MRI segmentation using Entropy maximization and Hybrid Particle Swarm Optimization with Wavelet Mutation

Author

De, Arunava ; Bhattacharjee, Anup Kumar ; Chanda, Chandan Kumar ; Maji, Bansibadan

Author_Institution

Dept. of Electron. & Commun., Nat. Inst. of Technol., Durgapur, India

fYear

2011

fDate

11-14 Dec. 2011

Firstpage

362

Lastpage

367

Abstract

A Hybrid Particle Swarm Optimization algorithm that incorporates a Wavelet theory based mutation operation is used for segmentation of Magnetic Resonance Images. We use Entropy maximization using Hybrid Particle Swarm algorithm with Wavelet based mutation operation to get the region of interest of the Magnetic Resonance Image. It applies the Multi-resolution Wavelet theory to enhance the Particle Swarm Optimization Algorithm in exploring the solution space more effectively for a better solution. Tests on various MRI images with lesions show that lesions are successfully extracted.

Keywords

biomedical MRI; entropy; image segmentation; medical image processing; particle swarm optimisation; wavelet transforms; MRI segmentation; entropy maximization; hybrid particle swarm optimization algorithm; lesions; magnetic resonance image segmentation; multiresolution wavelet theory based mutation operation; Entropy; Equations; Image segmentation; Lesions; Magnetic resonance imaging; Particle swarm optimization; Wavelet transforms; Entropy; Hybrid Particle Swarm Optimization; Magnetic Resonance Imaging; Multi-resolution Wavelet Analysis; Particle Swarm Optimization; Region of Interest; Wavelet Mutation;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technologies (WICT), 2011 World Congress on

Conference_Location

Mumbai

Print_ISBN

978-1-4673-0127-5

Type

conf

DOI

10.1109/WICT.2011.6141273

Filename

6141273