Sparse-Gan: Sparsity-Constrained Generative Adversarial Network for Anomaly Detection in Retinal OCT Image

@article{Zhou2020SparseGanSG,
  title={Sparse-Gan: Sparsity-Constrained Generative Adversarial Network for Anomaly Detection in Retinal OCT Image},
  author={Kang Zhou and Shenghua Gao and Jun Cheng and Zaiwang Gu and H. Fu and Zhi Tu and Jianlong Yang and Yitian Zhao and Jiang Liu},
  journal={2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)},
  year={2020},
  pages={1227-1231}
}
  • Kang Zhou, Shenghua Gao, Jiang Liu
  • Published 28 November 2019
  • Computer Science
  • 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)
With the development of convolutional neural network, deep learning has shown its success for retinal disease detection from optical coherence tomography (OCT) images. However, deep learning often relies on large scale labelled data for training, which is oftentimes challenging especially for disease with low occurrence. Moreover, a deep learning system trained from data-set with one or a few diseases is unable to detect other unseen diseases, which limits the practical usage of the system in… 

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