• DOI:10.1109/JBHI.2020.3045475
Corpus ID: 209140699

DR-GAN: Conditional Generative Adversarial Network for Fine-Grained Lesion Synthesis on Diabetic Retinopathy Images

@article{Zhou2020DRGANCG,
  title={DR-GAN: Conditional Generative Adversarial Network for Fine-Grained Lesion Synthesis on Diabetic Retinopathy Images},
  author={Y. Zhou and Boyang Wang and X. He and Shanshan Cui and Fan Zhu and Li Liu and Ling Shao},
  journal={IEEE journal of biomedical and health informatics},
  year={2020},
  volume={PP}
}

Y. Zhou, Boyang Wang, +4 authors Ling Shao

Published 2020

Computer Science, Medicine, Engineering

IEEE journal of biomedical and health informatics

Diabetic retinopathy (DR) is a complication of diabetes that severely affects eyes. It can be graded into five levels of severity according to international protocol. However, optimizing a grading model to have strong generalizability requires a large amount of balanced training data, which is difficult to collect, particularly for the high severity levels. Typical data augmentation methods, including random flipping and rotation, cannot generate data with high diversity. In this paper, we… CONTINUE READING

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