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Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques

INTRODUCTION: Medical images are usually affected by biological and physical artifacts or noise, which reduces image quality and hence poses difficulties in visual analysis, interpretation and thus requires higher doses and increased radiographs repetition rate. OBJECTIVES: This study aims at assess...

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Autores principales: Omer, Hiba, Tamam, Nissren, Alameen, Suhaib, Algadi, Sahar, Thanh Tai, Duong, Sulieman, Abdelmoneim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9073048/
https://www.ncbi.nlm.nih.gov/pubmed/35531247
http://dx.doi.org/10.1016/j.sjbs.2021.11.043
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author Omer, Hiba
Tamam, Nissren
Alameen, Suhaib
Algadi, Sahar
Thanh Tai, Duong
Sulieman, Abdelmoneim
author_facet Omer, Hiba
Tamam, Nissren
Alameen, Suhaib
Algadi, Sahar
Thanh Tai, Duong
Sulieman, Abdelmoneim
author_sort Omer, Hiba
collection PubMed
description INTRODUCTION: Medical images are usually affected by biological and physical artifacts or noise, which reduces image quality and hence poses difficulties in visual analysis, interpretation and thus requires higher doses and increased radiographs repetition rate. OBJECTIVES: This study aims at assessing image quality during CT abdomen and brain examinations using filtering techniques as well as estimating the radiogenic risk associated with CT abdomen and brain examinations. MATERIALS AND METHODS: The data were collected from the Radiology Department at Royal Care International (RCI) Hospital, Khartoum, Sudan. The study included 100 abdominal CT images and 100 brain CT images selected from adult patients. Filters applied are namely: Mean filter, Gaussian filter, Median filter and Minimum filter. In this study, image quality after denoising is measured based on the Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and the Structural Similarity Index Metric (SSIM). RESULTS: The results show that the images quality parameters become higher after applications of filters. Median filter showed improved image quality as interpreted by the measured parameters: PSNR and SSIM, and it is thus considered as a better filter for removing the noise from all other applied filters. DISCUSSION: The noise removed by the different filters applied to the CT images resulted in enhancing high quality images thereby effectively revealing the important details of the images without increasing the patients’ risks from higher doses. CONCLUSIONS: Filtering and image reconstruction techniques not only reduce the dose and thus the radiation risks, but also enhances high quality imaging which allows better diagnosis.
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spelling pubmed-90730482022-05-07 Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques Omer, Hiba Tamam, Nissren Alameen, Suhaib Algadi, Sahar Thanh Tai, Duong Sulieman, Abdelmoneim Saudi J Biol Sci Original Article INTRODUCTION: Medical images are usually affected by biological and physical artifacts or noise, which reduces image quality and hence poses difficulties in visual analysis, interpretation and thus requires higher doses and increased radiographs repetition rate. OBJECTIVES: This study aims at assessing image quality during CT abdomen and brain examinations using filtering techniques as well as estimating the radiogenic risk associated with CT abdomen and brain examinations. MATERIALS AND METHODS: The data were collected from the Radiology Department at Royal Care International (RCI) Hospital, Khartoum, Sudan. The study included 100 abdominal CT images and 100 brain CT images selected from adult patients. Filters applied are namely: Mean filter, Gaussian filter, Median filter and Minimum filter. In this study, image quality after denoising is measured based on the Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and the Structural Similarity Index Metric (SSIM). RESULTS: The results show that the images quality parameters become higher after applications of filters. Median filter showed improved image quality as interpreted by the measured parameters: PSNR and SSIM, and it is thus considered as a better filter for removing the noise from all other applied filters. DISCUSSION: The noise removed by the different filters applied to the CT images resulted in enhancing high quality images thereby effectively revealing the important details of the images without increasing the patients’ risks from higher doses. CONCLUSIONS: Filtering and image reconstruction techniques not only reduce the dose and thus the radiation risks, but also enhances high quality imaging which allows better diagnosis. Elsevier 2022-04 2021-11-26 /pmc/articles/PMC9073048/ /pubmed/35531247 http://dx.doi.org/10.1016/j.sjbs.2021.11.043 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Omer, Hiba
Tamam, Nissren
Alameen, Suhaib
Algadi, Sahar
Thanh Tai, Duong
Sulieman, Abdelmoneim
Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques
title Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques
title_full Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques
title_fullStr Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques
title_full_unstemmed Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques
title_short Elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques
title_sort elimination of biological and physical artifacts in abdomen and brain computed tomography procedures using filtering techniques
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9073048/
https://www.ncbi.nlm.nih.gov/pubmed/35531247
http://dx.doi.org/10.1016/j.sjbs.2021.11.043
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