Description
Table of Contents
PART 1 Basics of MRI Reconstruction 1. Brief introduction to MRI physics 2. MRI reconstruction as an inverse problem 3. Optimization algorithms for MR reconstruction 4. Non-Cartesian MRI reconstruction 5. “Early constrained reconstruction methods PART 2 Reconstruction of undersampled MRI data 6. Parallel imaging 7. Simultaneous multislice reconstruction 8. Sparse reconstruction 9. Low-rank matrix and tensor–based reconstruction 10. Dictionary, structured low-rank, and manifold learning-based reconstruction 11. Machine learning for MRI reconstruction PART 3 Reconstruction methods for nonlinear forward models in MRI 12. Imaging in the presence of magnetic field inhomogeneities 13. Motion-corrected reconstruction 14. Chemical shift encoding-based water-fat separation 15. Model-based parametric mapping reconstruction 16. Quantitative susceptibility-mapping reconstruction APPENDIX A Linear algebra primer
