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Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain
In the COVID-19 era, it may be possible to detect COVID-19 by detecting lesions in scans, i.e., ground-glass opacity, consolidation, nodules, reticulation, or thickened interlobular septa, and lesion distribution, but it becomes difficult at the early stages due to embryonic lesion growth and the re...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689094/ https://www.ncbi.nlm.nih.gov/pubmed/36428826 http://dx.doi.org/10.3390/diagnostics12112766 |
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author | Diwakar, Manoj Singh, Prabhishek Swarup, Chetan Bajal, Eshan Jindal, Muskan Ravi, Vinayakumar Singh, Kamred Udham Singh, Teekam |
author_facet | Diwakar, Manoj Singh, Prabhishek Swarup, Chetan Bajal, Eshan Jindal, Muskan Ravi, Vinayakumar Singh, Kamred Udham Singh, Teekam |
author_sort | Diwakar, Manoj |
collection | PubMed |
description | In the COVID-19 era, it may be possible to detect COVID-19 by detecting lesions in scans, i.e., ground-glass opacity, consolidation, nodules, reticulation, or thickened interlobular septa, and lesion distribution, but it becomes difficult at the early stages due to embryonic lesion growth and the restricted use of high dose X-ray detection. Therefore, it may be possible for a patient who may or may not be infected with coronavirus to consider using high-dose X-rays, but it may cause more risks. Conclusively, using low-dose X-rays to produce CT scans and then adding a rigorous denoising algorithm to the scans is the best way to protect patients from side effects or a high dose X-ray when diagnosing coronavirus involvement early. Hence, this paper proposed a denoising scheme using an NLM filter and method noise thresholding concept in the shearlet domain for noisy COVID CT images. Low-dose COVID CT images can be further utilized. The results and comparative analysis showed that, in most cases, the proposed method gives better outcomes than existing ones. |
format | Online Article Text |
id | pubmed-9689094 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96890942022-11-25 Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain Diwakar, Manoj Singh, Prabhishek Swarup, Chetan Bajal, Eshan Jindal, Muskan Ravi, Vinayakumar Singh, Kamred Udham Singh, Teekam Diagnostics (Basel) Article In the COVID-19 era, it may be possible to detect COVID-19 by detecting lesions in scans, i.e., ground-glass opacity, consolidation, nodules, reticulation, or thickened interlobular septa, and lesion distribution, but it becomes difficult at the early stages due to embryonic lesion growth and the restricted use of high dose X-ray detection. Therefore, it may be possible for a patient who may or may not be infected with coronavirus to consider using high-dose X-rays, but it may cause more risks. Conclusively, using low-dose X-rays to produce CT scans and then adding a rigorous denoising algorithm to the scans is the best way to protect patients from side effects or a high dose X-ray when diagnosing coronavirus involvement early. Hence, this paper proposed a denoising scheme using an NLM filter and method noise thresholding concept in the shearlet domain for noisy COVID CT images. Low-dose COVID CT images can be further utilized. The results and comparative analysis showed that, in most cases, the proposed method gives better outcomes than existing ones. MDPI 2022-11-12 /pmc/articles/PMC9689094/ /pubmed/36428826 http://dx.doi.org/10.3390/diagnostics12112766 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Diwakar, Manoj Singh, Prabhishek Swarup, Chetan Bajal, Eshan Jindal, Muskan Ravi, Vinayakumar Singh, Kamred Udham Singh, Teekam Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain |
title | Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain |
title_full | Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain |
title_fullStr | Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain |
title_full_unstemmed | Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain |
title_short | Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain |
title_sort | noise suppression and edge preservation for low-dose covid-19 ct images using nlm and method noise thresholding in shearlet domain |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689094/ https://www.ncbi.nlm.nih.gov/pubmed/36428826 http://dx.doi.org/10.3390/diagnostics12112766 |
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