Fast Template Matching via Cross-Correlation
Motion correction and/or co-registration of three-dimensional arrays (medical imaging data) are performed by applying a user-defined mask of voxels. Normalized cross-correlations (in 3D) are computed using the FFT.
is a four-dimensional array of signal intensities.
Additional variables passed to the
An extremely basic method of motion correction/co-registration is
implemented by estimating “local” cross-correlations based on a
binary mask that is a subset of the original three-dimensional volume.
All convolutions are preformed via the FFT (
repetitive calculations are minimized where possible.
Only whole-voxel translations are considered. This does not begin to capture the true effects of motion in soft tissue, but we assume that the object of interest (e.g., tumor) is a fairly rigid structure. Potential extensions include rigid-body, affine and nonlinear registration techniques along with interploation schemes in order to capture intra-voxel manipulations of the data.
A list of objects are returned:
Motion-corrected version of the four-dimensional array.
Translations (in 3D) for each volume in the 4D array.
Estimated center of the binary mask.
Brandon Whitcher <email@example.com>
Lewis, J.P. (2003) Fast normalized cross-correlation.