Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Title
Statistical analysis of noise in MRI [electronic resource] : modeling, filtering and estimation / Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero.
ISBN
9783319399348 (electronic book)
3319399349 (electronic book)
9783319399331
Published
Switzerland : Springer, 2016.
Language
English
Description
1 online resource (xxi, 327 pages) : illustrations.
Call Number
TK5102.9
Dewey Decimal Classification
621.382/2
004
Summary
This unique text/reference presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques drawn from more than ten years of research in this area. Topics and features: Provides a complete framework for the modeling and analysis of noise in MRI, considering different modalities and acquisition techniques Describes noise and signal estimation for MRI from a statistical signal processing perspective Surveys the different methods to remove noise in MRI acquisitions, under different approaches and from a practical point of view Reviews different techniques for estimating noise from MRI data in single- and multiple-coil systems for fully sampled acquisitions Examines the issue of noise estimation when accelerated acquisitions are considered, and parallel imaging methods are used to reconstruct the signal Includes appendices covering probability density functions, combinations of random variables used to derive estimators, and useful MRI datasets This practically-focused work serves as a reference manual for researchers dealing with signal processing in MRI acquisitions, and is also suitable as a textbook for postgraduate students in engineering with an interest in medical image processing. Dr. Santiago Aja-Fernández is an Associate Professor at the School of Telecommunications of the University of Valladolid, Spain. His other publications include the Springer title Tensors in Image Processing and Computer Vision. Dr. Gonzalo Vegas-Sánchez-Ferrero is a Research Fellow at Brigham and Women's Hospital, and in the Applied Chest Imaging Laboratory of Harvard Medical School, Boston, MA, USA.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLInk, viewed July 22, 2016).
The Problem of Noise in MRI
Part I: Noise Models and the Noise Analysis Problem
Acquisition and Reconstruction of Magnetic Resonance Imaging
Statistical Noise Models for MRI
Noise Analysis in MRI: Overview
Noise Filtering in MRI
Part II: Noise Analysis in Non-Accelerated Acquisitions
Noise Estimation in the Complex Domain
Noise Estimation in Single-Coil MR Data
Noise Estimation in Multiple-Coil MR Data
Parametric Noise Analysis from Correlated Multiple-Coil MR Data
Part III: Noise Estimators in pMRI
Parametric Noise Analysis in Parallel MRI
Blind Estimation of Non-Stationary Noise in MRI
Appendix A: Probability Distributions and Combination of Random Variables
Appendix B: Variance Stabilizing Transformation
Appendix C: Data Sets Used in the Experiments.
