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Abstract #3568

A New Quality Measure for Gradient Encoding Schemes

Sarah C. Mang1,2, Daniel Gembris2,3, Wolfgang Grodd1, Uwe Klose1

1Section Exp. MRI of CNS, Diagnostic and Interventional Neuroradiology, Tbingen, Germany; 2Institute for Computational Medicine, University of Mannheim, Mannheim, Germany; 3Bruker Biospin MRI GmbH, Ettlingen, Germany


We present a new method for the evaluation of gradient encoding scheme quality. The signal deviation compares the input signal derived from a chosen tensor with the signal synthesized from a tensor fitted to this input signal. An encoding scheme of high quality has a low signal deviation. This encoding scheme quality measure is applicable to different kinds of diffusion representation. Here we did focus on higher order diffusion tensor models. We could show that a pair wise force minimizing direction set gives the best quality for all evaluated tensor models.