Statistical Analysis of Noise in MRI

Modeling, Filtering and Estimation

Nonfiction, Health & Well Being, Medical, Reference, Biostatistics, Computers, Application Software, General Computing
Cover of the book Statistical Analysis of Noise in MRI by Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero, Springer International Publishing
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Author: Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero ISBN: 9783319399348
Publisher: Springer International Publishing Publication: July 12, 2016
Imprint: Springer Language: English
Author: Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
ISBN: 9783319399348
Publisher: Springer International Publishing
Publication: July 12, 2016
Imprint: Springer
Language: English

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 useful MRI datasets.

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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 useful MRI datasets.

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