Abstract
An algorithm for the automatic alignment of MRI volumes of the human brain was developed, based on techniques adopted from the computer vision literature for image motion estimation. Most image registration techniques rely on the assumption that corresponding voxels in the two volumes have equal intensity, which is not true for MRI volumes acquired with different coils and/or pulse sequences. Intensity normalization and contrast equalization were used to minimize the differences between the intensities of the two volumes. However, these preprocessing steps do not correct perfectly for the image differences when using different coils and/or pulse sequences. Hence, the alignment algorithm relies on robust estimation, which automatically ignores voxels where the intensities are sufficiently different in the two volumes. A multiresolution pyramid implementation enables the algorithm to estimate large displacements. The resulting algorithm is used routinely to align MRI volumes acquired using different protocols (3D SPGR and 2D fast spin echo) and different coils (surface and head) to subvoxel accuracy (better than 1 mm).
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