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EJNMMI Research
Fig. 2 | EJNMMI Research

Fig. 2

From: Deep learning-based amyloid PET positivity classification model in the Alzheimer’s disease continuum by using 2-[18F]FDG PET

Fig. 2

Convolutional neural network architecture in 2.5 dimensions (2.5-D). A total of 291 2-D images were used as inputs for the model. 291 number of prediction values obtained from 291 submodules pass through the fully connected layer for the final prediction. Abbreviation: Conv = convolution layer; MaxPool = Max pooling layer; FC = fully connected layer

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