Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation

  title={Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation},
  author={Chen Chen and Kerstin Hammernik and Cheng Ouyang and Chen Qin and Wenjia Bai and Daniel Rueckert},
Deep learning-based segmentation methods are vulnerable to unforeseen data distribution shifts during deployment, e.g. change of image appearances or contrasts caused by different scanners, unexpected imaging artifacts etc. In this paper, we present a cooperative framework for training image segmentation models and a latent space augmentation method for generating hard examples. Both contributions improve model generalization and robustness with limited data. The cooperative training framework… Expand
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