Identifying various type of Pathologies in Magnetic Resonance (MR) Image using Jaya algorithm

Abstract

Tumor diagnosis play a significant role in the medical field. The task of identifying the tumor leads to more critical because of more complexity in the structure and size of the cancer cell. The recommended Jaya algorithm can be used for clustering and produced improved result in segmenting the tumor region. Jaya algorithm produces optimal solution for constrained problem by identifying the best and worst solution for all subset. If the solution provided is better than the previous one then the new one is updated otherwise it will take the previous one for consideration. These techniques delivered a prominent result for tumor having different boundaries and complex structures. The results obtained from jaya algorithm are compared with conventional algorithm like particle swarm optimization (PSO) clearly shows quite improved that can be used to identify various pathologies in magnetic resonance (MR) image.