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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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