Get the metric value. The metric value is the mean square difference * in intensity between the fixed image and transforming moving image * comp

* Get the segmentation image. */

* Infer dimensionality from the first input transform. */

* Set the adaptive smoothing weight clamped between 0 and 1 which weights * between using just the intensity image (weight = 0) and using only the

Define the output displacement field domain from a const image */

* Set the standard deviation of the displacement noise. Default = 1 (mm). */

* Set the low resolution input image to be refined. */

* Set the prior label parameters. For each class/label for label propagation * the boundary probabilty value is set and the exponential decay para

Set the warping field */

This function computes the topological number associated with NBH and a certain connectivity. This function is a "hack": a more elegant/efficient impl

* */