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Abstract #1867

Sub-volume motion detection to speed up image-based navigators and prospective motion correction

Anja Jäger1,2, Thomas Beck2, and Andreas Maier1

1Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander- Universität Erlangen-Nürnberg, Erlangen, Germany, 2Siemens Healthcare, MR Application Development, Erlangen, Germany

A method for detection of patient motion based on sub-volumes is presented. Current methods for image-based motion detection are limited because rigid motion parameters can only be detected for full volumes. This limits the potential of navigator acceleration and causes undesirable effects due to respiratory motion in some applications. Our novel approach extends the rigid-body-motion model by detection based on a subset of slices relative to a fully sampled reference volume. It is validated with phantom and in-vivo data and allows for both considerable acceleration of navigator scans and prospective correction of head motion in fMRI applications.

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