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Abstract #0584

Projection-based 2D/3D registration of collapsed FatNav data for prospective motion correction

Enrico Avventi 1 , Mathias Engstrm 1,2 , Ola Norbeck 1 , Magnus Mrtensson 2,3 , and Stefan Skare 1,2

1 Dept. of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden, 2 Dept. of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden, 3 EMEA Research & Collaboration, GE Science Laboratory, GE Healthcare, Stockholm, Sweden

In previous works we developed a novel and promising navigator technique aimed for prospective motion correction: cFatNav (collapsed FatNav). A cFatNav sub-sequence consists of three EPI readouts sampling orthogonal planes in k-space placed between a non space-selective, fat saturation pulse and the host sequence excitation. From each sampled k-space plane, via IFFT, we can obtain a view of the excited volume projected along three orthogonal direction. We have shown that 2D registration applied to cFatNav data produces precise motion estimates when the motion occur mostly along one of the three sampled planes. In this work we present a 2D/3D registration algorithm for cFatNav data that can handle out-of-plane motion. Specifically each of the three collapsed views are matched against a reference 3D volume simultaneously by Gauss-Newton method.

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