolic syndrome
- prognostic factors
- type diabetes
- magnetic resonance imaging
- body mass index
- optical coherence tomography
- patient reported outcomes
- contrast enhanced
- mass spectrometry