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10.1016/j.heliyon.2020.e05453 http://scihub22266oqcxt.onion/10.1016/j.heliyon.2020.e05453 33195849!7648513!33195849     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Heliyon 2020 ; 6 (11): e05453 Nephropedia Template TP {{tp|p=33195849|t=2020. An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients |pdf=|usr=}}{{33195849}} gab.com Text An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients JO: Heliyon http://www.kidney.de/pget.php?&tw=1&pmid=33195849 #FOAvip 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. Twit Text FOAVip An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients ????Heliyon http://www.kidney.de/pget.php?&tw=1&pmid=33195849 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33195849 #FOAvip English Wikipedia <ref>{{Cite pmid|33195849}}</ref> An efficient approach based on 3D reconstruction of CT scan to improve the management and monitoring of COVID-19 patients #MMPMID33195849 Hasni M; Farahat Z; Abdeljelil A; Marzouki K; Aoudad M; Tlemsani Z; Megdiche K; Ngote N Heliyon 2020[Nov]; 6 (11): e05453 PMID33195849show ga 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. äAn efficient approach based on 3D reconstruction of CT scan to improve(epmc).pdf DeepDyve Pubget Overpricing