Identifying COVID19 from Chest CT Images: A Deep Convolutional Neural Networks Based Approach.
J Healthc Eng
; 2020: 8843664, 2020.
Article
in English
| MEDLINE | ID: covidwho-729435
ABSTRACT
Coronavirus Disease (COVID19) is a fast-spreading infectious disease that is currently causing a healthcare crisis around the world. Due to the current limitations of the reverse transcription-polymerase chain reaction (RT-PCR) based tests for detecting COVID19, recently radiology imaging based ideas have been proposed by various works. In this work, various Deep CNN based approaches are explored for detecting the presence of COVID19 from chest CT images. A decision fusion based approach is also proposed, which combines predictions from multiple individual models, to produce a final prediction. Experimental results show that the proposed decision fusion based approach is able to achieve above 86% results across all the performance metrics under consideration, with average AUROC and F1-Score being 0.883 and 0.867, respectively. The experimental observations suggest the potential applicability of such Deep CNN based approach in real diagnostic scenarios, which could be of very high utility in terms of achieving fast testing for COVID19.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Tomography, X-Ray Computed
/
Neural Networks, Computer
/
Coronavirus Infections
/
Clinical Laboratory Techniques
/
Betacoronavirus
/
Deep Learning
Type of study:
Diagnostic study
/
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
J Healthc Eng
Year:
2020
Document Type:
Article
Affiliation country:
2020
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