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Abstract #2677

Bias Correction for Respiration Detection in Radial 3D Gradient-Echo Imaging

Robert Grimm1, Kai Tobias Block2, Berthold Kiefer2, Joachim Hornegger1,3

1Pattern Recognition Lab, Department of Computer Science, University of Erlangen-Nuremberg, Erlangen, Germany; 2Siemens Healthcare MR, Erlangen, Germany; 3Erlangen Graduate School in Advanced Optical Technologies (SAOT)

Radial k-space sampling is a promising technique for abdominal imaging due to the high motion robustness and the embedded information on the respiration phase. However, these self-gating signals are often corrupted by high-frequency variations from an angle-dependent bias, caused by inaccurate gradient timings. Here, we present a novel filtering scheme to estimate and correct the bias without compromising temporal resolution. After correction, the variance of the signal can be used to assess the quality of the gating signal for different slices. The approach is evaluated with volunteer data acquired under irregular breathing patterns, and results from gated reconstructions are shown.