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Abstract #1632

Automatic and Spatially Varying Phase Correction for Diffusion Weighted Images

Marco Pizzolato1 and Rachid Deriche2

1EPFL, Lausanne, Switzerland, 2Athena, Inria, Sophia Antipolis, France

Phase Correction is a post-processing procedure exploiting the phase of magnetic resonance images in order to obtain real-valued images containing tissue contrast with additive Gaussian noise, as opposed to magnitude images which are typically affected by a bias due to the Rician distribution of noise. This bias is particularly relevant in Diffusion Weighted Images where the signal-to-noise ratio is intrinsically low. We propose a method for automatically assessing the optimal amount of required correction based on properties of the noise affecting the images: its variance and positional non-stationarity. We present results for diffusion metrics such as FA, AD, and MD.

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