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Angle closure Glaucoma Evaluation Challenge

The goal of the challenge is to evaluate and compare automated algorithms for angle closure classification and localization of scleral spur (SS) points on a common dataset of AS-OCT images. We invite the medical image analysis community to participate by developing and testing existing and novel automated classification and segmentation methods. More detail AGE challenge.

1.Download data

After you sign up Grand Challenge and join the AGE challenge.

Dataset can be downloaded from the Download page

We assume Training100.zip and Validation_ASOCT_Image.zip are stored @ ./AGE_challenge Baseline/datasets/

2.Environment installation

  • Python >= 3.5
  • cuDNN >= 7.3
  • CUDA 9
  • paddlepaddle-gpu >= 1.5.0
  • xlrd == 1.2.0
  • tqdm == 4.32.2
  • pycocotools == 2.0.0

More detail PaddlePaddle Installation Manuals

3. Angle closure classification task

See Classification/.

4. Scleral spur localization task

We provide two baseline models for localization task.

See LocalizationFCN/ and LocalizationRCNN/.