@book {660,
	title = {Statistical Analysis of Noise in MRI. Modeling, Filtering and Estimation},
	year = {2016},
	pages = {327},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Switzerland},
	abstract = {<p>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.</p>
},
	issn = {978-3-319-39933-1},
	doi = {http://dx.doi.org/10.1007/978-3-319-39934-8},
	url = {http://link.springer.com/book/10.1007/978-3-319-39934-8},
	author = {Santiago Aja-Fern{\'a}ndez and Gonzalo Vegas-S{\'a}nchez-Ferrero}
}
