Non-uniform sparsity in rapid compressive sensing MRI

Razzaq, Fuleah A., Mohamed, Shady, Bhatti, Asim and Nahavandi, Saeid 2012, Non-uniform sparsity in rapid compressive sensing MRI, in SMC 2012 : Proceedings of the 2012 IEEE International Conference on Systems, Man, and Cybernetics, IEEE, Piscataway, N.J., pp. 2253-2258, doi: 10.1109/ICSMC.2012.6378076.

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Title Non-uniform sparsity in rapid compressive sensing MRI
Author(s) Razzaq, Fuleah A.
Mohamed, ShadyORCID iD for Mohamed, Shady orcid.org/0000-0002-8851-1635
Bhatti, AsimORCID iD for Bhatti, Asim orcid.org/0000-0001-6876-1437
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Conference name IEEE Systems, Man and Cybernetics. Conference (2012 : Seoul, Korea)
Conference location Seoul, Korea
Conference dates 14-17 Oct. 2012
Title of proceedings SMC 2012 : Proceedings of the 2012 IEEE International Conference on Systems, Man, and Cybernetics
Editor(s) [Unknown]
Publication date 2012
Conference series IEEE Systems, Man and Cybernetics Conference
Start page 2253
End page 2258
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) compressive sensing
fourier transform
L1 minimization
magnetic resonance imaging
signal-to noise ratio (SNR)
sparse signals
Summary Magnetic Resonance Imaging (MRI) is one of the prominent medical imaging techniques. This process is time-consuming and can take several minutes to acquire one image. The aim of this research is to reduce the imaging process time of MRI. This issue is addressed by reducing the number of acquired measurements using theory of Compressive Sensing (CS). Compressive Sensing exploits sparsity in MR images. Randomly under sampled k-space generates incoherent noise which can be handled using a nonlinear image reconstruction method. In this paper, a new framework is presented based on the idea to exploit non-uniform nature of sparsity in MR images, where local sparsity constrains were used instead of traditional global constraint, to further reduce the sample set. Experimental results and comparison with CS using global constraint are demonstrated.
ISBN 9781467317146
Language eng
DOI 10.1109/ICSMC.2012.6378076
Field of Research 080401 Coding and Information Theory
Socio Economic Objective 929999 Health not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2012, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30050968

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