The popularity of magnetic resonance (MR) imaging in medicine is no mystery: it is non-invasive, it produces high quality structural and functional image data, and it is very versatile and flexible. Research into MR technology is advancing at a blistering pace, and modern engineers must keep up with the latest developments. This is only possible with a firm grounding in the basic principles of MR, and Advanced Image Processing in Magnetic Resonance Imaging solidly integrates this foundational knowledge with the latest advances in the field. Beginning with the basics of signal and image generation and reconstruction, the book covers in detail the signal processing techniques and algorithms, filtering techniques for MR images, quantitative analysis including image registration and integration of EEG and MEG techniques with MR, and MR spectroscopy techniques. The final section of the book explores functional MRI (fMRI) in detail, discussing fundamentals and advanced exploratory data analysis, Bayesian inference, and nonlinear analysis. Many of the results presented in the book are derived from the contributors' own work, imparting highly practical experience through experimental and numerical methods. Contributed by international experts at the forefront of the field, Advanced Image Processing in Magnetic Resonance Imaging is an indispensable guide for anyone interested in further advancing the technology and capabilities of MR imaging.describe the main modes of variation in the training set and the eigenvalues the amount of variance explained by each mode. ... Point distribution models (PDMs) represent the shape model described earlier, without image matching. ... Training samples are manual segmentations expressed as binary volumes, and point correspondence is achieved by fitting a template mesh with a fixed-point topology toanbsp;...
|Title||:||Advanced Image Processing in Magnetic Resonance Imaging|
|Author||:||Luigi Landini, Vincenzo Positano, Maria Santarelli|
|Publisher||:||CRC Press - 2005-09-13|