Aiming at the problems of image super-resolution algorithm with many convolutional neural networks, such as large parameters, large computational complexity and blurred image texture, we propose a new algorithm model....Aiming at the problems of image super-resolution algorithm with many convolutional neural networks, such as large parameters, large computational complexity and blurred image texture, we propose a new algorithm model. The classical convolutional neural network is improved, the convolution kernel size is adjusted, and the parameters are reduced;the pooling layer is added to reduce the dimension. Reduced computational complexity, increased learning rate, and reduced training time. The iterative back-projection algorithm is combined with the convolutional neural network to create a new algorithm model. The experimental results show that compared with the traditional facial illusion method, the proposed method can obtain better performance.展开更多
Background Venovenous extracorporeal membrane oxygenation(VV-ECMO)has been demonstrated to be effective in treating patients with virus-induced acute respiratory distress syndrome(ARDS).However,whether the management ...Background Venovenous extracorporeal membrane oxygenation(VV-ECMO)has been demonstrated to be effective in treating patients with virus-induced acute respiratory distress syndrome(ARDS).However,whether the management of ECMO is different in treating H1N1 influenza and coronavirus disease 2019(COVID-19)-associated ARDS patients remains unknown.Methods This is a retrospective cohort study.We included 12 VV-ECMO-supported COVID-19 patients admitted to The First Affiliated Hospital of Guangzhou Medical University,Guangzhou Eighth People's Hospital,and Wuhan Union Hospital West Campus between January 23 and March 31,2020.We retrospectively included VV-ECMO-supported patients with COVID-19 and H1N1 influenza-associated ARDS.Clinical characteristics,respiratory mechanics including plateau pressure,driving pressure,mechanical power,ventilatory ratio(VR)and lung compliance,and outcomes were compared.Results Data from 25 patients with COVID-19(n=12)and H1N1(n=13)associated ARDS who had received ECMO support were analyzed.COVID-19 patients were older than H1N1 influenza patients(P=0.004).The partial pressure of arterial carbon dioxide(PaCO_(2))and VR before ECMO initiation were significantly higher in COVID-19 patients than in H1N1 influenza patients(P<0.001 and P=0.004,respectively).COVID-19 patients showed increased plateau and driving pressure compared with H1N1 subjects(P=0.013 and P=0.018,respectively).Patients with COVID-19 remained longer on ECMO support than did H1N1 influenza patients(P=0.015).COVID-19 patients who required ECMO support also had fewer intensive care unit and ventilator-free days than H1N1.Conclusions Compared with H1N1 influenza patients,COVID-19 patients were older and presented with increased PaCO_(2) and VR values before ECMO initiation.The differences between ARDS patients with COVID-19 and influenza on VV-ECMO detailed herein could be helpful for obtaining a better understanding of COVID-19 and for better clinical management.展开更多
文摘Aiming at the problems of image super-resolution algorithm with many convolutional neural networks, such as large parameters, large computational complexity and blurred image texture, we propose a new algorithm model. The classical convolutional neural network is improved, the convolution kernel size is adjusted, and the parameters are reduced;the pooling layer is added to reduce the dimension. Reduced computational complexity, increased learning rate, and reduced training time. The iterative back-projection algorithm is combined with the convolutional neural network to create a new algorithm model. The experimental results show that compared with the traditional facial illusion method, the proposed method can obtain better performance.
基金support from the Special Project of the Guangdong Science and Technology Department (grant number:2020B1111340013)Mergency Key Program of Guangzhou Laboratory (grant number:EKPG21-29)+1 种基金Guangzhou City School (Institute)Joint Funding Project (grant number:202201020414)the National Natural Science Foundation of China (grant number:81970071).
文摘Background Venovenous extracorporeal membrane oxygenation(VV-ECMO)has been demonstrated to be effective in treating patients with virus-induced acute respiratory distress syndrome(ARDS).However,whether the management of ECMO is different in treating H1N1 influenza and coronavirus disease 2019(COVID-19)-associated ARDS patients remains unknown.Methods This is a retrospective cohort study.We included 12 VV-ECMO-supported COVID-19 patients admitted to The First Affiliated Hospital of Guangzhou Medical University,Guangzhou Eighth People's Hospital,and Wuhan Union Hospital West Campus between January 23 and March 31,2020.We retrospectively included VV-ECMO-supported patients with COVID-19 and H1N1 influenza-associated ARDS.Clinical characteristics,respiratory mechanics including plateau pressure,driving pressure,mechanical power,ventilatory ratio(VR)and lung compliance,and outcomes were compared.Results Data from 25 patients with COVID-19(n=12)and H1N1(n=13)associated ARDS who had received ECMO support were analyzed.COVID-19 patients were older than H1N1 influenza patients(P=0.004).The partial pressure of arterial carbon dioxide(PaCO_(2))and VR before ECMO initiation were significantly higher in COVID-19 patients than in H1N1 influenza patients(P<0.001 and P=0.004,respectively).COVID-19 patients showed increased plateau and driving pressure compared with H1N1 subjects(P=0.013 and P=0.018,respectively).Patients with COVID-19 remained longer on ECMO support than did H1N1 influenza patients(P=0.015).COVID-19 patients who required ECMO support also had fewer intensive care unit and ventilator-free days than H1N1.Conclusions Compared with H1N1 influenza patients,COVID-19 patients were older and presented with increased PaCO_(2) and VR values before ECMO initiation.The differences between ARDS patients with COVID-19 and influenza on VV-ECMO detailed herein could be helpful for obtaining a better understanding of COVID-19 and for better clinical management.
