DocumentCode :
3181068
Title :
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
Link To Document :
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