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Integration of Entropy Maximization and Quantum Behaved Particle Swarm Algorithm for Unsupervised Change Detection of MR Skull Bone Lesions

by Ankita Mitra, Arunava De, Anup Kumar Bhattacharjee
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 13
Year of Publication: 2015
Authors: Ankita Mitra, Arunava De, Anup Kumar Bhattacharjee
10.5120/20617-3321

Ankita Mitra, Arunava De, Anup Kumar Bhattacharjee . Integration of Entropy Maximization and Quantum Behaved Particle Swarm Algorithm for Unsupervised Change Detection of MR Skull Bone Lesions. International Journal of Computer Applications. 117, 13 ( May 2015), 33-39. DOI=10.5120/20617-3321

@article{ 10.5120/20617-3321,
author = { Ankita Mitra, Arunava De, Anup Kumar Bhattacharjee },
title = { Integration of Entropy Maximization and Quantum Behaved Particle Swarm Algorithm for Unsupervised Change Detection of MR Skull Bone Lesions },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 13 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 33-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number13/20617-3321/ },
doi = { 10.5120/20617-3321 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:59:20.235582+05:30
%A Ankita Mitra
%A Arunava De
%A Anup Kumar Bhattacharjee
%T Integration of Entropy Maximization and Quantum Behaved Particle Swarm Algorithm for Unsupervised Change Detection of MR Skull Bone Lesions
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 13
%P 33-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Entropy is the measure of randomness in a system whereas the entropy maximization procedure leads to the most probable state of a system behaviour. Entropy maximization using an optimization algorithm is used to find the threshold of the MR image of the brain. Standard Particle Swarm algorithm sufferes from stagnation. An automatic regrouping mechanism is used to deal with the stagnation. An Quantum Particle Swarm algorithm together with Entropy maximization helps us to get the most probable threshold value which correctly segments the lesions from the background in MR of brain. Using change detection algorithm the segmented object of the MR at time tx is compared with another object of the MR at the time ty . The proposed method is applied on variety of MR images having lesions and gives favourable results in identifying changes taking place in the human brain.

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Index Terms

Computer Science
Information Sciences

Keywords

Region of Interest Particle Swarm Optimization Magnetic Resonance Imaging Entropy Hybrid Particle Swarm Optimization Wavelet Mutation Image Differencing

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