Research ArticleAdult Brain
Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on 18F-Florbetapir PET Using ADNI Data
F. Reith, M.E. Koran, G. Davidzon and G. Zaharchuk for the Alzheimer′s Disease Neuroimaging Initiative
American Journal of Neuroradiology June 2020, 41 (6) 980-986; DOI: https://doi.org/10.3174/ajnr.A6573
F. Reith
aFrom the Departments of Radiology (F.R., M.E.K., G.D., G.Z.)
M.E. Koran
aFrom the Departments of Radiology (F.R., M.E.K., G.D., G.Z.)
bNuclear Medicine (M.E.K., G.D.), Stanford University, Stanford, California.
G. Davidzon
aFrom the Departments of Radiology (F.R., M.E.K., G.D., G.Z.)
bNuclear Medicine (M.E.K., G.D.), Stanford University, Stanford, California.
G. Zaharchuk
aFrom the Departments of Radiology (F.R., M.E.K., G.D., G.Z.)

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In this issue
American Journal of Neuroradiology
Vol. 41, Issue 6
1 Jun 2020
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F. Reith, M.E. Koran, G. Davidzon, G. Zaharchuk
Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on 18F-Florbetapir PET Using ADNI Data
American Journal of Neuroradiology Jun 2020, 41 (6) 980-986; DOI: 10.3174/ajnr.A6573
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