• The Problem of Noise in MRI.- Part I: Noise Models and the Noise Analysis Problem.- Acquisition and Reconstruction of Magnetic Resonance Imaging.- Statistical Noise Models for MRI.- Noise Analysis in MRI: Overview.- Noise Filtering in MRI.- Part II: Noise Analysis in Non-Accelerated Acquisitions.- Noise Estimation in the Complex Domain.- Noise Estimation in Single-Coil MR Data.- Noise Estimation in Multiple-Coil MR Data.- Parametric Noise Analysis from Correlated Multiple-Coil MR Data.- Part III: Noise Estimators in pMRI.- Parametric Noise Analysis in Parallel MRI.- Blind Estimation of Non-Stationary Noise in MRI.- Appendix A: Probability Distributions and Combination of Random Variables.- Appendix B: Variance Stabilizing Transformation.- Appendix C: Data Sets Used in the Experiments.

“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)

• The Problem of Noise in MRI.- Part I: Noise Models and the Noise Analysis Problem.- Acquisition and Reconstruction of Magnetic Resonance Imaging.- Statistical Noise Models for MRI.- Noise Analysis in MRI: Overview.- Noise Filtering in MRI.- Part II: Noise Analysis in Non-Accelerated Acquisitions.- Noise Estimation in the Complex Domain.- Noise Estimation in Single-Coil MR Data.- Noise Estimation in Multiple-Coil MR Data.- Parametric Noise Analysis from Correlated Multiple-Coil MR Data.- Part III: Noise Estimators in pMRI.- Parametric Noise Analysis in Parallel MRI.- Blind Estimation of Non-Stationary Noise in MRI.- Appendix A: Probability Distributions and Combination of Random Variables.- Appendix B: Variance Stabilizing Transformation.- Appendix C: Data Sets Used in the Experiments.

“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)

• The Problem of Noise in MRI.- Part I: Noise Models and the Noise Analysis Problem.- Acquisition and Reconstruction of Magnetic Resonance Imaging.- Statistical Noise Models for MRI.- Noise Analysis in MRI: Overview.- Noise Filtering in MRI.- Part II: Noise Analysis in Non-Accelerated Acquisitions.- Noise Estimation in the Complex Domain.- Noise Estimation in Single-Coil MR Data.- Noise Estimation in Multiple-Coil MR Data.- Parametric Noise Analysis from Correlated Multiple-Coil MR Data.- Part III: Noise Estimators in pMRI.- Parametric Noise Analysis in Parallel MRI.- Blind Estimation of Non-Stationary Noise in MRI.- Appendix A: Probability Distributions and Combination of Random Variables.- Appendix B: Variance Stabilizing Transformation.- Appendix C: Data Sets Used in the Experiments.

“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)