Detection of Alzheimer’s Disease using CNN Architectures
Abstract
Alzheimer’s disease is a neurological condition that causes some structural alterations in the brain. In this paper we have given an overview of all the available good CNN models used in medical imaging for image classification purpose such asAlexNet, GoogleNet, ResNet 18, ResNet 50, SqueezeNet and DenseNet. Using these CNN models, we have been able to classify three different stages of Alzheimer's disease – Cognitively Normal (NC), Mild Cognitive Impairment (MCI) and Alzheimer’s Disease(AD). The dataset is derived from ADNI and has been preprocessed before applying various CNN models. The experimental results demonstrate that all models performed well and the best accuracy has been acquired by the GoogleNet of 96.81%.
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