Compressed sensing for body MRI

@article{Feng2017CompressedSF,
  title={Compressed sensing for body MRI},
  author={Li Feng and Thomas Benkert and Kai Tobias Block and Daniel K. Sodickson and Ricardo Otazo and Hersh Chandarana},
  journal={Journal of Magnetic Resonance Imaging},
  year={2017},
  volume={45}
}
The introduction of compressed sensing for increasing imaging speed in magnetic resonance imaging (MRI) has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing… 
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