Bat optimization based neuron model of stochastic resonance for the enhancement of MR images

Munendra Singh, Ashish Verma, Neeraj Sharma

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

Stochastic resonance (SR) performs the enhancement of the low in contrast image with the help of noise. The present paper proposes a modified neuron model based stochastic resonance approach applied for the enhancement of T1 weighted, T2 weighted, fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI) sequences of magnetic resonance imaging. Multi objective bat algorithm has been applied to tune the parameters of the modified neuron model for the maximization of two competitive image performance indices contrast enhancement factor (F) and mean opinion score (MOS). The quality of processed image depends on the choice of these image performance indices rather the selection of SR parameters. The proposed approach performs well on enhancement of magnetic resonance (MR) images, as a result there is improvement in the gray-white matter differentiation and has been found helpful in the better diagnosis of MR images.

Original languageEnglish
Pages (from-to)124-134
Number of pages11
JournalBiocybernetics and Biomedical Engineering
Volume37
Issue number1
DOIs
Publication statusPublished - 2017

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

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