Automated processing of thermal imaging to detect COVID-19

Author:

Brzezinski Rafael Y.,Rabin Neta,Lewis Nir,Peled Racheli,Kerpel Ariel,Tsur Avishai M.,Gendelman Omer,Naftali-Shani Nili,Gringauz Irina,Amital Howard,Leibowitz Avshalom,Mayan Haim,Ben-Zvi Ilan,Heller Eyal,Shechtman Liran,Rogowski Ori,Shenhar-Tsarfaty Shani,Konen Eli,Marom Edith M.,Ironi Avinoah,Rahav Galia,Zimmer Yair,Grossman Ehud,Ovadia-Blechman Zehava,Leor Jonathan,Hoffer Oshrit

Abstract

AbstractRapid 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.

Funder

Israel Innovation Authority

Nicholas and Elizabeth Slezak Super Center for Cardiac Research and Biomedical Engineering

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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