Abstract #3470

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

Ayan Sengupta^1,2, 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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