Optimizing Katsevich image reconstruction algorithm on multicore processors

The Katsevich image reconstruction algorithm is the first theoretically exact cone beam image reconstruction algorithm for a helical scanning path in computed tomography (CT). However, it requires much more computation and memory than other CT algorithms. Fortunately, there are many opportunities for coarse-grained parallelism using multiple threads and fine-grained parallelism using SIMD units that can be exploited by emerging multi- core processors. In this paper, we implemented and optimized Katsevich image reconstruction based on the previously proposed pi- interval method and cone beam cover method and parallelized them using OpenMP API and SIMD instructions. We also exploited symmetry in the backprojection stage. Our results show that reconstructing a 1024 times 1024 times 1024 image using 5120 512 times 128 projections on a dual-socket quad-core system took 23,798 seconds on our baseline and 642 seconds on our final version, a more than 37 times speedup. Furthermore, by parallelizing the code with more threads we found that the scalability is eventually hinged by the limited front-side bus bandwidth.