Sparse reconstruction of compressive sensing MRI using cross-domain stochastically fully connected conditional random fields

@article{Li2016SparseRO,
  title={Sparse reconstruction of compressive sensing MRI using cross-domain stochastically fully connected conditional random fields},
  author={Edward Li and Farzad Khalvati and Mohammad Javad Shafiee and Masoom A. Haider and Alexander Wong},
  journal={BMC Medical Imaging},
  year={2016},
  volume={16}
}
  • E. Li, F. Khalvati, +2 authors A. Wong
  • Published 25 December 2015
  • Computer Science, Medicine, Physics, Mathematics
  • BMC Medical Imaging
BackgroundMagnetic Resonance Imaging (MRI) is a crucial medical imaging technology for the screening and diagnosis of frequently occurring cancers. However, image quality may suffer from long acquisition times for MRIs due to patient motion, which also leads to patient discomfort. Reducing MRI acquisition times can reduce patient discomfort leading to reduced motion artifacts from the acquisition process. Compressive sensing strategies applied to MRI have been demonstrated to be effective in… Expand
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