A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT

Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 diagnosis on chest CT is helpful to counter the outbreak of SARS-CoV-2. A weakly-supervised deep learning framework was developed using 3D CT volumes for COVID-19 classification and lesion localization. For each patient, the lung region was segmented using a pre-trained UNet; then the segmented 3D lung region was fed into a 3D deep neural network to predict the probability of COVID-19 infectious; the COVID-19 lesions are localized by combining the activation regions in the classification network and the unsupervised connected…

• T
  Tencent
• NN
  National Natural Science Foundation of China

  Awards: 61876212, 61733007, 81873919
• FR
  Fundamental Research Funds for the Central Universities

  Award: 2020kfyXGYJ021