Artificial intelligence guided enhancement of digital PET: scans as fast as CT?

Abstract

Both digital positron emission tomography (PET) detector technologies and artificial intelligence based image post-reconstruction methods allow to reduce the PET acquisition time while maintaining diagnostic quality. The aim of this study was to acquire ultra-low-count fluorodeoxyglucose (FDG) ExtremePET images on a digital PET/computed tomography (CT) scanner at an acquisition time comparable to a CT scan and to generate synthetic full-dose PET images using an artificial neural network.

Publication
European Journal of Nuclear Medicine and Molecular Imaging
Moon Kim
Moon Kim
Team Lead Annotation Lab
Jens Kleesiek
Jens Kleesiek
Professor of Translational Image-guided Oncology
Ken Herrmann
Ken Herrmann
Chair Department of Nuclear Medicine