AbstractsComputer Science

Automatic detection of brain tumor tissue from magneticresonance image using meta heuristic algorithms;

by K Selvanayaki

Institution: Anna University
Year: 2015
Keywords: Artificial bee colony optimization; Brain tumor tissue; Magnetic resonance image; Markov random field; Meta heuristic algorithms; Receiver operating characteristics; Science and humanities
Posted: 02/05/2017
Record ID: 2088808
Full text PDF: http://shodhganga.inflibnet.ac.in/handle/10603/49414


MRI based Textural image segmentation and classification is the most effective one in the Brain tumor detection The brain is a reliable place for patterns to enter and sustain among each other It is the origin of all human behavior thoughts feelings and experience It also integrates and controls allosteric balance and autonomic functions in the body The brain is built up of soft tissues and it is affected by tumor tissues A brain tumor is an unusual group of tissue in which some cells uncontrollably grow and in multiples newlinepossibly unregulated by the systems that control normal cells MRI is one of the best technologies currently being used for diagnosing brain Tumor Brain Tumor is diagnosed at advanced stages with the help of the MRI image In this thesis an intelligent system is designed to diagnose brain tumor through MRI using image processing techniques with newlineintelligent optimization tools such as Fuzzy C Means Modified Particle Swarm Optimization Modified Particle Swarm Optimization with Fuzzy C Means Genetic algorithm Ant Colony Optimization Bacteria Foraging algorithm Artificial Bee Colony Optimization ABC and Artificial Neural Network with ABC The detection brain tumor is performed in two phases preprocessing and segmentation in the first phase and feature extraction selection and classification in the second phase newline Advisors/Committee Members: Kalugasalam P.