An Improved Implementation of Brain Tumor Detection Using Soft Computing

Abstract

Ant Colony Optimization (ACO) metaheuristic is a recent population-based approach inspired by the observation of real ants colony and based upon their collective foraging behavior. In ACO, solutions of the problem are constructed within a stochastic iterative process, by adding solution components to partial solutions. Each individual ant constructs a part of the solution using an artificial pheromone, which reflects its experience accumulated while solving the problem, and heuristic information dependent on the problem. In this paper, the proposed technique ACO hybrid with Fuzzy and Hybrid Self Organizing Hybrid with Fuzzy describe segmentation consists of two steps. In the first step, the MRI brain image is Segmented using HSOM Hybrid with Fuzzy and the second step ACO Hybrid with Fuzzy method to extract the suspicious region Both techniques are compared and performance evaluation is evaluated.