Methods for Analyzing Large Neuroimaging Datasets - Couverture souple

Couverture souple

ISBN 10 : 1071642626 ISBN 13 : 9781071642627

Editeur : Humana, 2025

Synopsis

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.

Détails de l'édition

• Éditeur: Humana
• Date d'édition: 2025
• Langue: anglais
• ISBN 10: 1071642626
• ISBN 13: 9781071642627
• Reliure: Broché
• Nombre de pages: 444
• Éditeur: Whelan Robert, Lemaître Hervé
• Coordonnées du fabricant: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Allemagne