Methods for Analyzing Large Neuroimaging Datasets
Book Details
| Authors | Robert Whelan, Hervé Lemaître |
| Publisher | Humana Press |
| Published | 2025 |
| Edition | 1st |
| Paperback | 432 pages |
| Language | English |
| ISBN-13 | 9781071642597, 9781071642627, 9781071642603 |
| ISBN-10 | 1071642596, 1071642626, 107164260X |
| License | Creative Commons Attribution |
Book Description
This open access book explores the latest advancements and challenges in standardized methodologies, efficient code management, and scalable data processing of neuroimaging datasets. The chapters in this book are organized in four parts. Part One shows the researcher how to access and download large datasets, and how to compute at scale. Part Two covers best practices for working with large data, including how to build reproducible pipelines and how to use Git. Part Three looks at how to do structural and functional preprocessing data at scale, and Part Four describes various toolboxes for interrogating large neuroimaging datasets, including machine learning and deep learning approaches. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory.
Authoritative and comprehensive, Methods for Analyzing Large Neuroimaging Datasets is a valuable resource that will help researchers obtain the practical knowledge necessary for conducting robust and reproducible analyses of large neuroimaging datasets.
This book is available under a Creative Commons Attribution license (CC BY), which means that you are free to copy, distribute, and modify it, as long as you give appropriate credit to the original author.
If you enjoyed the book and would like to support the author, you can purchase a printed copy (hardcover or paperback) from official retailers.
Download and Read Links
Share this Book
[localhost]# find . -name "*Similar_Books*"
Programming Computer Vision with Python
If you want a basic understanding of computer vision's underlying theory and algorithms, this hands-on introduction is the ideal place to start. You'll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python. Programming Comp
Web Application Security
While many resources for network and IT security are available, detailed knowledge regarding modern web application security has been lacking - until now. This practical guide provides both offensive and defensive security concepts that software engineers can easily learn and apply. Andrew Hoffman, a senior security engineer at Salesforce, introduc
Efficient Learning Machines
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, cla
Learning Neo4j
Neo4j is the world's leading graph database and offers users a radical new way of dealing with connected data. This book has been created to help you get to grips with it, providing you with an accessible route through a tool built to contend with the complexity of modern data. Learn the fundamental concepts behind Neo4j, and put them into practice
Git Notes for Professionals
The Git Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow.
Digital Video Concepts, Methods, and Metrics
Digital Video Concepts, Methods, and Metrics: Quality, Compression, Performance, and Power Trade-off Analysis is a concise reference for professionals in a wide range of applications and vocations. It focuses on giving the reader mastery over the concepts, methods and metrics of digital video coding, so that readers have sufficient understanding to