---

＜電子ブック＞
Magnetic Resonance Brain Imaging : Modelling and Data Analysis Using R / by Jörg Polzehl, Karsten Tabelow
(Use R!. ISSN:21975744)

版	2nd ed. 2023.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2023
本文言語	英語
大きさ	XXI, 258 p. 78 illus., 47 illus. in color : online resource
著者標目	*Polzehl, Jörg author Tabelow, Karsten author SpringerLink (Online service)
件　名	LCSH:Biometry LCSH:Radiology LCSH:Image processing -- Digital techniques  全ての件名で検索 LCSH:Computer vision LCSH:Mathematical statistics -- Data processing  全ての件名で検索 LCSH:Signal processing FREE:Biostatistics FREE:Radiology FREE:Computer Imaging, Vision, Pattern Recognition and Graphics FREE:Statistics and Computing FREE:Signal, Speech and Image Processing
一般注記	This book discusses modelling and analysis of Magnetic Resonance Imaging (MRI) data of the human brain. For the data processing pipelines we rely on R, the software environment for statistical computing and graphics. The book is intended for readers from two communities: Statisticians, who are interested in neuroimaging and look for an introduction to the acquired data and typical scientific problems in the field and neuroimaging students, who want to learn about the statistical modeling and analysis of MRI data. Being a practical introduction, the book focuses on those problems in data analysis for which implementations within R are available. By providing full worked-out examples the book thus serves as a tutorial for MRI analysis with R, from which the reader can derive its own data processing scripts. The book starts with a short introduction into MRI. The next chapter considers the process of reading and writing common neuroimaging data formats to and from the Rsession. The main chapters then cover four common MR imaging modalities and their data modeling and analysis problems: functional MRI, diffusion MRI, Multi-Parameter Mapping and Inversion Recovery MRI. The book concludes with extended Appendices on details of the utilize non-parametric statistics and on resources for R and MRI data. The book also addresses the issues of reproducibility and topics like data organization and description, open data and open science. It completely relies on a dynamic report generation with knitr: The books R-code and intermediate results are available for reproducibility of the examples HTTP:URL=https://doi.org/10.1007/978-3-031-38949-8

 類似資料