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Abstract #4549

Spatially Variable Rician Noise in DTI

Ivan I. Maximov1, Ezequiel A. Farrher1, Farida Grinberg1, Nadim Jon Shah1,2

1Institute of Neuroscience & Medicine 4, Forschungszentrum Juelich, Juelich, Germany; 2Department of Neurology, Faculty of Medicine, JARA, RWTH Aachen University, Aachen, Germany

We propose a new algorithm for noise correction in DTI experiments based on the hypothesis of spatially-variable noise fields. Application of the robust estimator followed by Rician correction of the initially assumed Gaussian standard deviation allows us to produce a more stable and precise scheme for the noise evaluation at arbitrary signal-to-noise ratio levels.