Machine Intelligence, Big Data Analytics, and IoT in Image Processing

1Deep Learning Techniques Using Transfer Learning for Classification of Alzheimer’s Disease

Monika Sethi¹, Sachin Ahuja²* and Puneet Bawa¹

¹ Chitkara University Institute of Engineering & Technology, Chitkara University, Punjab, India

² ED-Engineering at Chandigarh University, Punjab, India

Abstract

Alzheimer’s disease (AD) is a severe disorder in which brain cells degenerate, increasing memory loss with treatment choices for AD symptoms varying based on the disease’s stage, and as the disease progresses, individuals at certain phases undergo specific healthcare. The majority of existing studies make predictions based on a single data modality either they utilize magnetic resonance imaging (MRI)/positron emission tomography (PET)/diffusion tensor imaging (DTI) or the combination of these modalities. However, a thorough understanding of AD staging assessment can be achieved by integrating these data modalities and performance could be further enhanced using a combination of two or more modalities. However, deep learning techniques trained the network from scratch, which has the following drawbacks: (a) demands an enormous quantity of labeled training dataset that could be a problem for the medical field where physicians annotate the data, further it could be very expensive, (b) requires a huge amount of computational resources. (c) These models also require tedious and careful adjustments of numerous hyper-parameters, which results to under or overfitting and, in turn, to degraded ...