This repository contains the IPython code for the paper

Taibou Birgui Sekou, Moncef Hidane, Julien Olivier and Hubert Cardot. From Patch to Image Segmentation using Fully Convolutional Networks - Application to Retinal Images.

Given a retinal image database and a fully convolutional network (FCN) f, this tool first pre-trains it on an on-the-fly generated patch database, then fine-tunes it on the original full-sized images.

Environment: The following software/libraries are needed:

• TensorFlow 1.12.0
• numpy 1.15.1
• h5py 2.7.0
• matplotlib 2.0.2
• scikit-image 0.14.1
• scikit-learn *.19.1

Datasets: The following datasets are used in our experiments:

• DRIVE
• STARE
• CHASE_DB1
• IDRiD

Data preprocessing: All the images are preprocessed using:

• Gray scale conversion
• Gamma correction (with gamma=1.7)
• CLAHE normalization