Statistical Analysis of Noise in MRI, Softcover reprint of the original 1st ed. 2016
Modeling, Filtering and Estimation

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.

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