Accelerating the Image Registration of MRI Volumes by Modern GPGPU Parallel Computation

Shiun-Ying Ju¹, Yu-Wei Tang¹, Teng-Yi Huang¹

Image registration has been an important topic in the MRI applications, such as longitudinal follow-up studies, brain-normalization for group statistics and motion correction for fMRI studies. However, the automatic registration requires a lot of iteration loops and a huge amount computation for linear transformations and thus it is generally very time-consuming task. In our study, we proposed to use the parallel computing on recently advanced general-purpose computation on graphic processing units (GPGPU) to accelerate the registration calculations, especially for the popular SPM system. We got about 23-fold acceleration of the computation process on our datasets.