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arXiv · 1302.0077

Sparse MRI for motion correction

Zai Yang·Cishen Zhang·Lihua Xie
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Abstract

MR image sparsity/compressibility has been widely exploited for imaging acceleration with the development of compressed sensing. A sparsity-based approach to rigid-body motion correction is presented for the first time in this paper. A motion is sought after such that the compensated MR image is maximally sparse/compressible among the infinite candidates. Iterative algorithms are proposed that jointly estimate the motion and the image content. The proposed method has a lot of merits, such as no need of additional data and loose requirement for the sampling sequence. Promising results are presented to demonstrate its performance.

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BibTeXRIS

Zai Yang, Cishen Zhang, Lihua Xie. 2013-02-01. Sparse MRI for motion correction. https://arxiv.org/abs/1302.0077

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