Lung infection and normal region segmentation from CT volumes of COVID-19 cases

Masahiro Oda; Yuichiro Hayashi; Yoshito Otake; Masahiro Hashimoto M.D.; Toshiaki Akashi M.D.; Kensaku Mori

doi:10.1117/12.2582066

15 February 2021 Lung infection and normal region segmentation from CT volumes of COVID-19 cases

Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto M.D., Toshiaki Akashi M.D., Kensaku Mori

Proceedings Volume 11597, Medical Imaging 2021: Computer-Aided Diagnosis; 115972X (2021) https://doi.org/10.1117/12.2582066
Event: SPIE Medical Imaging, 2021, Online Only

Conference Poster

Abstract

This paper proposes an automated segmentation method of infection and normal regions in the lung from CT volumes of COVID-19 patients. From December 2019, novel coronavirus disease 2019 (COVID-19) spreads over the world and giving significant impacts to our economic activities and daily lives. To diagnose the large number of infected patients, diagnosis assistance by computers is needed. Chest CT is effective for diagnosis of viral pneumonia including COVID-19. A quantitative analysis method of condition of the lung from CT volumes by computers is required for diagnosis assistance of COVID-19. This paper proposes an automated segmentation method of infection and normal regions in the lung from CT volumes using a COVID-19 segmentation fully convolutional network (FCN). In diagnosis of lung diseases including COVID-19, analysis of conditions of normal and infection regions in the lung is important. Our method recognizes and segments lung normal and infection regions in CT volumes. To segment infection regions that have various shapes and sizes, we introduced dense pooling connections and dilated convolutions in our FCN. We applied the proposed method to CT volumes of COVID-19 cases. From mild to severe cases of COVID-19, the proposed method correctly segmented normal and infection regions in the lung. Dice scores of normal and infection regions were 0.911 and 0.753, respectively.

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Citation Download Citation

Masahiro Oda, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto M.D., Toshiaki Akashi M.D., and Kensaku Mori "Lung infection and normal region segmentation from CT volumes of COVID-19 cases", Proc. SPIE 11597, Medical Imaging 2021: Computer-Aided Diagnosis, 115972X (15 February 2021); https://doi.org/10.1117/12.2582066

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