Signal processing for magnetic resonance imaging and spectroscopy
著者
書誌事項
Signal processing for magnetic resonance imaging and spectroscopy
（Signal processing and communications series, 15）
Marcel Dekker, c2002
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
- Introduction to image reconstruction
- wavelet-based multiresolution local tomography
- the point spread function of convolution regridding reconstruction
- mapping motion and strain with MRI
- rotational motion artifact suppression based on fuzzy POCS
- tagged MR cardiac imaging
- functional MR image visualization and signal processing methods
- multiscale segmentation of volumetric MR brain images
- a precise segmentation of the cerebral cortex from 3D MRI using cellular model and homotopic deformations
- feature space analysis of MRI
- geometric approaches for segmentation and signal detection in functional MRI analysis
- MR image segmentation and analysis based on neural networks
- stochastic model based image analysis
- functional MR image analysis
- tagged MRI image analysis.
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