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
大学図書館所蔵 全7件
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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