Machine Learning and Deep Learning in Neuroimaging Data Analysis

Anitha S. Pillai, Bindu Menon, Anitha S. Pillai, Bindu Menon

• Publisher: CRC Press
• Year: 2024
• Print ISBN: 9781032190686
• eBook ISBN: 9781003815600
• Topic: Computer Science
• Subtopic: Computer Vision & Pattern Recognition
• Index: Computer Science

Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.

Table of contents

• Cover
• Half Title Page
• Title Page
• Copyright Page
• Table of Contents
• Contributors
• Chapter 1 ◾ Neuroimaging and Deep Learning in Stroke Diagnosis: A Review of a Decade of Research
• Chapter 2 ◾ Artificial Intelligence in Stroke Imaging
• Chapter 3 ◾ Applications of Machine Learning and Deep Learning Models in Brain Imaging Analysis
• Chapter 4 ◾ A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis
• Chapter 5 ◾ A Framework for Brain Tumor Image Compression with Principal Component Analysis: Application of Machine Learning in Neuroimaging
• Chapter 6 ◾ Role of Artificial Intelligence in Neuroimaging for Cognitive Research
• Chapter 7 ◾ Machine Learning and Deep Learning in Deep Brain Stimulation Targeting for Parkinson’s Disease
• Index