Acceleration of blob-based iterative reconstruction algorithm using Tesla GPU

Blob-based iterative image reconstruction techniques provide high-quality denoised images in the photon starving emission tomography. However, the attractiveness of blob-based iterative algorithms is devalued by their high demands on the computation time. In this study we investigate the use of graphic processing units (GPU) to parallelize the ray-driven blob-based OSEM reconstruction algorithm for SPECT. We obtained a speed-up factor of 14.7 as compared to the blob reconstruction performed using CPU. Therefore, the reconstruction time of blob-based image on GPU was comparable to the reconstruction time of voxel-based image on the CPU. The algorithm can be further accelerated by more effective utilization of the GPU register space and shared GPU memory, which we plan to implement in the future.