H. Ombao – Handbook of Neuroimaging Data Analysis (2017)

Автор: H. Ombao
Название книги: Handbook of Neuroimaging Data Analysis
Формат: PDF
Жанр: Медицина
Страницы: 667
Качество: Изначально компьютерное, E-book

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.

Preface

With this handbook, we summarize the state-of-the-art in the statistical modeling and
analysis of neuroimaging data and point out the current challenges. Our goal is that this
will provide statisticians and other quantitative researchers with an introduction to important
active research areas in neuroimaging data analysis, and provide them with a path to
contribute to this rapidly emerging area covering both theoretical and applied statistics.
There are challenges to the statistical analysis of neuroimaging data. It is a massive
data problem; in most cases the signal of interest is relatively weak; the data exhibit a
complicated spatio-temporal correlation structure. Today statistics plays an integral role
in neuroimaging data analysis. It is truly an exciting time to be involved in neuroimaging
research as increasingly ambitious experiments are being performed daily. This creates a signi
cant new demand, and an unmatched opportunity, for quantitative researchers working
in the neurosciences.
Understanding human brain structure and function is arguably one of the most complex,
important and challenging issues in science today. For this endeavor to be successful,
researchers are needed to make sense of the massive amounts of data being generated.
Our sincere hope is that this book can in some way aid in this development, by providing
researchers with an introduction to the fascinating world of neuroimaging data analysis.