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Non-uniform sparsity in rapid compressive sensing MRI
conference contribution
posted on 2012-01-01, 00:00 authored by F Razzaq, Shady MohamedShady Mohamed, Asim BhattiAsim Bhatti, Saeid NahavandiMagnetic 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.
History
Event
IEEE Systems, Man and Cybernetics. Conference (2012 : Seoul, Korea)Pagination
2253 - 2258Publisher
IEEELocation
Seoul, KoreaPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2012-10-14End date
2012-10-17ISBN-13
9781467317146Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2012, IEEETitle of proceedings
SMC 2012 : Proceedings of the 2012 IEEE International Conference on Systems, Man, and CyberneticsUsage metrics
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compressive sensingfourier transformL1 minimizationmagnetic resonance imagingsignal-to noise ratio (SNR)sparse signalsScience & TechnologyTechnologyComputer Science, CyberneticsComputer Science, Information SystemsEngineering, Electrical & ElectronicComputer ScienceEngineeringIMAGE-RECONSTRUCTIONK-SPACE
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