Lei Qin1,2, Fenghua Jin2, Yang Tao2, Jeff H. Duyn1
1NINDS, National Institutes of Health, Bethesda, MD, USA; 2Univ of Maryland, College Park, MD, USA
We propose a novel prospective motion correction method for MRI based on positional tracking with a single video camera. A short training scan, using whole-brain EPI during intentional head motion, serves to relate camera images of the human face to head position. With this information, motion during a real-time MRI scan is estimated by correlating each newly captured camera image with the one from the training data. The corresponding motion parameters are fed back to the MRI scan computer to adjust scan parameters. Results show the system is able to correct motion for high-resolution anatomical MRI.