Samer El-Khatib, Yuri Skobtsov, Sergey Rodzin, and Semyon Potryasaev. Theoretical and Experimental Evaluation of PSO-K-Means Algorithm for MRI Images Segmentation Using Drift Theorem // Artificial Intelligence Methods in Intelligent Algorithms. Proceedings of 8th Computer Science On-line Conference 2019, Vol. 2. P.316-323. https://doi.org/10.1007/978-3-030-19810-7_31
Theoretical and Experimental Evaluation of PSO-K-Means Algorithm for MRI Images Segmentation Using Drift Theorem
Image segmentation is the process of subdividing an image into regions that are consistent and homogeneous in some characteristics. An important factor in the recognition of magnetic resonance images is not only the accuracy, but also the speed of the segmentation procedure. Modified Exponential Particle Swarm Optimization algorithm is proposed in paper. The time complexity of proposed algorithm is investigated using consequences from Drift theorem. It is established that the proposed algorithm has a polynomial estimation of complexity. Images from the Ossirix image dataset and real medical images were used for testing.