Magnetic Resonance Image Reconstruction: Theory, Methods and Applications

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. Explains the underlying principles of MRI reconstruction, along with the latest research Gives example codes for some of the methods presented Includes updates on the latest developments, including compressed sensing, tensor-based reconstruction and machine learning based reconstruction INDICE: Introduction, Fundamental Concepts 1. Introduction to MR image acquisition and signal encoding 2. Intro to MR reconstruction as an inverse problem 3. Model based MRI reconstruction 4. Optimisation algorithms for MRI reconstruction Undersampled Reconstruction Methods 5. Non-Cartesian MRI reconstruction 6. Parallel Imaging 7. Compressed Sensing 8. Low-rank approaches 9. Tensor-based techniques 10. Dictionary-learning based reconstruction 11. Deep-learning based reconstruction Applications 12. Dynamic MRI reconstruction 13. Motion compensated reconstruction 14. Quantitative MRI reconstruction

• ISBN: 978-0-12-822726-8
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 375
• Fecha Publicación: 01/10/2022
• Nº Volúmenes: 1
• Idioma: Inglés