Corpus ID: 215754465

End-to-End Variational Networks for Accelerated MRI Reconstruction

@article{Sriram2020EndtoEndVN,
  title={End-to-End Variational Networks for Accelerated MRI Reconstruction},
  author={Anuroop Sriram and Jure Zbontar and Tullie Murrell and Aaron Defazio and C. Lawrence Zitnick and Nafissa Yakubova and Florian Knoll and Patricia Ann Johnson},
  journal={ArXiv},
  year={2020},
  volume={abs/2004.06688}
}
  • Anuroop Sriram, Jure Zbontar, +5 authors Patricia Ann Johnson
  • Published 2020
  • Computer Science, Engineering
  • ArXiv
  • The slow acquisition speed of magnetic resonance imaging (MRI) has led to the development of two complementary methods: acquiring multiple views of the anatomy simultaneously (parallel imaging) and acquiring fewer samples than necessary for traditional signal processing methods (compressed sensing). While the combination of these methods has the potential to allow much faster scan times, reconstruction from such undersampled multi-coil data has remained an open problem. In this paper, we… CONTINUE READING

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