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An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients

PURPOSE: To reconstruct a 3D visualization from CT images of COVID-19 patients in order to improve understanding of the disease for better management and follow-up. MATERIALS AND METHODS: We have retrieved CT images of 185 COVID-19 patients from the Cheikh Zaid International University Hospital in R...

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Autores principales: Hasni, Mouad, Farahat, Zineb, Abdeljelil, Azar, Marzouki, Kamal, Aoudad, Mohamed, Tlemsani, Zakaria, Megdiche, Kawtar, Ngote, Nabil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648513/
https://www.ncbi.nlm.nih.gov/pubmed/33195849
http://dx.doi.org/10.1016/j.heliyon.2020.e05453
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author Hasni, Mouad
Farahat, Zineb
Abdeljelil, Azar
Marzouki, Kamal
Aoudad, Mohamed
Tlemsani, Zakaria
Megdiche, Kawtar
Ngote, Nabil
author_facet Hasni, Mouad
Farahat, Zineb
Abdeljelil, Azar
Marzouki, Kamal
Aoudad, Mohamed
Tlemsani, Zakaria
Megdiche, Kawtar
Ngote, Nabil
author_sort Hasni, Mouad
collection PubMed
description PURPOSE: To reconstruct a 3D visualization from CT images of COVID-19 patients in order to improve understanding of the disease for better management and follow-up. MATERIALS AND METHODS: We have retrieved CT images of 185 COVID-19 patients from the Cheikh Zaid International University Hospital in Rabat, Morocco. We then performed computer processing that allowed us to obtain a 3D visualization of these patients. RESULTS: In this article, we have chosen to do 3D reconstruction of three specific cases among 185 patients: - Cases (A1, A2) which are negative RT-PCR patient with normal CT images. - Cases (B1, B2) which are positive RT-PCR patient with abnormal CT images. - Case (C) which is a negative RT-PCR patient with CT abnormalities. To improve our results and have a better quality of the 3D reconstruction, we used different algorithms and a specific row data processing. CONCLUSION: 3D reconstruction has a significant role in the diagnosis and management of COVID-19 patients. The quality and reliability of 3D reconstructions allow the clinician to make a quick and efficient diagnosis and avoid an eventual false negative (produced by the RT-PCR test). We suggest including chest 3D reconstruction in the patient management and prognosis evaluation.
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spelling pubmed-76485132020-11-09 An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients Hasni, Mouad Farahat, Zineb Abdeljelil, Azar Marzouki, Kamal Aoudad, Mohamed Tlemsani, Zakaria Megdiche, Kawtar Ngote, Nabil Heliyon Research Article PURPOSE: To reconstruct a 3D visualization from CT images of COVID-19 patients in order to improve understanding of the disease for better management and follow-up. MATERIALS AND METHODS: We have retrieved CT images of 185 COVID-19 patients from the Cheikh Zaid International University Hospital in Rabat, Morocco. We then performed computer processing that allowed us to obtain a 3D visualization of these patients. RESULTS: In this article, we have chosen to do 3D reconstruction of three specific cases among 185 patients: - Cases (A1, A2) which are negative RT-PCR patient with normal CT images. - Cases (B1, B2) which are positive RT-PCR patient with abnormal CT images. - Case (C) which is a negative RT-PCR patient with CT abnormalities. To improve our results and have a better quality of the 3D reconstruction, we used different algorithms and a specific row data processing. CONCLUSION: 3D reconstruction has a significant role in the diagnosis and management of COVID-19 patients. The quality and reliability of 3D reconstructions allow the clinician to make a quick and efficient diagnosis and avoid an eventual false negative (produced by the RT-PCR test). We suggest including chest 3D reconstruction in the patient management and prognosis evaluation. Elsevier 2020-11-07 /pmc/articles/PMC7648513/ /pubmed/33195849 http://dx.doi.org/10.1016/j.heliyon.2020.e05453 Text en © 2020 The Authors. Published by Elsevier Ltd. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Hasni, Mouad
Farahat, Zineb
Abdeljelil, Azar
Marzouki, Kamal
Aoudad, Mohamed
Tlemsani, Zakaria
Megdiche, Kawtar
Ngote, Nabil
An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients
title An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients
title_full An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients
title_fullStr An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients
title_full_unstemmed An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients
title_short An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients
title_sort efficient approach based on 3d reconstruction of ct scan to improve the management and monitoring of covid-19 patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648513/
https://www.ncbi.nlm.nih.gov/pubmed/33195849
http://dx.doi.org/10.1016/j.heliyon.2020.e05453
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