Accuracy and generalization capability of an automatic method for the detection of typical brain hypometabolism in prodromal Alzheimer disease.

Fabrizio De CarliFlavio NobiliMarco PaganiMatteo BaucknehtFederico MassaMatteo GrazziniCathrine JonssonEnrico PeiraSilvia MorbelliDario Arnaldinull null

Published in: European journal of nuclear medicine and molecular imaging (2018)

The present findings show a good level of reproducibility and generalizability of a model for detecting the hypometabolic pattern in AD and confirm the accuracy of FDG-PET in Alzheimer disease.

Keyphrases

mild cognitive impairment
pet ct
positron emission tomography
pet imaging
computed tomography
resting state
deep learning
white matter
machine learning
parkinson disease
loop mediated isothermal amplification
functional connectivity
label free
multiple sclerosis
cerebral ischemia
neural network