Fast k-space sample selection in MRSI with a limited region of support

One of the primary drawbacks in the application of magnetic resonance spectroscopic imaging is the long acquisition times required to obtained the desired resolution. When region of support information is available, the number of phase-encoding steps and thus time can be reduced without loss of info...

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Bibliographic Details
Published in:IEEE transactions on medical imaging 2001-09, Vol.20 (9), p.868-876
Main Authors: Yun Gao, Reeves, S.J.
Format: Article
Language:English
Subjects:
Algorithms
Biological and medical sciences
Hardware
Heart
Image reconstruction
Image resolution
Image sampling
Investigative techniques, diagnostic techniques (general aspects)
Lipidomics
Magnetic resonance imaging
Medical sciences
Miscellaneous. Technology
Myocardium
Optical resolving power
Optimization
R&D
Radiodiagnosis. Nmr imagery. Nmr spectrometry
Real time systems
Research & development
Sampling
Spatial resolution
Spectroscopy
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Summary:One of the primary drawbacks in the application of magnetic resonance spectroscopic imaging is the long acquisition times required to obtained the desired resolution. When region of support information is available, the number of phase-encoding steps and thus time can be reduced without loss of information if the k-space locations are chosen well. The authors propose to select locations using a rectangular sampling array that is shifted to various positions in k-space to obtain the necessary sampling density. This method allows multiple samples to be selected simultaneously and reduces the computation required to evaluate the selection criterion. The authors present an efficient forward selection algorithm for optimizing the shift pattern so that the image can be reconstructed as reliably as possible from a periodic nonuniform set of samples. The proposed algorithm has important practical potential in that it can finish the selection in less than half a minute for typical image sizes and can reconstruct the image with fewer samples than regular sampling. With appropriate imaging hardware, this new algorithm makes selective sampling possible in a real-time image acquisition setting.
ISSN:0278-0062
1558-254X
DOI:10.1109/42.952725