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Magnetic Resonance Image Reconstruction
Theory, Methods, and Applications
Gives researchers and students the fundamentals and state-of-the-art methods in Magnetic Resonance Image Reconstruction, including applications
Mehmet Akcakaya (Edited by), Mariya Ivanova Doneva (Edited by), Claudia Prieto (Edited by)
9780128227268, Elsevier Science
Paperback, published 11 November 2022
516 pages, 75 illustrations (45 in full color)
23.5 x 19 x 3.2 cm, 1 kg
Magnetic Resonance Image Reconstruction: Theory, Methods and Applications presents the fundamental concepts of MR image reconstruction, including its formulation as an inverse problem, as well as the most common models and optimization methods for reconstructing MR images. The book discusses approaches for specific applications such as non-Cartesian imaging, under sampled reconstruction, motion correction, dynamic imaging and quantitative MRI. This unique resource is suitable for physicists, engineers, technologists and clinicians with an interest in medical image reconstruction and MRI.
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
Subject Areas: Physics [PH]
