Alzheimer's Disease Classification using Capsule Network

The most prevalent type of dementia is Alzheimer's disease, which impairs thinking, memory, and communication abilities. Better patient treatment is made possible with early disease identification. To detect and predict Alzheimer's disease through the analysis of Magnetic Resonance Images (MRIs), deep learning and big data analytics have recently been created. To improve the classification of Alzheimer's disease patients, this work utilizes capsule network. A critical evaluation is carried out on patients with Alzheimer's disease to improve stage-specific classification. Specifically, the study analyses various methods for performing abnormality identification in brain MRI images and pinpoint the shortcomings of those methods. Thus, it is possible to close the research gaps and enhance the shortcomings of different approaches to produce more accurate and superior results.