An Improved Soft Subspace Clustering Algorithm Based on Particle Swarm Optimization for MR Image Segmentation

In conclusion, the extended noise clustering method is implemented in order to maximize the weight. Additionally, the constraint condition of the weight is changed from the equality constraint to the boundary constraint in order to reduce the impact of noise. The methodology presented in this research works to reduce the amount of sensitivity the SSC algorithm has to noisy data. It is possible to demonstrate the efficacy of this algorithm by using photos with noise already present or by introducing noise to existing photographs. The revised SSC approach based on particle swarm optimization (PSO) is demonstrated to have superior segmentation accuracy through a number of trials; as a result, this work gives a novel method for the segmentation of noisy images.Graphical Abstract

Source: Interdisciplinary Sciences, Computational Life Sciences - May 10, 2023 Category: Bioinformatics Source Type: research