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Abstract #3470

Online reconstruction of GRE Fat Navigators with Gadgetron on Siemens Terra 7T Scanner

Ayan Sengupta1,2, Iulius Dragonu3, and Christopher T. Rodgers2
1Department of Psychology, Royal Holloway, University of London, London, United Kingdom, 2Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom, 3Siemens Healhineers, London, United Kingdom

High resolution Ultra High Field 7T imaging is highly prone towards involuntary motion artifacts. Fat Navigator based motion correction provides a robust solution but it is a retrospective correction method. In this study we present an online reconstruction method 3D GRE FatNavs with open-source reconstruction tool, Gadgetron. We improved the performance of the GRAPPA reconstruction pipeline in Gadgetron for fast online reconstruct FatNav. We also implemented a Python Gadget to perform fsl Flirt based co-registration through NiPype to produce motion parameters from the FatNav.

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