Retrospective Coregistration of Functional Magnetic Resonance Imaging Data Using External Monitoring

Coregistration is essential for correcting head motion artifacts in functional magnetic resonance imaging (fMRI). Coregistration algorithms typically realign images through optimization of a similarity measure based on voxel signal intensities. However, coregistration can also be performed through external monitoring, whereby a tracking device measures head motion directly and independently of the imaging data. This paper describes development of external monitoring using fMRI-compatible infrared cameras. Three subjects participated in block-design fMRI experiments consisting of bilateral finger tapping alone and tapping combined with visuomotor tracking to produce controlled task-correlated head motion. Functional MRI time-series were coregistered using the external monitoring technique and a known image-based algorithm for comparison. Over various performance characteristics, external monitoring and image-based coregistration exhibited good agreement, in particular reducing signals correlated with millimeter task-correlated motions by 50-100%, with a 5% difference between the two techniques. These results promise future applications and refinements of external monitoring in patient populations where head motion is especially problematic. Possibilities include 3D prospective coregistration during real-time fMRI, coregistration of individual slices, and motion correction in anatomic MRI.