Abstract:
A computer algorithm for the three-dimensional (3D) alignment of
PET images is described. To align two images, the algorithm calculates
the ratio of one image to the other on a voxel-by-voxel basis and then
iteratively moves the images relative to one another to minimize the
variance of this ratio across voxels. Since the method relies on
anatomic information in the images rather than on external fiducial
markers, it can be applied retrospectively. Validation studies using a
3D brain phantom show that the algorithm aligns images acquired at a
wide variety of positions with maximum positional errors that are
usually less than the width of a voxel (1.745 mm). Simulated cortical
activation sites do not interfere with alignment. Global errors in
quantitation from realignment are less than 2%. Regional errors due to
partial volume effects are largest when the gantry is rotated by large
angles or when the bed is translated axially by one-half the interplane
distance. To minimize such partial volume effects, the algorithm can be
used prospectively, during acquisition, to reposition the scanner gantry
and bed to match an earlier study. Computation requires 3-6 min on a Sun
SPARCstation 2