Improvements to the itk::KernelTransform and Subclasses

Abstract

Kernel-based transforms such as the thin plate spline are frequently used to model deformations in medical imaging. The existing implementation in ITK is capable of being used to warp images, but does not work in the registration framework. The existing implementation is inefficient, requiring recomputation of all cached values at every parameter change, and the Jacobian calculation is not implemented. By reversing the roles of the fixed and moving parameters, the transform can be adapted for registration use. We present modified classes which are more efficient, and calculate the Jacobian correctly.