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.
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