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Abstract #3910

A U-Net based Approach to the Prediction of Regions-of-Interest for Metabolic Sodium Imaging

Wieland A. Worthoff1, Yannic Sommer1, Zaheer Abbas1, and N. Jon Shah1,2,3,4
1Institut of Neuroscience and Medicine - 4, Forschungszentrum Jülich GmbH, Jülich, Germany, 2Institut of Neuroscience and Medicine - 11, Forschungszentrum Jülich GmbH, Jülich, Germany, 3Department of Neurology, RWTH Aachen University, Aachen, Germany, 4JARA-BRAIN - Translational Medicine, Jülich-Aachen Research Alliance, Aachen, Germany


Sodium MRI yields metabolic information about the brain and might indicate existing or emerging pathologies. Often this information is to be determined in a certain region-of-interest (ROI). These ROIs can be, for example, all grey or white matter regions, or more specific sub-regions thereof and it is important to predict these ROIs without bias. Here, an approach to obtain well segmented ROIs is presented based on a deep neural network architecture.

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