Multimodal medical image registration using Particle Swarm Optimization: A review

Intensity-based registration techniques have been increasingly used in multimodal image co-registration, which is a fundamental task in medical imaging, because it enables to integrate different images into a single representation such that complementary information can be easily accessed and fused. These schemes usually require the optimization of some similarity metric (e.g., Mutual Information) calculated on the input images. Local optimization methods often do not obtain good results, possibly leading to premature convergence to local optima, especially with non-smooth fitness functions. In these cases, we can adopt global optimization methods, and Swarm Intelligence techniques represent a very effective and efficient solution. This paper focuses on biomedical image registration using Particle Swarm Optimization (PSO). Several literature approaches are critically reviewed, by investigating modifications and hybridizations with Evolutionary Strategies. Since biomedical image registration represents a challenging clinical task, the experimental findings encourage further research studies in the near future.