charleskangzhou / kaggle_dr_image_quality_miccai2018_workshop

The funds image quality label is provided by iMed (homepage: http://imed.nimte.ac.cn/ ; http://imed.nimte.ac.cn/aboutus.html)

paper

Fundus Image Quality-Guided Diabetic Retinopathy Grading https://link.springer.com/chapter/10.1007/978-3-030-00949-6_29

Kaggle DR dataset

EyePACS: Diabetic retinopathy detection. https://www.kaggle.com/c/diabetic-retinopathy-detection/data

Kaggle DR Image Quality Dataset

The fundus image quality label is provided by iMed.(homepage: http://imed.nimte.ac.cn/;http://imed.nimte.ac.cn/aboutus.html)

Four instances of poor quality images in Kaggle DR dataset

The quality of these images are too poor to identify the lesion.

Unbalanced ratio

In our Kaggle DR image quality dataset, the number of good and poor quality images are shown as follows. The ratio is extremely unbalanced.

Quality Label

The csv files are in quality_csv_label

quality_label_train.csv

quality_label_validate.csv

quality_label_test.csv

0 denotes poor quality

1 denotes good quality

Citation

If you find this useful, please cite our work as follows:

@incollection{zhou2018fundus, title={Fundus Image Quality-Guided Diabetic Retinopathy Grading},
author={Zhou, Kang and Gu, Zaiwang and Li, Annan and Cheng, Jun and Gao, Shenghua and Liu, Jiang},
booktitle={Computational Pathology and Ophthalmic Medical Image Analysis},
pages={245--252},
year={2018},
publisher={Springer}
}