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Abstract #4862

Fast Method for Parametric System Identification of Gradient Systems

Yu-Chun Chang 1,2 , Martin Eschelbach 1 , Nikolai Avdievitch 1 , Klaus Scheffler 1 , and Anke Henning 1,3

1 Max Planck Institute of Biological Cybernetics, Tuebingen, Baden-Wuerttemburg, Germany, 2 Graduate School of Neural & Behavioural Sciences, University of Tuebingen, Tuebingen, Baden-Wuerttemburg, Germany, 3 Institute for Biomedical Engineering, University and ETH Zurich, Switzerland

A method for characterising a gradient system is introduced. This is a parametric method and thus the system has an analytic form. It is fast and requires only one measurement in each gradient direction and can thus be completed in minutes. It can also be extended to characterise the shim system. Monitoring the B0 field is done using a 16 channel field camera. The predicted model is compared to measured data.

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