Deep Learning for Computer-Aided Diagnosis of COVID-19

Yen-Wei Chen, Jiaqing LIU, Huiming HUANG, Fang WANG, Lanfen LIN, Tomoko Tateyama, Yutaro IWAMOTO

doi:https://doi.org/10.36463/idw.2021.0853

1:00 PM - 1:20 PM

[DES1/AIS1-1(Invited)] Deep Learning for Computer-Aided Diagnosis of COVID-19

*Yen-Wei Chen¹, Jiaqing LIU¹, Huiming HUANG², Fang WANG², Lanfen LIN², Tomoko Tateyama³, Yutaro IWAMOTO¹ (1.Ritsumeikan University (Japan), 2.Zhejiang University (China), 3.Shiga University (Japan))

Deep learning, COVID-19, CT image, CT involvement score

https://doi.org/10.36463/idw.2021.0853

Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide. CT is extensively used as a key complement for diagnosing COVID-19; moreover, high sensitivity was reported in patients infected by COVID-19. CT image analysis for quantitative assessments of COVID-19 becomes an important issue. Recently, deep learning has been used for computer-aided diagnosis of COVID-19, including lung infection detection, segmentation, and disease diagnosis, etc. In spite of the...

Proceedings of the International Display Workshops Volume 28 (IDW '21)

[DES1/AIS1-1(Invited)] Deep Learning for Computer-Aided Diagnosis of COVID-19