Convolutional Neural Network based Alzheimer's Disease Prediction in MRI Images

• Published in: 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS) pp. 452 - 457
• Main Authors: Sudar, K. Muthamil, Nagaraj, P., Jeereddy, HarshaVardhan Reddy, Dasi, Likhiteswar Reddy
• Format: Conference Proceeding
• Language: English
• Published: IEEE 07.04.2022
• Subjects: Brain cells; Convolutional Neural Network; Deep learning; Electric breakdown; Firebase; Google colab; Image processing; Magnetic resonance imaging; Neurons; Proteins
• DOI: 10.1109/ICSCDS53736.2022.9760792

The neurologic illness that leads the brain to shrink (atrophy)and cells of brain to pass away is known as Alzheimer's disease. Dementia is described as a gradual deterioration of cognitive, behavioral, and social abilities that hinders the ability of a person to function alone. Alzheimer's illness is the very frequent type of dementia. An improper build-up of proteins in and around brain cells is thought to be the beginning of Alzheimer's disease. Among them the proteins implicated is amyloid, which forms plaques surrounding brain cells. Tau is the other protein that causes tangles and deposits in brain cells. The protein deposits present in the brain are yet considered to be part of the most visible indicators of Alzheimer's disease. Another symptom is the brain's breakdown of connections present among the neurons. Neurons communicate between different sections of the brain. Further areas of reasoning, like detecting proper of the terms, foresight/contiguous difficulties, faulty thinking or judgement, could in addition indicate primary periods of Alzheimer's illness. In deep learning, there are different techniques for image processing, where each technique has different accuracy.