/DENet_GlaucomaScreen

Code for "Disc-aware Ensemble Network for Glaucoma Screening from Fundus Image"

Primary LanguagePython

DENet_GlaucomaScreen

Code for TMI 2018 "Disc-aware Ensemble Network for Glaucoma Screening from Fundus Image"

Project homepage：http://hzfu.github.io/proj_glaucoma_fundus.html

  1. The code is based on: Keras 2.0 + Tensorflow 1.0
  2. The deep output is raw segmentation result without ellipse fitting.
  3. The pre-train models are trained on ORIGA full dataset.
  4. Download the trained models for DENet to 'pre_model' folder: [OneDrive] [BaiduPan]:
    1. Disc detection model: 'pre_model_DiscSeg.h5'
    2. Global image Screening model: 'pre_model_img.h5'
    3. Segmentation-guided Screening model: 'pre_model_disc.h5'
    4. Local disc Screening model: 'pre_model_ROI.h5'
    5. Polar disc Screening model: 'pre_model_flat.h5'

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

[1] Huazhu Fu, Jun Cheng, Yanwu Xu, Changqing Zhang, Damon Wing Kee Wong, Jiang Liu, and Xiaochun Cao, "Disc-aware Ensemble Network for Glaucoma Screening from Fundus Image", IEEE Transactions on Medical Imaging (TMI), 2018. DOI: 10.1109/TMI.2018.2837012 (ArXiv version)

[2] Huazhu Fu, Jun Cheng, Yanwu Xu, Damon Wing Kee Wong, Jiang Liu, and Xiaochun Cao, "Joint Optic Disc and Cup Segmentation Based on Multi-label Deep Network and Polar Transformation", IEEE Transactions on Medical Imaging (TMI), vol. 37, no. 7, pp. 1597–1605, 2018. (ArXiv version)

Update log:

  • 18.07.06: Released the code.