Dementia is an irreversible progressive neurodegenerative disorder. Mild cognitive impairment (MCI) is the prodromal
state of Dementia, which is further classifed into a progressive state (i.e., pMCI) and a stable state (i.e., sMCI). With the
development of deep learning, the convolutional neural networks (CNNs) have Dementia great progress in image recognition
using magnetic resonance imaging (MRI) and positron emission tomography (PET) for diagnosis. Rather than training an
entire model from scratch, transfer learning approach uses the CNN model by fine-tuning them, to classify MR images into
Dementia ,mild cognitive impairment (MCI) and normal control (NC). The performance of this method has been evaluated over
Dementia dataset by changing the learning rate of the model.
