TY - JOUR
T1 - Automated processing of thermal imaging to detect COVID-19
AU - Brzezinski, Rafael Y.
AU - Rabin, Neta
AU - Lewis, Nir
AU - Peled, Racheli
AU - Kerpel, Ariel
AU - Tsur, Avishai M.
AU - Gendelman, Omer
AU - Naftali-Shani, Nili
AU - Gringauz, Irina
AU - Amital, Howard
AU - Leibowitz, Avshalom
AU - Mayan, Haim
AU - Ben-Zvi, Ilan
AU - Heller, Eyal
AU - Shechtman, Liran
AU - Rogowski, Ori
AU - Shenhar-Tsarfaty, Shani
AU - Konen, Eli
AU - Marom, Edith M.
AU - Ironi, Avinoah
AU - Rahav, Galia
AU - Zimmer, Yair
AU - Grossman, Ehud
AU - Ovadia-Blechman, Zehava
AU - Leor, Jonathan
AU - Hoffer, Oshrit
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85114138025&partnerID=8YFLogxK
U2 - 10.1038/s41598-021-96900-9
DO - 10.1038/s41598-021-96900-9
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C2 - 34471180
AN - SCOPUS:85114138025
SN - 2045-2322
VL - 11
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 17489
ER -