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Magnetic Resonance Image Reconstruction: Theory, Methods and Applications presents the fundamental concepts of MR image reconstruction, including its formulation as an invers… Read more
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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
MA
MD
CP