Paper Info
Title
Mr Spectroscopic Image Reconstruction Using Structural Information From Anatomical Mr Images
Abstract
Spectroscopic imaging (SI) techniques combine the ability of NAIR spectroscopy to identify and measure biochemical constituents with the ability of MR imaging to localize NAIR signals. The basic imaging technique acquires a set of spatial-frequency-domain samples on a regular grid and takes an inverse Fourier transform of the acquired data to obtain the spatial-domain image. Unfortunately, the time required to gather the data while maintaining an adequate signal-to-noise ratio (SNR) limits the number of spatial-frequency-domain samples that can be acquired. In this paper, we use a high-resolution MR, scout image to obtain edge locations in the sample imaged with MRSI. MRI discontinuities represent boundaries between different tissue types, and these discontinuities are likely to appear in the spectroscopic image as well. We propose a new model that encourages edge formation in the MRSI image reconstruction wherever AIR image edges occur. A major difference between our model and previous methods is that an edge found in the AIR image need not be confirmed by the data; smoothing is reduced across the edge if either the MR image or the MRSI data suggests an edge. Simulations and results on in vivo MRSI data are presented that demonstrate the effectiveness of the method.
Year
DOI
Venue
2003
10.1117/12.479701
COMPUTATIONAL IMAGING
Keywords
Field
DocType
magnetic resonance imaging, spectroscopic imaging, Bayesian methods, image reconstruction
Iterative reconstruction,Computer vision,Classification of discontinuities,Regular grid,Computer science,Signal-to-noise ratio,Fourier transform,Smoothing,Artificial intelligence,Image restoration,Magnetic resonance spectroscopic imaging
Conference
Volume
ISSN
Citations 
5016
0277-786X
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Thomas S. Denney Jr.1379.17
Stanley J. Reeves213833.98