COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach
COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach
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Publisher
Henderson: Tech Science Press
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Language
English
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Publisher
Henderson: Tech Science Press
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Scope and Contents
Contents
The purpose of this research is the segmentation of lungs computed tomography (CT) scan for the diagnosis of COVID-19 by using machine learning methods. Our dataset contains data from patients who are prone to the epidemic. It contains three types of lungs CT images (Normal, Pneumonia, and COVID-19) collected from two different sources; the first o...
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Full title
COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach
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Record Identifier
TN_cdi_proquest_journals_2507804761
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2507804761
Other Identifiers
ISSN
1546-2226,1546-2218
E-ISSN
1546-2226
DOI
10.32604/cmc.2021.016037
