Statistical Analysis of Noise in MRI: Modeling, Filtering by Santiago Aja-Fernández,Gonzalo Vegas-Sánchez-Ferrero

By Santiago Aja-Fernández,Gonzalo Vegas-Sánchez-Ferrero

This distinct textual content offers a finished evaluation of tools for modeling sign and noise in magnetic resonance imaging (MRI), delivering a scientific learn, classifying and evaluating the various and sundry estimation and filtering recommendations. positive aspects: offers an entire framework for the modeling and research of noise in MRI, contemplating varied modalities and acquisition options; describes noise and sign estimation for MRI from a statistical sign processing standpoint; surveys the various easy methods to get rid of noise in MRI acquisitions from a realistic perspective; reports various concepts for estimating noise from MRI information in unmarried- and multiple-coil structures for absolutely sampled acquisitions; examines the problem of noise estimation whilst sped up acquisitions are thought of, and parallel imaging tools are used to reconstruct the sign; contains appendices overlaying chance density services, mixtures of random variables used to derive estimators, and worthy MRI datasets.

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