# DENet_GlaucomaScreen

**Repository Path**: nosferatu/DENet_GlaucomaScreen

## Basic Information

- **Project Name**: DENet_GlaucomaScreen
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-06-07
- **Last Updated**: 2021-06-07

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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]](https://1drv.ms/u/s!ArBRrL8ao6jzmkF5oVSUXEeWfK77?e=ddcG9c) [[BaiduPan]](https://pan.baidu.com/s/1eDT0N4tQsWI4McyGB36vLw):
	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'  
 

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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](http://arxiv.org/abs/1805.07549))

[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](https://arxiv.org/abs/1801.00926)) 


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**For ORIGA and SCES datasets**

Unfortunately, the ORIGA, SCES, and SINDI datasets cannot be released due to the clinical policy.

But, here is an other glaucoma challenge, *Retinal Fundus Glaucoma Challenge (REFUGE)*, including disc/cup segmentation, glaucoma screening, and localization of Fovea. If you are interested, you can register it from:
[[HERE]](https://refuge.grand-challenge.org/home/)

We also provide the results of our DENet, the details could be found from: [[HERE]](https://github.com/HzFu/REFUGE_baseline) 

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Update log:

- 18.07.06: Released the code.