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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