Motion correction is an important issue in FMRI analysis as even the slightest patient motion can induce significant motion artefacts (potentially of greater magnitude than the BOLD effect itself), particularly at tissue boundaries, at the edge of the brain or near major vessels.
A rigid-body motion correction tool was developed based on the affine registration tool in FSL (FLIRT, see below). This method (MCFLIRT) applies the same cost function regularisation techniques as FLIRT but does not need the multi-start optimisation techniques since movement from one volume to another within an FMRI sequence is small, giving good initialisation. Instead, the tool was specifically customised to be highly accurate for typical FMRI data [22].
Motion correction, however, is an inherently non-rigid problem since the volume is not acquired at a single instant, but each slice is acquired at a different time. Consequently, when the head is moving, each slice is transformed by a slightly different rigid-body transformation, making whole-volume-rigid-body-correction oversimplistic. Furthermore, the fact that each slice has slightly shifted timing with respect to each other is incompatible with the assumptions of subsequent temporal analysis. This is often dealt with by applying a slice-timing correction (interpolation within each voxel's time series) either before or after rigid-body motion correction. Applying rigid-body motion correction and slice-timing corrections separately (in either order) is imperfect, as the two problems arise simultaneously and therefore need to be solved in a single integrated approach.
To this end we have developed a limited degree of freedom (DOF) model of the slice transformation process, assuming smooth motion within each TR. (This model is an approximation to the real situation where any sudden small motion could occur during a TR; using a more general model is problematic as it introduces extra degrees of freedom, requiring rigid-body registration of a single slice to a reference volume, which is non-robust and inaccurate.) Cost functions are generalised from the 3D case to include the entire 4D data set since it is unlikely that any single volume can be relied upon to provide a sufficiently accurate (motion-free) reference volume. Initial results using this approach (referred to as FORCE - FMRIB's Optimized Retrospective Correction Environment) indicate that it is possible to reduce final motion-related error in comparison with separated rigid-body correction and slice-timing correction [2].