2011
DOI: 10.1002/mrm.23008
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The influence of radial undersampling schemes on compressed sensing reconstruction in breast MRI

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 implemen… Show more

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Cited by 88 publications
(96 citation statements)
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“…45 While it is true that these sampling strategies can provide evenly spaced projections in k-space, they have certain limitations. Both the BR and GA techniques are defined for sampling k-space in two dimensions and the extension to 3D is nontrivial.…”
Section: -7mentioning
confidence: 99%
“…45 While it is true that these sampling strategies can provide evenly spaced projections in k-space, they have certain limitations. Both the BR and GA techniques are defined for sampling k-space in two dimensions and the extension to 3D is nontrivial.…”
Section: -7mentioning
confidence: 99%
“…Compressed sensing (CS) is a recently emerging technique that may significantly accelerate data acquisition [15][16][17][18][19]. It allows images, which are intrinsically sparse in some domains, to be faithfully recovered from insufficient sampling data sets by using a nonlinear reconstruction method [20].…”
Section: Introductionmentioning
confidence: 99%
“…The images are then reconstructed retrospectively from this data set. This occurs with a freely-selectable temporal resolution while a different number of acquired k-space spokes within one time frame are summarized [36,37]. This concept could lead to a significant simplification of the clinical workflow.…”
mentioning
confidence: 99%