Generation of synthetic PET images of synaptic density and amyloid from ¹⁸F‐FDG images using deep learning

Abstract

It is feasible to use 3D U-Net-based methods to generate synthetic ¹¹ C-UCB-J PET images from ¹⁸ F-FDG images with reasonable prediction accuracy. It is also possible to predict ¹¹ C-PiB SUVR images from ¹⁸ F-FDG images, though the incorporation of additional non-imaging information is needed.