Signal Processing for Magnetic Resonance Imaging and Spectroscopy

This reference/text contains the latest signal processing techniques in magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) for more efficient clinical diagnoses-providing ready-to-use algorithms for image segmentation and analysis, reconstruction and visualization, and removal of distortions and artifacts for increased detec

Hong Yan

Series Introduction, Preface, Contributors, PART I. IMAGE RECONSTRUCTION AND RESTORATION, 1. Introduction to Image Reconstruction, 2. Wavelet-Based Multiresolution Local Tomography, 3. The Point Spread Function of Convolution Regridding Reconstruction, 4. Mapping Motion and Strain with MRI, 5. Rotational Motion Artifact Correction Based on Fuzzy Projection onto Convex Sets, 6. Tagged MR Cardiac Imaging, 7. Functional MR Image Visualization and Signal Processing Methods, PART II. IMAGE SEGMENTATION AND ANALYSIS, 8. Multiscale Segmentation of Volumetric MR Brain Images, 9. A Precise Segmentation of the Cerebral Cortex from 3-D MRI Using a Cellular Model and Homotopic Deformations, 10. Feature Space Analysis of MRI, 11. Geometric Approaches for Segmentation and Signal Detection in Functional MRI Analysis, 12. MR Image Segmentation and Analysis Based on Neural Networks, 13. Stochastic Model Based Image Analysis, 14. Functional MR Image Analysis, 15. Tagged MR Image Analysis, PART III. SPECTROSCOPIC SIGNAL PROCESSING, 16. Time-Domain Spectroscopic Quantitation, 17. Multidimensional NMR Spectroscopic Signal Processing, 18. Advanced Methods in Spectroscopic Imaging, 19. Characterization of Brain Tissue from MR Spectra for Tumor Discrimination, 20. Wavelet Packets Algorithm for Metabolite Quantification in Magnetic Resonance Spectroscopy and Chemical Shift Imaging, 21. Crame-r-Rao Bound Analysis of Spectroscopic Signal Processing Methods, Index