Rethinking MRI random signals modeling

Jean Marie Vianney Kinani, Alberto J. Rosales-Silva, Francisco J. Gallegos-Funes, Alfonso Arellano

Research output: Contribution to conferencePaper

Abstract

Based on both the Physics of MRI and the central limit theorem, it is common practice to assume that the noise in MR images is Gauss distributed, but from an MR signal post-acquisition standpoint, this modeling approach can be proved to be erroneous, especially when the SNR is low. In this article, we present a thorough analysis that shows why the Gaussian model was adopted, and through the MR complex raw data post-acquisition mathematical treatment, the Rician model will be developed and proved to be the right MR random signals model. © 2013 IEEE.
Original languageAmerican English
Pages116-121
Number of pages103
DOIs
StatePublished - 1 Jan 2013
Event2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2013 -
Duration: 1 Jan 2013 → …

Conference

Conference2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2013
Period1/01/13 → …

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  • Cite this

    Kinani, J. M. V., Rosales-Silva, A. J., Gallegos-Funes, F. J., & Arellano, A. (2013). Rethinking MRI random signals modeling. 116-121. Paper presented at 2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2013, . https://doi.org/10.1109/ICEEE.2013.6676085