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# NORDIC_Raw | ||
Matlab code for performing image reconstruction in MRI and performing the NORDIC denoising | ||
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The two files NORDIC and NIFTI_NORDIC perform similar concepts, locally low-rank denoising. | ||
Both approaches, uses a g-factor map to flatten the noise, and a noise-scan for estimating the homoegenous noise. | ||
For NORDIC, the noise-scan and the g-factor are explicit constructions provided as the last elements in a 4D array. | ||
For NIFTI_NORDIC, these are estimated based on the data. The construction for estimating the g-factor noise and the thermal noise level | ||
uses the MPPCA method of Veraart et al. 2016 | ||
NIFTI_NORDIC has additional paramters that can be adjusted, for learning or understanding the influence of the different algortimic choices. | ||
For NIFTI_NORDIC, there are two different options, depending on whether dMRI or fMRI is used. | ||
This difference appears related to the hwo the phase is retained in the DICOM of the vendor software. A corresponding distinction is not neccesary for the NORDIC processing. | ||
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This version of NIFTI_NORDIC has been made possible through the testing and evaulation of many people, including | ||
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Logan Dowdle | ||
Luca Vizioli | ||
Cheryl Olman | ||
Essa Yacoub | ||
Henry Braun | ||
Remi Patriat | ||
Federico De Martino | ||
Lonike Faes | ||
Torben Ellegaard Lund | ||
Lasse Knudsen | ||
Stamatios Sotiropoulos | ||
Karen Mullinger | ||
Daniel Marsh | ||
Susan Francis | ||
Jose Manzano Patron | ||
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Any questions, ciomments or suggestions can be directed to | ||
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Steen Moeller | ||
moell018@umn.edu |