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Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm
In this paper, an optimal algorithm is presented for de-noising of medical images. The presented algorithm is based on improved version of local pixels grouping and principal component analysis. In local pixels grouping algorithm, blocks matching based on L(2) norm method is utilized, which leads to...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4759838/ https://www.ncbi.nlm.nih.gov/pubmed/26955565 |
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author | Fadaee, Mojtaba Shamsi, Mousa Saberkari, Hamidreza Sedaaghi, Mohammad Hossein |
author_facet | Fadaee, Mojtaba Shamsi, Mousa Saberkari, Hamidreza Sedaaghi, Mohammad Hossein |
author_sort | Fadaee, Mojtaba |
collection | PubMed |
description | In this paper, an optimal algorithm is presented for de-noising of medical images. The presented algorithm is based on improved version of local pixels grouping and principal component analysis. In local pixels grouping algorithm, blocks matching based on L(2) norm method is utilized, which leads to matching performance improvement. To evaluate the performance of our proposed algorithm, peak signal to noise ratio (PSNR) and structural similarity (SSIM) evaluation criteria have been used, which are respectively according to the signal to noise ratio in the image and structural similarity of two images. The proposed algorithm has two de-noising and cleanup stages. The cleanup stage is carried out comparatively; meaning that it is alternately repeated until the two conditions based on PSNR and SSIM are established. Implementation results show that the presented algorithm has a significant superiority in de-noising. Furthermore, the quantities of SSIM and PSNR values are higher in comparison to other methods. |
format | Online Article Text |
id | pubmed-4759838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-47598382016-03-07 Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm Fadaee, Mojtaba Shamsi, Mousa Saberkari, Hamidreza Sedaaghi, Mohammad Hossein J Med Signals Sens Original Article In this paper, an optimal algorithm is presented for de-noising of medical images. The presented algorithm is based on improved version of local pixels grouping and principal component analysis. In local pixels grouping algorithm, blocks matching based on L(2) norm method is utilized, which leads to matching performance improvement. To evaluate the performance of our proposed algorithm, peak signal to noise ratio (PSNR) and structural similarity (SSIM) evaluation criteria have been used, which are respectively according to the signal to noise ratio in the image and structural similarity of two images. The proposed algorithm has two de-noising and cleanup stages. The cleanup stage is carried out comparatively; meaning that it is alternately repeated until the two conditions based on PSNR and SSIM are established. Implementation results show that the presented algorithm has a significant superiority in de-noising. Furthermore, the quantities of SSIM and PSNR values are higher in comparison to other methods. Medknow Publications & Media Pvt Ltd 2015 /pmc/articles/PMC4759838/ /pubmed/26955565 Text en Copyright: © 2015 Journal of Medical Signals & Sensors http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Fadaee, Mojtaba Shamsi, Mousa Saberkari, Hamidreza Sedaaghi, Mohammad Hossein Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm |
title | Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm |
title_full | Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm |
title_fullStr | Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm |
title_full_unstemmed | Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm |
title_short | Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm |
title_sort | computed tomography images de-noising using a novel two stage adaptive algorithm |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4759838/ https://www.ncbi.nlm.nih.gov/pubmed/26955565 |
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