2D and 3D nonrigid body registration in fMRI

It is well known that even small movements of the head can lead to artifacts in fMRI. Corrections for these movements are usually made by a registration algorithm which accounts for translational and rotational motion of the head under a rigid body assumption. The brain, however, is not entirely rigid and images are prone to local deformations due to CSF motion, susceptibility effects, local changes in blood flow and inhomogeneities in the magnetic and gradient fields. Since nonrigid body motion is not adequately corrected by approaches relying on simple rotational and translational corrections, we have investigated a general approach where an n^th order polynomial is used to map all images onto a common reference image. The coefficients of the polynomial transformation were determined through minimization of the ratio of the variance to the mean of each pixel. Simulation studies were conducted to validate the technique. Results of experimental studies using polynomial transformation for 2D and 3D registration show lower variance to mean ratio compared to simple rotational and translational corrections