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Название: Signal Processing for Magnetic Resonance Imaging and Spectroscopy
Автор: Yan H.
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 detection of disease.
Detailing cost-effective procedures for improved image and spectrum quality, Signal Processing for Magnetic Resonance Imaging and Spectroscopy discusses the evaluation of specific shapes and geometric features in MR images; modern strategies for MR data processing; the characterization and analysis of cerebral, muscular, and cardiac tissues; wavelet transform and projection on convex sets (POCS), methods for image reconstruction, restoration, and enhancement; and effective methods for the reduction of ghost artifacts.