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Evaluation of Retinal Image Quality Assessment
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README.md

Eye-Quality (EyeQ) Assessment Dataset

The project web for "Evaluation of Retinal Image Quality Assessment"


-Introduction:

Eye-Quality (EyeQ) Assessment Dataset is a re-annotatation subset from the EyePACS dataset for fundus image quality assessment.

EyeQ dataset has 28,792 retinal images with a three-level quality grading (i.e., 'Good', 'Usable' and 'Reject').

Examples of different retinal image quality grades.

Train - - - - - Test - - - - - Total
DR-0 DR-1 DR-2 DR-3 DR-4 All DR-0 DR-1 DR-2 DR-3 DR-4 All
Good 6,342 699 1,100 167 39 8,347 5,966 886 1,354 199 65 8,470
Usable 1,353 103 283 79 58 1,896 3,201 359 721 145 133 4,559
Reject 1,544 109 426 87 154 2,320 2,195 153 569 104 199 3,220
Total 9,239 911 1,809 333 251 12,543 1,1362 1,398 2,644 448 397 16,249

-Usage:

  1. The original fundus images could be downloaded from EyePACS dataset.
  2. All the original fundus images should be pre-porcessed by 'EyeQ_process_main.py' in folder 'EyeQ_preprocess'.
  3. The quality label is in 'Label_EyeQ_v1.xlsx', where the 'train' and 'test' list is divided by EyePACS, and the 'DR_grade' label is also from EyePACS.

-Reference:

If you use this dataset and code, please cite the following papers:

[1] Huazhu Fu, Boyang Wang, Jianbing Shen, Shanshan Cui, Yanwu Xu, Jiang Liu, Ling Shao, "Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces", in MICCAI, 2019. [PDF]


Update log:

  • 19.07.10: Released the dataset.
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