Rigid template registration in MET images using CUDA

Rigid registration is a basic tool in many applications, especially in Molecular Electron Tomography (MET), and also in, e.g., registration of rigid implants in medical images and as initialization for deformable registration. As MET volumes have a low signal to noise ratio, a complete search of the six-dimensional (6D) parameter space is often employed. In this paper, we describe how rigid registration with normalized cross-correlation can be implemented on the GPU using NVIDIA's parallel computing architecture CUDA. We compare the performance to the Colores software and two Matlab implementations, one of which is using the GPU accelerated JACKET library. With well-aligned padding and using CUDA, the performance increases by an order of a magnitude, making it feasible to work with three-dimensional fitness landscapes, here denoted scoring volumes, that are generated on the fly. This will eventually enable the biologists to interactively register macromolecule chains in MET volumes piece by piece.