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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