Preprint
Iterative Non-Local Shrinkage Algorithm for MR Image Reconstruction
ArXiv.org
05/15/2014
DOI: 10.48550/arXiv.1405.5494
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. We derive analytical
shrinkage rules for several penalties that are relevant in non-local
regularization. The redundancy in the searches used to evaluate the shrinkage
steps are exploited using filtering operations. The resulting algorithm is
observed to be considerably faster than current alternating non-local
algorithms. The comparisons of the proposed scheme with state-of-the-art
regularization schemes show a considerable reduction in alias artifacts and
preservation of edges.
Details
- Title: Subtitle
- Iterative Non-Local Shrinkage Algorithm for MR Image Reconstruction
- Creators
- Yasir Q MoshinGreg OngieMathews Jacob
- Resource Type
- Preprint
- Publication Details
- ArXiv.org
- DOI
- 10.48550/arXiv.1405.5494
- ISSN
- 2331-8422
- Language
- English
- Date posted
- 05/15/2014
- Academic Unit
- Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984071711202771
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