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Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review
The universal transmission of pandemic COVID-19 (Coronavirus) causes an immediate need to commit in the fight across the whole human population. The emergencies for human health care are limited for this abrupt outbreak and abandoned environment. In this situation, inventive automation like computer...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7928188/ https://www.ncbi.nlm.nih.gov/pubmed/33686333 http://dx.doi.org/10.1007/s11042-021-10714-5 |
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author | Bhargava, Anuja Bansal, Atul |
author_facet | Bhargava, Anuja Bansal, Atul |
author_sort | Bhargava, Anuja |
collection | PubMed |
description | The universal transmission of pandemic COVID-19 (Coronavirus) causes an immediate need to commit in the fight across the whole human population. The emergencies for human health care are limited for this abrupt outbreak and abandoned environment. In this situation, inventive automation like computer vision (machine learning, deep learning, artificial intelligence), medical imaging (computed tomography, X-Ray) has developed an encouraging solution against COVID-19. In recent months, different techniques using image processing are done by various researchers. In this paper, a major review on image acquisition, segmentation, diagnosis, avoidance, and management are presented. An analytical comparison of the various proposed algorithm by researchers for coronavirus has been carried out. Also, challenges and motivation for research in the future to deal with coronavirus are indicated. The clinical impact and use of computer vision and deep learning were discussed and we hope that dermatologists may have better understanding of these areas from the study. |
format | Online Article Text |
id | pubmed-7928188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-79281882021-03-04 Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review Bhargava, Anuja Bansal, Atul Multimed Tools Appl Article The universal transmission of pandemic COVID-19 (Coronavirus) causes an immediate need to commit in the fight across the whole human population. The emergencies for human health care are limited for this abrupt outbreak and abandoned environment. In this situation, inventive automation like computer vision (machine learning, deep learning, artificial intelligence), medical imaging (computed tomography, X-Ray) has developed an encouraging solution against COVID-19. In recent months, different techniques using image processing are done by various researchers. In this paper, a major review on image acquisition, segmentation, diagnosis, avoidance, and management are presented. An analytical comparison of the various proposed algorithm by researchers for coronavirus has been carried out. Also, challenges and motivation for research in the future to deal with coronavirus are indicated. The clinical impact and use of computer vision and deep learning were discussed and we hope that dermatologists may have better understanding of these areas from the study. Springer US 2021-03-03 2021 /pmc/articles/PMC7928188/ /pubmed/33686333 http://dx.doi.org/10.1007/s11042-021-10714-5 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Bhargava, Anuja Bansal, Atul Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review |
title | Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review |
title_full | Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review |
title_fullStr | Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review |
title_full_unstemmed | Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review |
title_short | Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review |
title_sort | novel coronavirus (covid-19) diagnosis using computer vision and artificial intelligence techniques: a review |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7928188/ https://www.ncbi.nlm.nih.gov/pubmed/33686333 http://dx.doi.org/10.1007/s11042-021-10714-5 |
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