fastTemplateMatching: Fast Template Matching via Cross-Correlation
In dcemriS4: A Package for Image Analysis of DCE-MRI (S4 Implementation)

Description Usage Arguments Details Value Author(s) References See Also

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.

fastTemplateMatching(input, ...)

## S4 method for signature 'array'
fastTemplateMatching(input, ...)

`input`	is a four-dimensional array of signal intensities.
`...`	Additional variables passed to the `plot` function.

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 (fft) and 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:

`out`	Motion-corrected version of the four-dimensional array.
`offset`	Translations (in 3D) for each volume in the 4D array.
`t.center`	Estimated center of the binary mask.