1st Edition

Diagnosis of Neurological Disorders Based on Deep Learning Techniques

Edited By Jyotismita Chaki Copyright 2023
236 Pages 81 B/W Illustrations
by CRC Press

236 Pages 81 B/W Illustrations
by CRC Press

236 Pages 81 B/W Illustrations
by CRC Press

This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders. It includes application of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional... Read more

Chapter 1 Introduction to Deep Learning Techniques for Diagnosis of Neurological Disorders
Jyotismita Chaki

Chapter 2 A Comprehensive Study of Data Pre-Processing Techniques for Neurological Disease (NLD) Detection
G. Chemmalar Selvi, G.G. Lakshmi Priya, M. Sabrina, S. Sharanya, Y. Laasya, N. Sunaina, and K. Usha

Chapter 3 Classification of the Level of Alzheimer’s Disease Using Anatomical Magnetic Resonance Images Based on a Novel Deep Learning Structure
Saif Al-Jumaili, Athar Al-Azzawi, Osman Nuri Uçan, and Adil Deniz Duru

Chapter 4 Detection of Alzheimer’s Disease Stages Based on Deep Learning Architectures from MRI Images
Febin Antony, Anita H B, and Jincy A George

Chapter 5 Analysis on Detection of Alzheimer’s using Deep Neural Network
Keerthika C and Anisha M. Lal

Chapter 6 Detection and Classification of Alzheimer’s Disease: A Deep Learning Approach with Predictor Variables
Deepthi K. Oommen and J. Arunnehru

Chapter 7 Classification of Brain Tumor Using Optimized Deep Neural Network Models
P. Chitra

Chapter 8 Fully Automated Segmentation of Brain Stroke Lesions Using Mask Region-Based Convolutional Neural Network
Emre Dandıl and Mehmet Süleyman Yıldırım

Chapter 9 Efficient Classification of Schizophrenia EEG Signals Using Deep Learning Methods
Subha D. Puthankattil, Marrapu Vynatheya, and Ahsan Ali

Chapter 10 Implementation of a Deep Neural Network-Based Framework for Actigraphy Analysis and Prediction of Schizophrenia
Vijayalakshmi G V Mahesh, Alex Noel Joseph Raj, and Chandraprabha R

Chapter 11 Evaluating Psychomotor Skills in Autism Spectrum Disorder Through Deep Learning
Ravi Kant Avvari

Chapter 12 Dementia Detection with Deep Networks Using Multi-Modal Image Data
Altuğ Yiğit, Zerrin Işık, and Yalın Baştanlar

Chapter 13 The Importance of the Internet of Things in Neurological Disorder: A Literature Review
Pelin Alcan

Biography

Jyotismita Chaki, PhD, is an Associate Professor in School of Computer Science and Engineering at Vellore Institute of Technology, Vellore, India. She gained her PhD (Engg.) from Jadavpur University, Kolkata, India. Her research interests include computer vision and image processing, pattern recognition, medical imaging, artificial intelligence, and machine learning. Jyotismita has authored more than 40 international conference and journal papers and is the author and editor of more than eight books. Currently, she is the Academic Editor of PLOS One journal and PeerJ Computer Science journal and Associate Editor of IET Image Processing journal, Array journal, and Machine Learning with Applications journal.