Methods for Analyzing Large Neuroimaging Datasets

432 Seiten, Hardcover

Kurzbeschreibung des Verlags

This Open Access volume 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.

• Reihe: Neuromethods
• ISBN: 9781071642597
• Sprache: Englisch
• Erscheinungsdatum: 10.12.2024
• Genre: Medizin/Nichtklinische Fächer
• Verlag: Springer US
• Herausgegeben von: Robert Whelan, Hervé Lemaître