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The influence of radial undersampling schemes on compressed sensing reconstruction in breast MRI.
Magn Reson Med 2012; 67(2):363-77MR

Abstract

Fast imaging applications in magnetic resonance imaging (MRI) frequently involve undersampling of k-space data to achieve the desired temporal resolution. However, high temporal resolution images generated from undersampled data suffer from aliasing artifacts. In radial k-space sampling, this manifests as undesirable streaks that obscure image detail. Compressed sensing reconstruction has been shown to reduce such streak artifacts, based on the assumption of image sparsity. Here, compressed sensing is implemented with three different radial sampling schemes (golden-angle, bit-reversed, and random sampling), which are compared over a range of spatiotemporal resolutions. The sampling methods are implemented in static scenarios where different undersampling patterns could be compared. Results from point spread function studies, simulations, phantom and in vivo experiments show that the choice of radial sampling pattern influences the quality of the final image reconstructed by the compressed sensing algorithm. While evenly undersampled radial trajectories are best for specific temporal resolutions, golden-angle radial sampling results in the least overall error when various temporal resolutions are considered. Reduced temporal fluctuations from aliasing artifacts in golden-angle sampling translates to improved compressed sensing reconstructions overall.

Authors+Show Affiliations

Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.No affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article

Language

eng

PubMed ID

21656558

Citation

Chan, Rachel W., et al. "The Influence of Radial Undersampling Schemes On Compressed Sensing Reconstruction in Breast MRI." Magnetic Resonance in Medicine, vol. 67, no. 2, 2012, pp. 363-77.
Chan RW, Ramsay EA, Cheung EY, et al. The influence of radial undersampling schemes on compressed sensing reconstruction in breast MRI. Magn Reson Med. 2012;67(2):363-77.
Chan, R. W., Ramsay, E. A., Cheung, E. Y., & Plewes, D. B. (2012). The influence of radial undersampling schemes on compressed sensing reconstruction in breast MRI. Magnetic Resonance in Medicine, 67(2), pp. 363-77. doi:10.1002/mrm.23008.
Chan RW, et al. The Influence of Radial Undersampling Schemes On Compressed Sensing Reconstruction in Breast MRI. Magn Reson Med. 2012;67(2):363-77. PubMed PMID: 21656558.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - The influence of radial undersampling schemes on compressed sensing reconstruction in breast MRI. AU - Chan,Rachel W, AU - Ramsay,Elizabeth A, AU - Cheung,Edward Y, AU - Plewes,Donald B, Y1 - 2011/06/07/ PY - 2011/01/19/received PY - 2011/03/31/revised PY - 2011/04/28/accepted PY - 2011/6/10/entrez PY - 2011/6/10/pubmed PY - 2012/7/3/medline SP - 363 EP - 77 JF - Magnetic resonance in medicine JO - Magn Reson Med VL - 67 IS - 2 N2 - Fast imaging applications in magnetic resonance imaging (MRI) frequently involve undersampling of k-space data to achieve the desired temporal resolution. However, high temporal resolution images generated from undersampled data suffer from aliasing artifacts. In radial k-space sampling, this manifests as undesirable streaks that obscure image detail. Compressed sensing reconstruction has been shown to reduce such streak artifacts, based on the assumption of image sparsity. Here, compressed sensing is implemented with three different radial sampling schemes (golden-angle, bit-reversed, and random sampling), which are compared over a range of spatiotemporal resolutions. The sampling methods are implemented in static scenarios where different undersampling patterns could be compared. Results from point spread function studies, simulations, phantom and in vivo experiments show that the choice of radial sampling pattern influences the quality of the final image reconstructed by the compressed sensing algorithm. While evenly undersampled radial trajectories are best for specific temporal resolutions, golden-angle radial sampling results in the least overall error when various temporal resolutions are considered. Reduced temporal fluctuations from aliasing artifacts in golden-angle sampling translates to improved compressed sensing reconstructions overall. SN - 1522-2594 UR - https://www.unboundmedicine.com/medline/citation/21656558/The_influence_of_radial_undersampling_schemes_on_compressed_sensing_reconstruction_in_breast_MRI_ L2 - https://doi.org/10.1002/mrm.23008 DB - PRIME DP - Unbound Medicine ER -