ArticlePloS one2018
Dynamic magnetic resonance imaging method based on golden-ratio cartesian sampling and compressed sensing.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- CArtesian sampling with Variable density and Adjustable temporal resolution (CAVA).Magnetic resonance in medicine · 2020Article
- Hybrid of Compressed Sensing and Parallel Imaging Applied to Three-dimensional Isotropic TMagnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2020Article
- Performance of sparse-view CT reconstruction with multi-directional gradient operators.PloS one · 2019Article
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Authors and funding
4 authors.
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Abstract
Dynamic magnetic resonance imaging (DMRI) is used to noninvasively trace the movements of organs and the process of drug delivery. The results can provide quantitative or semiquantitative pathology-related parameters, thus giving DMRI great potential for clinical applications. However, conventional DMRI techniques suffer from low temporal resolution and long scan time owing to the limitations of the k-space sampling scheme and image reconstruction algorithm. In this paper, we propose a novel DMRI sampling scheme based on a golden-ratio Cartesian trajectory in combination with a compressed sensing reconstruction algorithm. The results of two simulation experiments, designed according to the two major DMRI techniques, showed that the proposed method can improve the temporal resolution and shorten the scan time and provide high-quality reconstructed images.
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