This article reviews the requirements for successful compressed sensing (CS), describes
their natural fit to MRI, and gives examples of four interesting applications of CS in MRI. The …

Subject motion during magnetic resonance imaging (MRI) has been problematic since its
introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow …

The sparsity which is implicit in MR images is exploited to significantly undersample k‐
space. Some MR images such as angiograms are already sparse in the pixel …

The thoroughly updated Fourth Edition of this acclaimed reference describes and illustrates
the full range of pediatric disorders diagnosable by modern neuroimaging. This edition …

Dynamic images of natural objects exhibit significant correlations in k‐space and time. Thus,
it is feasible to acquire only a reduced amount of data and recover the missing portion …

In 1988, the first contrast agent specifically designed for magnetic resonance imaging (MRI),
gadopentetate dimeglumine (Magnevist®), became available for clinical use. Since then, a …

Robust principal component analysis (RPCA) via decomposition into low-rank plus sparse
matrices offers a powerful framework for a large variety of applications such as image …

Recent theoretical advances in the field of compressive sampling—also referred to as
compressed sensing (CS)—hold considerable promise for practical applications in MRI, but …

In several applications, MRI is used to monitor the time behavior of the signal in an organ of
interest; eg, signal evolution because of physiological motion, activation, or contrast‐agent …

While nonenhanced magnetic resonance (MR) angiographic methods have been available
since the earliest days of MR imaging, prolonged acquisition times and image artifacts have …