Classification and Structuring of DL-Based Method for Finding Alzheimer’s Disease through MRI Images

Alzheimer’s disease (AD) is a type of neurological disorder that progresses over a period and affects a significant number of people worldwide. Early detection of AD is necessary for rapid intervention and improved outcomes for patients. In this paper, we compare the performance of four widely used Deep Convolutional Neural Network (DCNN) architectures: CNN, VGG16, InceptionV3, and DenseNet121. The study focuses on the use of DCNNs for AD identification. Our dataset is collected from the Kaggle website and preprocessed such that the inputs are identical for every model. Several criteria are used to assess the DCNN architecture’s performance, including recall, accuracy, precision, and f1-score. By looking at individual architecture’s predictive capabilities, we may discover further the benefits and drawbacks of AD detection jobs. Also, transfer learning techniques employ pre-trained weights from large neuroimaging datasets to enhance model performance and generalization abilities. This study contributes to the increasing body of knowledge in AD research by identifying the ideal DCNN architecture for fast and accurate AD diagnosis.

I. Introduction

Alzheimer’s disease (AD) is an irreversible neurological condition that impairs thinking abilities, memory loss, and cognitive decline. The illness is a neurodegenerative form of dementia characterized by gradually worsening symptoms. The current Alzheimer’s disease population in America is above six million. It is generally acknowledged that the primary cause of dementia is Alzheimer’s disease. Brain-damaged tissue may lead to dementia. Due to this damage, brain cells cannot effectively interact with one another, resulting in a decline in cognitive and behavioral capacities [1]. Alterations in cell-to-cell protein levels are associated with Alzheimer’s disease and disrupt neuronal communication in the hippocampus. The hippocampus region of the brain is responsible for learning and memory. It is more probable that brain cell destruction will occur in the hippocampus [2]. For this reason, memory problems are often the first indicators of Alzheimer’s disease.