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Abstract #0082

Influence of the gradient delay correction on self-navigated motion resolved reconstruction with golden angle stack-of-stars acquisition

Xucheng Zhu1, Mariya Doneva2, Peder E.Z. Larson1,3, and Michael Lustig1,4

1Bioengineering, UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, CA, United States, 2Philips Research Europe, Hamburg, Germany, 3Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, 4Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, CA, United States

Gradient delay often leads to misalignment of k-space data, which induces artifacts on reconstructed images. As many self-gated motion correction methods largely depend on central k-space data, misalignment might affect motion state estimation and reconstruction. In order to acquire robust motion states and improve motion resolved reconstruction, we propose a workflow incorporating gradient delay correction, robust motion extraction, and motion resolved reconstruction. We tested our method on in vivo volunteer data, and demonstrate the improvement over a reconstruction that does not account for these delays.

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