Mehmet Akcakaya,
Mariya Ivanova Doneva,
Claudia Prieto
Elsevier Science
e druk, 2022
9780128227268
Magnetic Resonance Image Reconstruction
Theory, Methods, and Applications
Specificaties
Paperback, blz.
|
Engels
Elsevier Science |
2022
ISBN13: 9780128227268
Rubricering
Onderdeel van serie
Advances in Magnetic Resonance Technology and Applications
Levertijd ongeveer 9 werkdagen
Gratis verzonden
Samenvatting
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.
Specificaties
Inhoudsopgave
<p>PART 1 Basics of MRI Reconstruction <br>1. Brief introduction to MRI physics <br>2. MRI reconstruction as an inverse problem<br>3. Optimization algorithms for MR reconstruction<br>4. Non-Cartesian MRI reconstruction<br>5. “Early constrained reconstruction methods</p> <p>PART 2 Reconstruction of undersampled MRI data<br>6. Parallel imaging<br>7. Simultaneous multislice reconstruction<br>8. Sparse reconstruction<br>9. Low-rank matrix and tensor–based reconstruction<br>10. Dictionary, structured low-rank, and manifold learning-based reconstruction<br>11. Machine learning for MRI reconstruction</p> <p>PART 3 Reconstruction methods for nonlinear forward models in MRI<br>12. Imaging in the presence of magnetic field inhomogeneities<br>13. Motion-corrected reconstruction<br>14. Chemical shift encoding-based water-fat separation<br>15. Model-based parametric mapping reconstruction<br>16. Quantitative susceptibility-mapping reconstruction</p> <p>APPENDIX A Linear algebra primer</p>