P-LORAKS: Low-rank modeling of local k-space neighborhoods with parallel imaging data.

@article{Haldar2016PLORAKSLM,
  title={P-LORAKS: Low-rank modeling of local k-space neighborhoods with parallel imaging data.},
  author={Justin P. Haldar and Jingwei Zhuo},
  journal={Magnetic resonance in medicine},
  year={2016},
  volume={75 4},
  pages={1499-514}
}
PURPOSE To propose and evaluate P-LORAKS a new calibrationless parallel imaging reconstruction framework. THEORY AND METHODS LORAKS is a flexible and powerful framework that was recently proposed for constrained MRI reconstruction. LORAKS was based on the observation that certain matrices constructed from fully sampled k-space data should have low rank whenever the image has limited support or smooth phase, and made it possible to accurately reconstruct images from undersampled or noisy data… CONTINUE READING
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