Unbiased noise estimation and denoising in parallel magnetic resonance imaging

@article{Borrelli2014UnbiasedNE,
  title={Unbiased noise estimation and denoising in parallel magnetic resonance imaging},
  author={Pasquale Borrelli and Giuseppe Palma and Marco Comerci and Bruno Alfano},
  journal={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2014},
  pages={1230-1234}
}
In magnetic resonance (MR) clinical practice, noise estimation is usually performed on Rayleigh-distributed background (no signal area) of magnitude images. Although noise variance in quadrature MR images is considered spatially independent, parallel MRI (pMRI) techniques as SENSE or GRAPPA generate spatially varying noise (SVN) distribution. In this scenario noise estimation from background may produce biased results. To address these limitations we introduce a novel noise estimation scheme… CONTINUE READING
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