Automated processing of thermal imaging to detect COVID-19
Abstract Rapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on advanced image processing algorithms....
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Nature Portfolio
2021
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oai:doaj.org-article:5f6862399abb4b39be5aef00ee6f0d732021-12-02T15:29:02ZAutomated processing of thermal imaging to detect COVID-1910.1038/s41598-021-96900-92045-2322https://doaj.org/article/5f6862399abb4b39be5aef00ee6f0d732021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96900-9https://doaj.org/toc/2045-2322Abstract Rapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on advanced image processing algorithms. We captured thermal images of the backs of individuals with and without COVID-19 using a portable thermal camera that connects directly to smartphones. Our novel image processing algorithms automatically extracted multiple texture and shape features of the thermal images and achieved an area under the curve (AUC) of 0.85 in COVID-19 detection with up to 92% sensitivity. Thermal imaging scores were inversely correlated with clinical variables associated with COVID-19 disease progression. In summary, we show, for the first time, that a hand-held thermal imaging device can be used to detect COVID-19. Non-invasive thermal imaging could be used to screen for COVID-19 in out-of-hospital settings, especially in low-income regions with limited imaging resources.Rafael Y. BrzezinskiNeta RabinNir LewisRacheli PeledAriel KerpelAvishai M. TsurOmer GendelmanNili Naftali-ShaniIrina GringauzHoward AmitalAvshalom LeibowitzHaim MayanIlan Ben-ZviEyal HellerLiran ShechtmanOri RogowskiShani Shenhar-TsarfatyEli KonenEdith M. MaromAvinoah IroniGalia RahavYair ZimmerEhud GrossmanZehava Ovadia-BlechmanJonathan LeorOshrit HofferNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021) |
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DOAJ |
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DOAJ |
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Medicine R Science Q |
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Medicine R Science Q Rafael Y. Brzezinski Neta Rabin Nir Lewis Racheli Peled Ariel Kerpel Avishai M. Tsur Omer Gendelman Nili Naftali-Shani Irina Gringauz Howard Amital Avshalom Leibowitz Haim Mayan Ilan Ben-Zvi Eyal Heller Liran Shechtman Ori Rogowski Shani Shenhar-Tsarfaty Eli Konen Edith M. Marom Avinoah Ironi Galia Rahav Yair Zimmer Ehud Grossman Zehava Ovadia-Blechman Jonathan Leor Oshrit Hoffer Automated processing of thermal imaging to detect COVID-19 |
| description |
Abstract Rapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on advanced image processing algorithms. We captured thermal images of the backs of individuals with and without COVID-19 using a portable thermal camera that connects directly to smartphones. Our novel image processing algorithms automatically extracted multiple texture and shape features of the thermal images and achieved an area under the curve (AUC) of 0.85 in COVID-19 detection with up to 92% sensitivity. Thermal imaging scores were inversely correlated with clinical variables associated with COVID-19 disease progression. In summary, we show, for the first time, that a hand-held thermal imaging device can be used to detect COVID-19. Non-invasive thermal imaging could be used to screen for COVID-19 in out-of-hospital settings, especially in low-income regions with limited imaging resources. |
| format |
article |
| author |
Rafael Y. Brzezinski Neta Rabin Nir Lewis Racheli Peled Ariel Kerpel Avishai M. Tsur Omer Gendelman Nili Naftali-Shani Irina Gringauz Howard Amital Avshalom Leibowitz Haim Mayan Ilan Ben-Zvi Eyal Heller Liran Shechtman Ori Rogowski Shani Shenhar-Tsarfaty Eli Konen Edith M. Marom Avinoah Ironi Galia Rahav Yair Zimmer Ehud Grossman Zehava Ovadia-Blechman Jonathan Leor Oshrit Hoffer |
| author_facet |
Rafael Y. Brzezinski Neta Rabin Nir Lewis Racheli Peled Ariel Kerpel Avishai M. Tsur Omer Gendelman Nili Naftali-Shani Irina Gringauz Howard Amital Avshalom Leibowitz Haim Mayan Ilan Ben-Zvi Eyal Heller Liran Shechtman Ori Rogowski Shani Shenhar-Tsarfaty Eli Konen Edith M. Marom Avinoah Ironi Galia Rahav Yair Zimmer Ehud Grossman Zehava Ovadia-Blechman Jonathan Leor Oshrit Hoffer |
| author_sort |
Rafael Y. Brzezinski |
| title |
Automated processing of thermal imaging to detect COVID-19 |
| title_short |
Automated processing of thermal imaging to detect COVID-19 |
| title_full |
Automated processing of thermal imaging to detect COVID-19 |
| title_fullStr |
Automated processing of thermal imaging to detect COVID-19 |
| title_full_unstemmed |
Automated processing of thermal imaging to detect COVID-19 |
| title_sort |
automated processing of thermal imaging to detect covid-19 |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/5f6862399abb4b39be5aef00ee6f0d73 |
| work_keys_str_mv |
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