
Signal Processing for Magnetic Resonance Imaging and Spectroscopy
Hong Yan(Editor)
Marcel Dekker Inc (Publisher)
1st Edition
Published on 1. February 2002
Book
Hardback
672 pages
978-0-8247-0653-1 (ISBN)
Article exhausted; check different version
Description
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.
More details
Language
English
Place of publication
New York
United States
Publishing group
Taylor & Francis Inc
Target group
Professional and scholarly
Weight
1043 gr
ISBN-13
978-0-8247-0653-1 (9780824706531)
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Schweitzer Classification
Other editions
Additional editions

E-Book
02/2002
1st Edition
CRC Press
€357.99
Available for download

E-Book
02/2002
CRC Press
€357.99
Available for download
Person
City University of Hong Kong, Kowloon Kowloon
Content
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.