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Non-uniform sparsity in rapid compressive sensing MRI
conference contributionposted on 2012-01-01, 00:00 authored by F Razzaq, Shady MohamedShady Mohamed, Asim BhattiAsim Bhatti, Saeid NahavandiSaeid Nahavandi
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.
EventIEEE Systems, Man and Cybernetics. Conference (2012 : Seoul, Korea)
Pagination2253 - 2258
Place of publicationPiscataway, N.J.
Publication classificationE1 Full written paper - refereed
Copyright notice2012, IEEE
Title of proceedingsSMC 2012 : Proceedings of the 2012 IEEE International Conference on Systems, Man, and Cybernetics
Read the peer-reviewed publication
compressive sensingfourier transformL1 minimizationmagnetic resonance imagingsignal-to noise ratio (SNR)sparse signalsScience & TechnologyTechnologyComputer Science, CyberneticsComputer Science, Information SystemsEngineering, Electrical & ElectronicComputer ScienceEngineeringIMAGE-RECONSTRUCTIONK-SPACE