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Abstract #4710

Motion Correction for Perfusion Weighted Images in Stroke: Approach and Impact on Quantification

Rakesh Mullick1, Dattesh Shanbhag1, Uday Patil1, Xiaodong Tao2

1Imaging Technologies Lab, GE Research, Bangalore, Karnataka, India; 2Imaging Technologies Lab, GE Research, Niskayuna, NY, USA

Head motion while imaging stroke, neoplasic and neuro-degenerative disease is often observed during routine clinical imaging. Even with head stabilization, involuntary head movement can cause image artifacts leading to incorrect diagnosis. These artifacts have acute effects in select (extended duration) image sequences targeted to acquire spatio-temporal data like perfusion-weighted imaging and functional imaging scans. It is therefore imperative to address motion artifacts either early in the imaging chain or through a post-processing step. In cases of acute stroke, where time to image is of utmost importance, the extended duration of scan due to use of navigators precludes their use and places more importance on retrospective motion correction through image segmentation/registration techniques. In this work we present an approach based on image registration to align the spatio-temporal data, evaluate the impact on quantification of stroke related perfusion maps. The underlying challenge to correct and evaluate motion artifacts is further discussed.