Accelerating Mutual-Information-Based Registration on multi-core systems

Mutual-Information-Based Registration (MIBR) is an image registration method that maps points from one image to another. It has been widely used in medical image processing applications. However, MIBR is a very compute-intensive task, and fast processing speed is often required in medical diagnosis. Nowadays, with the multi-core processor becoming the mainstream, MIBR can be accelerated by fully utilizing the computing power of available multi-core processors. In this paper, we propose a parallel MIBR algorithm and present some optimization techniques to improve the implementation's performance. The result shows our optimized implementation can register a pair of 512 × 512 × 30 3D images in one second on an 8-core system, which meets the real-time processing requirement. We also conduct a detailed scalability and memory performance analysis on the multi-core system. The analysis helps us to identify the causes of bottlenecks, and make suggestion for future improvement on large-scale multi-core systems.