A registration and interpolation procedure for subvoxel matching of serially acquired MR images.

OBJECTIVE

Methods for automatically registering and reslicing MR images using an interpolation function that matches the structure of the image data are described.

MATERIALS AND METHODS

Phantom and human brain images were matched by rigid body rotations and translations in two and three dimensions using a least-squares optimization procedure. Subvoxel image shifts were produced with linear or sinc interpolation.

RESULTS

The use of sinc interpolation ensured that the repositioned images were faithful to the original data and enabled quantitative intensity comparisons to be made. In humans, image segmentation was vital to avoid extraneous soft tissue changes producing systematic errors in registration.

CONCLUSIONS

The sinc-based interpolation technique enabled serially acquired MR images to be positionally matched to subvoxel accuracy so that small changes in the brain could be distinguished from effects due to misregistration.