Authors:
Provides comprehensive coverage of the field within a single, unified framework
Presents a unique overview of the various techniques for noise estimation, explaining which method is best applied for different scanners and types of data
Includes practical solutions for noise problems that can be directly implemented in MRI-related software
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Table of contents (11 chapters)
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Front Matter
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Noise Models and the Noise Analysis Problem
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Front Matter
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Noise Analysis in Nonaccelerated Acquisitions
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Front Matter
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Noise Estimators in pMRI
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Front Matter
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Back Matter
About this book
Reviews
Authors and Affiliations
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University of Valladolid, Valladolid, Spain
Santiago Aja-Fernández
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Harvard Medical School, Boston, USA
Gonzalo Vegas-Sánchez-Ferrero
Bibliographic Information
Book Title: Statistical Analysis of Noise in MRI
Book Subtitle: Modeling, Filtering and Estimation
Authors: Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
DOI: https://doi.org/10.1007/978-3-319-39934-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2016
Hardcover ISBN: 978-3-319-39933-1Published: 27 July 2016
Softcover ISBN: 978-3-319-82000-2Published: 31 May 2018
eBook ISBN: 978-3-319-39934-8Published: 12 July 2016
Edition Number: 1
Number of Pages: XXI, 327
Number of Illustrations: 73 b/w illustrations, 99 illustrations in colour
Topics: Probability and Statistics in Computer Science, Statistics for Life Sciences, Medicine, Health Sciences, Image Processing and Computer Vision, Simulation and Modeling, Biomedical Engineering and Bioengineering