Papers by Author: Yong Sheng Wang

Abstract: Extracting axis of 3D blood vessel images is very important and useful to quantify blood vessel in medical diagnosis. According to blood vessel features, we constructed the energy constraint equation of blood vessel. The initial skeleton curve of blood vessel images obtained by thinning algorithm dynastically converges to the position of the axis under energy constraint equation and along gradient direction of the distance field of blood vessel images. When the equation energy reaches a minimum value, the initial skeleton curve also fixes in the axis position at this time. Experimental results show that the position of the blood vessels axis extracted by this method is accurate, and the axis preserves topology and connectivity.

Abstract: This paper proposed the concept of centroid in particle swarm optimization which is similar to physical centroid properties of objects. Similarly, we may think of a particle swarm as a discrete system of particles and find the centroid representing the entire population. Usually, it has a more promising position than worse particles among the population. In order to verify the role of centroid which can speed up the convergence rate of the algorithm, and prevent the algorithm from being trapped into a local solution early as far as possible at the same time, A Novel Centroid Particle Swarm Optimization Algorithm Based on Two Subpopulations(CPSO) is proposed. Numerical simulation experiments show that CPSO by testing some benchmark functions is better than Linear Decreasing Weight PSO (LDWPSO) in convergence speed in the same accuracy of solution case.