Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning.PURPOSE
 This study investigated parametric [Formula: see text] images directly generated from static PET images without an image-derived input function on a 2-m total-body PET/CT scanner (uEXPLORER) using a deep learning model to significantly reduce the dynamic scanning time and improve patient comfort.


 Moreover, this study explored the potential of direct parametric image generation with uEXPLORER. 
uEXPLORER
Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning.PURPOSE
 The findings illustrated the feasibility of the proposed technique and its potential to reduce the required scanning duration for 2-m total-body dynamic PET/CT systems. 
PET/CT system
This study investigated parametric [Formula: see text] images directly generated from static PET images without an image-derived input function on a 2-m total-body PET/CT scanner (uEXPLORER) using a deep learning model to significantly reduce the dynamic scanning time and improve patient comfort.


 A deep learning model was implemented to predict parametric [Formula: see text] images from the static PET images. 
deep learning model