[Retracted] Diagnosis of Alzheimer Disease Using 2D MRI Slices by Convolutional Neural Network

Figure 3

Block diagram of proposed system (AlzNet). There are five convolutional layers; after each convolutional layer there is a max-pooling layer; the activation function in every convolutional layer was ReLU. After the convolution layers and flattening layer, there is a dense unit 121 with a ReLU as an activation function, with a dropout to prevent overfitting, then there is a dense unit and sigmoid as an activation function; at the last stage, there is a binary classifier.