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Statistical Analysis of Noise in MRI

Modeling, Filtering and Estimation

  • Book
  • © 2016

Overview

Authors:
  1. Santiago Aja-Fernández

    1. University of Valladolid, Valladolid, Spain

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    You can also search for this author in PubMed   Google Scholar

  2. Gonzalo Vegas-Sánchez-Ferrero

    1. Harvard Medical School, Boston, USA

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    You can also search for this author in PubMed   Google Scholar

  • 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)

  1. Front Matter

    Pages i-xxi
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  2. The Problem of Noise in MRI

    • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
    Pages 1-6

  3. Noise Models and the Noise Analysis Problem

    1. Front Matter

      Pages 7-7
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    2. Acquisition and Reconstruction of Magnetic Resonance Imaging

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 9-29

    3. Statistical Noise Models for MRI

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 31-71

    4. Noise Analysis in MRI: Overview

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 73-88

    5. Noise Filtering in MRI

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 89-119

  4. Noise Analysis in Nonaccelerated Acquisitions

    1. Front Matter

      Pages 121-121
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    2. Noise Estimation in the Complex Domain

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 123-140

    3. Noise Estimation in Single-Coil MR Data

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 141-171

    4. Noise Estimation in Multiple–Coil MR Data

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 173-186

    5. Parametric Noise Analysis from Correlated Multiple-Coil MR Data

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 187-207

  5. Noise Estimators in pMRI

    1. Front Matter

      Pages 209-209
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    2. Parametric Noise Analysis in Parallel MRI

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 211-228

    3. Blind Estimation of Non-stationary Noise in MRI

      • Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
      Pages 229-274

  6. Back Matter

    Pages 275-327
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Keywords

About this book

This unique text 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. 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 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 usefulMRI datasets.

Reviews

“The book is presented in a simple and lucid manner, starting with the basics of MRI noise and its analysis with simple models, progressing to an analysis using complex models and the noise issues in multi-coil and parallel acquisition schemes. Overall the book is self-contained to help the beginners … .” (Pramod Kumar Pisharady, IAPR Newsletter , Vol. 40 (2), 2018)

Authors and Affiliations

  • University of Valladolid, Valladolid, Spain

    Santiago Aja-Fernández

  • Harvard Medical School, Boston, USA

    Gonzalo Vegas-Sánchez-Ferrero

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