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This repository includes several retinal diseases recognition tasks including open-set semi-supervised learning, domain adaptation, label noise and long-tailed classification.

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PyJulie/Awesome-Retinal-Diseases-Recognition

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Retinal Diseases Recognition

This repository includes several retinal diseases recognition tasks including open-set semi-supervised learning, domain adaptation, label noise and long-tailed classification.

Todo

  1. Codes release and datasets preparation

1. Open-set Semi-supervised Retinal Diseases Grading.

@article{ju2021synergic,
title={Synergic Adversarial Label Learning for Grading Retinal Diseases via Knowledge Distillation and Multi-task Learning},
author={Ju, Lie and Wang, Xin and Zhao, Xin and Lu, Huimin and Mahapatra, Dwarikanath and Bonnington, Paul and Ge, Zongyuan},
journal={IEEE Journal of Biomedical and Health Informatics},
year={2021},
publisher={IEEE}
}

[Paper] [Arxiv] [code]

2. Fundus Images Domain Adaptation

@article{ju2021leveraging,
title={Leveraging Regular Fundus Images for Training UWF Fundus Diagnosis Models via Adversarial Learning and Pseudo-Labeling},
author={Ju, Lie and Wang, Xin and Zhao, Xin and Bonnington, Paul and Drummond, Tom and Ge, Zongyuan},
journal={IEEE Transactions on Medical Imaging},
year={2021},
publisher={IEEE}
}

@article{feng2021unsupervised,
title={Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization},
author={Feng, Wei and Ju, Lie and Wang, Lin and Song, Kaimin and Wang, Xin and Zhao, Xin and Tao, Qingyi and Ge, Zongyuan},
journal={arXiv preprint arXiv:2108.01821},
year={2021}
}

3. Retinal Diseases Classification with Label Noise

@article{ju2021improving,
title={Improving medical image classification with label noise using dual-uncertainty estimation},
author={Ju, Lie and Wang, Xin and Wang, Lin and Mahapatra, Dwarikanath and Zhao, Xin and Harandi, Mehrtash and Drummond, Tom and Liu, Tongliang and Ge, Zongyuan},
journal={arXiv preprint arXiv:2103.00528},
year={2021}
}

4. Long-tailed Retinal Diseases Classification

@article{ju2021relational,
title={Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition},
author={Ju, Lie and Wang, Xin and Wang, Lin and Liu, Tongliang and Zhao, Xin and Drummond, Tom and Mahapatra, Dwarikanath and Ge, Zongyuan},
journal={arXiv preprint arXiv:2104.11057},
year={2021}
}

@article{ju2021long,
title={Long-Tailed Multi-Label Retinal Diseases Recognition Using Hierarchical Information and Hybrid Knowledge Distillation},
author={Ju, Lie and Wang, Xin and Yu, Zhen and Wang, Lin and Zhao, Xin and Ge, Zongyuan},
journal={arXiv preprint arXiv:2111.08913},
year={2021}
}

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This repository includes several retinal diseases recognition tasks including open-set semi-supervised learning, domain adaptation, label noise and long-tailed classification.

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