Hybrid Analysis for Detection of Alzheimer Disease Using Computer Aided Diagnostic Tool

Brain image analysis, a significant field in clinical research, is employed to detect brain diseases. Alzheimer's disease is an irreversible, progressive neurological disorder characterized by the loss of neurotransmitters, leading to cognitive and mental decline. Detecting Alzheimer's disease early can facilitate appropriate treatment and prevent brain tissue damage. It is one of the most common causes of dementia, resulting in significant impairments in cognitive functions like memory, reasoning, and social skills, affecting daily life. This neurodegenerative form of dementia advances slowly over time, with decreased brain activity and blood flow being primary contributors to Alzheimer's. In the initial stages of the disease, rapid tissue loss in the hippocampus is observed, which is associated with functional impairment in other brain regions. Consequently, there is extensive research on segmenting clinical images, with various methods, including the Gaussian Mixture Model (GMM) segmentation technique, being employed for this purpose. Gaussian Mixture Models (GMM) can effectively separate the brain's white and gray matter. By extracting features from brain images, these characteristics can then be utilized to classify Alzheimer's disease.