A cooperating metaheuristic approach for MR image segmentation

This paper presents cooperating Cuckoo Search (CS) and Particle Swarm Optimization (PSO) algorithms for MR image segmentation. The problem can be formulated as an optimization problem and the proposed algorithm has been applied to find the best solution. Since image segmentation requires satisfying several criteria, it is important to know how to optimize them in parallel in the same algorithm. This paper is actually a further step of our works, which applies a new mechanism of using metaheuristic algorithms for optimizing a Markov Random Field (MRF) segmentation criterion. The proposed method is validated on both simulated and real MR images. The results indicate that our method can provide better solutions in terms of segmentation quality and efficiency.