NORDIC

NOise Reduction with DIstribution Corrected PCA (NORDIC) is a denoising technique that selectively suppresses the thermal noise contribution. NORDIC uses low-rank modeling of g-factor-corrected complex dMRI reconstruction and non-asymptotic random matrix distributions to remove signal components which cannot be distinguished from thermal noise. 

Citation

If you publish or present results obtained using the software or sequences in this package, please acknowledge the researchers who developed the sequences using the following language:

Vizioli L, et al. Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging. Nat Commun. 2021; 12:5181. doi: 10.1038/s41467-021-25431-8

Moeller S, et al. NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing. Neuroimage. 2021; 226:117539. doi: 10.1016/j.neuroimage.2020.117539

Contact

If you have noticed a bug or have a request for a new feature in a future release, please contact

Steen Moeller

Download

You can access the source code at the NORDIC git repository


References

  1. Vizioli L, et al. Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging. Nat Commun. 2021; 12:5181. doi: 10.1038/s41467-021-25431-8

  2. Moeller S, et al. NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing. Neuroimage. 2021; 226:117539. doi: 10.1016/j.neuroimage.2020.117539

Return to top
Staff Login