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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.)
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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.
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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.
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G. Zaharchuk
aFrom the Departments of Radiology (F.R., M.E.K., G.D., G.Z.)
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American Journal of Neuroradiology: 41 (6)
American Journal of Neuroradiology
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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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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, G. Zaharchuk
American Journal of Neuroradiology Jun 2020, 41 (6) 980-986; DOI: 10.3174/ajnr.A6573
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