Autoalign | Methodology and Technology for the Alignment of Functional Magnetic Resonance Imaging Time Series - Image Registration: The case of Functional MRI

Carlo Ciulla

ISBN 10: 3639422708 / ISBN 13: 9783639422702

Published by AV Akademikerverlag, 2012

About this Item

Autoalign | Methodology and Technology for the Alignment of Functional Magnetic Resonance Imaging Time Series - Image Registration: The case of Functional MRI | Carlo Ciulla | Taschenbuch | 332 S. | Englisch | 2012 | AV Akademikerverlag | EAN 9783639422702 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 106428613

Bibliographic Details

• Title: Autoalign | Methodology and Technology for the Alignment of Functional Magnetic Resonance Imaging Time Series - Image Registration: The case of Functional MRI
• Publisher: AV Akademikerverlag
• Publication Date: 2012
• Language: English
• ISBN 10: 3639422708
• ISBN 13: 9783639422702
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 21D millimeters 220 millimeters width by 150 millimeters height by 21 millimeters depth
• Weight: 512 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Revision with unchanged content. Functional Magnetic Resonance Imaging (FMRI) is currently acquired in Time Series to detect non-invasively, in-vivo functional activity of the human brain, thus determining four dimentional data sets. Although detectable, due to the short time in betweeen the acquisition of the brain volumes, head motion is usually minimal, however its correction is quite relevant to the consistency of the analysis of the FMRI data. This book presents methodology and technology for registering FMRI Time Series. Math formulations are given along with software engineering descriptions of the algorithms employed for the specific task of FMRI alignment. The book also presents the code that implements the methodology, which was written combining ANSI C, Open GL and Matlab. The intended audience of this work is composed by undergraduate and graduate students in academic disciplines within the domain of computer science applications, applied signal processing and computational engineering. Nevertheless this book is intented for anyone in the interests of how computer science, mathematics and engineering may combine together to forge the developmental effort in the quest for the solution of a technical challenge.

About the Author

holds the Laurea in Management Engineering (University of Palermo, Italy), the M.S. in Information Systems and the Ph.D. in Computer and Information Science (NJIT, USA). Researcher at NIBH, Japan; Yale University, University of Iowa and Wayne State University, USA; in 2007 joined LANE COLLEGE as Assistant Professor of Computer Science.