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Accelerated MRI using iterative non-local shrinkage
Conference proceeding

Accelerated MRI using iterative non-local shrinkage

Yasir Q Mohsin, Gregory Ongie and Mathews Jacob
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol.2014, pp.1545-1548
08/2014
DOI: 10.1109/EMBC.2014.6943897
PMID: 25570265
url
https://www.ncbi.nlm.nih.gov/pmc/articles/4411244View
Open Access

Abstract

We introduce a fast iterative non-local shrinkage algorithm to recover MRI data from undersampled Fourier measurements. This approach is enabled by the reformulation of current non-local schemes as an alternating algorithm to minimize a global criterion. The proposed algorithm alternates between a non-local shrinkage step and a quadratic subproblem. The resulting algorithm is observed to be considerably faster than current alternating non-local algorithms. We use efficient continuation strategies to minimize local minima issues. The comparisons of the proposed scheme with state-of-the-art regularization schemes show a considerable reduction in alias artifacts and preservation of edges.
denoising TV compressed sensing Magnetic resonance imaging Gaussian noise MRI non-local means Acceleration shrinkage Image reconstruction Signal to noise ratio

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