Different techniques for Alzheimer's disease classification using brain images: a study

Alzheimer's disease (AD) is a kind of dementia that is mostly experienced by people who are in the age of early 60s. In AD, brain cells that are responsible for forming memories and cognitive decisions, get affected which causes overall gray matter shrinkage in the human brain. Since AD patients are growing exponentially in the world, researchers are trying to develop an accurate mechanism for diagnosing the disease using brain images. In this paper, several research articles on AD classification are analyzed along with detailed observations. We have summarized as well as compared the research articles based on their classification performance. Although all the reviewed articles have the potential to classify AD, still there lies major future challenges. Among all the reviewed papers, it is found that the recent deep neural network-based classification techniques can produce the most promising results with an average performance rate of 93%.