GPU implementation of a deformable 3D image registration algorithm.

We present a parallel implementation of a new deformable image registration algorithm using the Computer Unified Device Architecture (CUDA). The algorithm co-registers preoperative and intraoperative 3-dimensional magnetic resonance (MR) images of a deforming organ. It employs a linear elastic dynamic finite-element model of the deformation and distance measures such as mutual information and sum of squared differences to align volumetric image data sets. Computationally intensive elements of the method such as interpolation, displacement and force calculation are significantly accelerated using a Graphics Processing Unit (GPU). The result of experiments carried out with a realistic breast phantom tissue shows a 37 fold speedup for the GPU-based implementation compared with an optimized CPU-based implementation in high resolution MR image registration. The GPU implementation is capable of registering 512 × 512 × 136 image sets in just over 2 seconds, making it suitable for clinical applications requiring fast and accurate processing of medical images.