AlexNet approach for early stage Alzheimer’s disease detection from MRI brain images

Abstract

Alzheimer's is a neurodegenerative disorder that affects the brain and cognitive function. Early finding of Alzheimer's disorder of the beginning stages it means Mild Cognitive Impairment (MCI). It is difficult to find these issues. According to these issues, we proposed a classification model that applies the AlexNet framework to retrieve significant characteristics effectively from MRI (Magnetic Resonance Imaging) medical images to diagnose Alzheimer's at the MCI level. The proposed model is tested using a large dataset of the Open Access Series of Imaging Studies (OASIS) Brain dataset. The proposed model has taken all parts of the human brain that areaxial, sagittal, and frontal for Alzheimer's disease detection, and its yield 98.35% accuracy by using more than 1 lakh MRI Alzheimer's images.