Multi-task contrastive learning for automatic CT and X-ray diagnosis of COVID-19

Jinpeng Li, Gangming Zhao, Yaling Tao, Penghua Zhai, Hao Chen, Huiguang He, Ting Cai

Abstract: Highlights•A novel Contrastive Multi-Task Convolutional Neural Network (CMT-CNN) is proposed for automatic COVID-19 diagnosis.•The main task is to diagnose COVID-19 from other pneumonia and normal controls. The auxiliary task is self-supervised contrastive learning to acquire transformation-invariant representations.•A series of interpretable transformations are defined for medical image augmentation.•Extensive experiments demonstrate that the auxiliary task can significantly improve the generalization of CNN on both CT and X-ray datasets.

External IDs:doi:10.1016/j.patcog.2021.107848