Post-reconstruction enhancement of [18F]FDG PET images with a convolutional neural network

Background The aim of the study was to develop and test an artificial intelligence (AI)-based method to improve the quality of [ 18 F]fluorodeoxyglucose (FDG) positron emission tomography (PET) images. Methods A convolutional neural network (CNN) was trained by using pairs of excellent (acquisition time of 6 min/bed position) and standard (acquisition time of 1.5 min/bed position) or sub-standard (acquisition time of 1 min/bed position) images...