Medical Image Enhancement by a Bilateral Filter Using Optimization Technique.
For researchers, denoising of Magnetic Resonance (MR) image is a greatest challenge in digital image processing. In this paper, the impulse noise and Rician noise in the medical MR images are removed by using Bilateral Filter (BF). The novel approaches are presented in this paper; Enhanced grasshopp...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 8 |
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| Autores principales: | , |
| Formato: | algorithm diagnostic images equations & formulas review tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=137490031&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137490031 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Aug2019 vid: 43 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137490031 137490031 137490031 10.1007/s10916-019-1370-x 137490031 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Medical Image Enhancement by a Bilateral Filter Using Optimization Technique. aug: au: Anoop, V. Bipin, P. R. affil: Jyothi Engineering College, Cheruthuruthy, 679531, Thrissur, Kerala, India sug: subj: Magnetic Resonance Imaging Noise Prevention and Control Digital Imaging Methods Image Enhancement Methods Algorithms Image Interpretation, Computer Assisted Methods ab: For researchers, denoising of Magnetic Resonance (MR) image is a greatest challenge in digital image processing. In this paper, the impulse noise and Rician noise in the medical MR images are removed by using Bilateral Filter (BF). The novel approaches are presented in this paper; Enhanced grasshopper optimization algorithm (EGOA) is used to optimize the BF parameters. To simulate the medical MR images (with different variances), the impulse and Rician noises are added. The EGOA is applied to the noisy image in searching regions of window size, spatial and intensity domain to obtain the filter parameters optimally. The PSNR is taken as fitness value for optimization. We examined the proposed technique results with other MR images After the optimal parameters assurance. In order to comprehend the BF parameters selection importance, the results of proposed denoising method is contrasted with other previously used BFs, genetic algorithm (GA), gravitational search algorithm (GSA) using the quality metrics such as signal-to-noise ratio (SNR), structural similarity index metric (SSIM), mean squared error (MSE), and PSNR. The outcome shows that the EOGA method with BF shows good results than the earlier methods in both edge preservation and noise elimination from medical MR images. The experimental results demonstrate the performance of the proposed method with the accuracy, computational time, and maximum deviation, Peak Signal to Noise Ratio (PSNR), MSE, SSIM, and entropy values of MR images over the existing methods. pubtype: Academic Journal doctype: algorithm diagnostic images equations & formulas review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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