Classification of Brain Tumor Using Firefly Optimisation Algorithm

Abstract

Tumor present in the human body is regarded as an undesired mass that grows unconditionally in brain. Manual classification of brain tumor is regarded as a time consuming process that is carried out in diagnostic centers. Classification of brain tumors using image processing schemas on other hand is a crucial task since the classification is entirely based on the size and location. In order to improve the task of classification, it is essential in developing a meta-learning heuristics that enables optimal classification of instances. In this paper, a meta-heuristic model using Firefly optimization algorithm is developed to classify the brain tumor regions. The simulation is conducted to validate the proposed method with existing methods in terms of various performance metrics. The results of simulation validates that the firefly algorithm obtains improved classification rate than other methods.