Alzheimer's Disease Classification using Convolutional Neural Networks

Deep learning has got tremendous popularity in recent years for addressing problems in wide range of sectors, including medical image research. Alzheimer's Disease (AD) is a broad brain degeneration-related neurodegenerative disease that causes progressive mental decline in both middle-aged and elderly people. Imaging and laboratory testing can rule out additional potential causes and helps in the diagnosis the symptoms of dementia. Adults who have Alzheimer's disease have varied degrees of memory loss and knowledge forgetting. This the statement implies that how much its important in for the early disease diagnosis. In this article, deep learning techniques are implemented to classify brain neuro images such as MRI dataset ADNI into groups for Mild cognitive impairment (MCI), Alzheimer's Disease (AD), Cognitively Normal (CN) and Healthy Person. According to the results, CNN's classification rate was outperformed by the images being classified with accuracy of 95.82%.