ISVC2020 Fundus2Angio

This code is part of the supplementary materials for the ISVC 2020 for our paper Fundus2Angio: A Conditional GAN Architecture for Generating Fluorescein Angiography Images from Retinal Fundus Photography . The paper has since been accpeted to ISVC 2020 and will be preseneted in October 2020.

Arxiv Pre-print

https://arxiv.org/abs/2005.05267

Citation

@article{kamran2020fundus2angio,
  title={Fundus2Angio: A Novel Conditional GAN Architecture for Generating Fluorescein Angiography Images from Retinal Fundus Photography},
  author={Kamran, Sharif Amit and Hossain, Khondker Fariha and Tavakkoli, Alireza and Zuckerbrod, Stewart Lee},
  journal={arXiv preprint arXiv:2005.05267},
  year={2020}
}

Virtual Oral Presentation (YouTube)

Pre-requisite

• Ubuntu 18.04 / Windows 7 or later
• NVIDIA Graphics card

Installation Instruction for Ubuntu

• Download and Install Nvidia Drivers
• Download and Install via Runfile Nvidia Cuda Toolkit 10.0
• Download and Install Nvidia CuDNN 7.6.5 or later
• Install Pip3 and Python3 enviornment

sudo apt-get install pip3 python3-dev

• Install Tensorflow-Gpu version-2.0.0 and Keras version-2.3.1

sudo pip3 install tensorflow-gpu==2.0.3
sudo pip3 install keras==2.3.1

• Install packages from requirements.txt

sudo pip3 -r requirements.txt

Dataset download link for Hajeb et al.

https://sites.google.com/site/hosseinrabbanikhorasgani/datasets-1/fundus-fluorescein-angiogram-photographs--colour-fundus-images-of-diabetic-patients