Abstract
Functional magnetic resonance imaging in real time is an emerging tool for the assessment of dynamic changes in brain activation. The short response latency (tens of seconds) renders the technique more sensitive to motion artifacts. Motion correction in real time requires computationally efficient algorithms which can be executed on a complete 3D data set within a single time of repetition cycle. In this study, a method to evaluate motion and realign functional images in real time implemented on standard imaging hardware is introduced. The detection of activity in correlation maps is improved, and artifactual edge enhancements are reduced. As the estimation of large movements is stable, this algorithm is attractive for clinical studies with uncooperative patients. Magn Reson Med 45:167-171, 2001.
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