Magnetic Resonance Image Reconstruction
portes grátis
Magnetic Resonance Image Reconstruction
Theory, Methods, and Applications
Doneva, Mariya Ivanova; Prieto, Claudia; Akcakaya, Mehmet
Elsevier Science Publishing Co Inc
11/2022
516
Mole
Inglês
9780128227268
15 a 20 dias
Descrição não disponível.
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
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
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Magnetic Resonance Imaging; Inverse problems; Image Reconstruction; Medical imaging; Undersampled Reconstruction, Compressed Sensing; Machine Learning Reconstruction
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
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
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
