Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Deep Convolutional Neural Network–Based Computer-Aided Detection System for COVID-19 Using Multiple Lung Scans: Design and Implementation Study
102
Zitationen
6
Autoren
2021
Jahr
Abstract
The proposed model achieved acceptable results in the categorization of 2 data classes. Therefore, a CAD system was designed on the basis of this model for COVID-19 detection using multiple lung computed tomography scans. The system differentiated all COVID-19 cases from non-COVID-19 ones without any error in the application phase. Overall, the proposed deep learning-based CAD system can greatly help radiologists detect COVID-19 in its early stages. During the COVID-19 pandemic, the use of a CAD system as a screening tool would accelerate disease detection and prevent the loss of health care resources.
Ähnliche Arbeiten
La certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
2020 · 19.284 Zit.
A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control (Invited Paper)
2024 · 14.284 Zit.
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
2018 · 8.706 Zit.
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
2021 · 7.328 Zit.
scikit-image: image processing in Python
2014 · 6.797 Zit.