AnandInguva/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}
}