• Corpus ID: 236912605

Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization

@article{Feng2021UnsupervisedDA,
  title={Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization},
  author={Wei Feng and Lie Ju and Lin Wang and Kaimin Song and Xin Wang and Xin Zhao and Qingyi Tao and Zongyuan Ge},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.01821}
}
Retinal vessel segmentation plays a key role in computer-aided screening, diagnosis, and treatment of various cardiovascular and ophthalmic diseases. Recently, deep learning-based retinal vessel segmentation algorithms have achieved remarkable performance. However, due to the domain shift problem, the performance of these algorithms often degrades when they are applied to new data that is different from the training data. Manually labeling new data for each test domain is often a timeconsuming… 
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