A deep learning approach for 18F-FDG PET attenuation correction.

Fang LiuHyungseok JangRichard KijowskiGengyan ZhaoTyler BradshawAlan B McMillan

Published in: EJNMMI physics (2018)

We have developed an automated approach (deepAC) that allows generation of a continuously valued pseudo-CT from a single 18F-FDG non-attenuation-corrected (NAC) PET image and evaluated it in PET/CT brain imaging.

Keyphrases

pet ct
deep learning
positron emission tomography
high resolution
computed tomography
artificial intelligence
transcription factor
convolutional neural network
white matter
resting state
dual energy
contrast enhanced
machine learning
pet imaging
magnetic resonance imaging
magnetic resonance
fluorescence imaging