[HTML][HTML] Automated detection and quantification of COVID-19 pneumonia: CT imaging analysis by a deep learning-based software

H Zhang, J Zhang, H Zhang, Y Nan, Y Zhao… - European journal of …, 2020 - Springer
Background The novel coronavirus disease 2019 (COVID-19) is an emerging worldwide
threat to public health. While chest computed tomography (CT) plays an indispensable role …

[HTML][HTML] A deep learning system to screen novel coronavirus disease 2019 pneumonia

X Xu, X Jiang, C Ma, P Du, X Li, S Lv, L Yu, Q Ni… - Engineering, 2020 - Elsevier
The real-time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral
RNA from sputum or nasopharyngeal swab had a relatively low positive rate in the early …

[HTML][HTML] Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography

J Chen, L Wu, J Zhang, L Zhang, D Gong, Y Zhao… - Scientific reports, 2020 - nature.com
Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel
coronavirus (COVID19) pneumonia. We aimed to construct a system based on deep …

A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis

S Wang, Y Zha, W Li, Q Wu, X Li, M Niu… - European …, 2020 - Eur Respiratory Soc
Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become
insufficient in many regions. Fast diagnosis of COVID-19 and finding high-risk patients with …

[HTML][HTML] COVID-19 pneumonia diagnosis using a simple 2D deep learning framework with a single chest CT image: model development and validation

H Ko, H Chung, WS Kang, KW Kim, Y Shin… - Journal of medical …, 2020 - jmir.org
Background Coronavirus disease (COVID-19) has spread explosively worldwide since the
beginning of 2020. According to a multinational consensus statement from the Fleischner …

[HTML][HTML] A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images

Q Ni, ZY Sun, L Qi, W Chen, Y Yang, L Wang… - European …, 2020 - Springer
Objectives To utilize a deep learning model for automatic detection of abnormalities in chest
CT images from COVID-19 patients and compare its quantitative determination performance …

Covidctnet: An open-source deep learning approach to identify covid-19 using ct image

T Javaheri, M Homayounfar, Z Amoozgar… - arXiv preprint arXiv …, 2020 - arxiv.org
Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options.
Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease …

[HTML][HTML] From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans

Z Li, Z Zhong, Y Li, T Zhang, L Gao, D Jin, Y Sun… - European …, 2020 - Springer
Objective To develop a fully automated AI system to quantitatively assess the disease
severity and disease progression of COVID-19 using thick-section chest CT images …

Using artificial intelligence to detect COVID-19 and community-acquired pneumonia based on pulmonary CT: evaluation of the diagnostic accuracy

L Li, L Qin, Z Xu, Y Yin, X Wang, B Kong, J Bai, Y Lu… - Radiology, 2020 - pubs.rsna.org
Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world
since the beginning of 2020. It is desirable to develop automatic and accurate detection of …

Artificial intelligence augmentation of radiologist performance in distinguishing COVID-19 from pneumonia of other origin at chest CT

HX Bai, R Wang, Z Xiong, B Hsieh, K Chang, K Halsey… - Radiology, 2020 - pubs.rsna.org
Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share
similar CT characteristics, which contributes to the challenges in differentiating them with …