Abstract #1023
Noise map estimation in diffusion MRI using Random Matrix Theory
Jelle Veraart 1 , Els Fieremans 1 , and Dmitry S. Novikov 1
1
Center for Biomedical Imaging, NYU Langone
Medical Center, New York, NY, United States
We propose a new technique to estimate the spatially
varying noise map based on diffusion MRI data to enable
Rician bias correction. The technique makes use of a
random matrix theorem, i.e. Marchenko-Pastors law, to
estimate the noise level by exploiting the redundancy in
multi-directional diffusion MR data.
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