Prediction of different eye diseases based on fundus photography via deep transfer learning

This repository contains the code and data used in the paper.

Project Summary

We propose to utilize a lightweight deep learning architecture called MobileNetV2 and transfer learning to distinguish four common eye diseases including Glaucoma, Maculopathy, Pathological Myopia, and Retinitis Pigmentosa from normal controls using a small training data. The inputs to the algorithm are fundus images. This project was implemented using the tensorflow framework. We include code and data here for ease reproduction of the results in the paper.

Reproduction Guidance

All experiments are performed on Google Research Colab (Many thanks to Google!!).

Data

All data can be found in folder "Dataset". Download the Data folder then upload the sub-folder "HIGHMIDCHANCEGLAUMYOPIAmaculopathyRP" to Google Drive.

For users own data, please follow the structure of the data set folder. You may need to change the script for different number of classes.

Codes

All implementation code, including intermediate and final results, can be found in Codes folder.

file discription

ModelAndResults.ipynb the model in this project.

Fundus5Runs.ipynb Comparision with other models.

binarys Binary classifier for each disease.

rerun the code

Upload the nodebook or use the code to Colab then connect it to Google drive.

Rerun the cells for results.

Structure

MobileNetV2 feature extractor:

An initial convolution layer, followed by 
17 reversed residual blocks, and followed by
1 poinwised convolution layer.

Implemented from keras-tensorflow-applications. Pretrained on ImageNet.

The model also contains one global average layer and the final prediction layer.

figure of structure

Tool

Model Results

Confusion Matrix, run on the test data.

0: Normal, 1: Glaucoma, 2: Pathological Myopia 3: Maculopathy, 4: Retinitis Pigmentosa

Visulization

visualization using Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

A: Normal, B: Glaucoma, C: Pathological Myopia D: Maculopathy, F: Retinitis Pigmentosa. Mis-classified image are marked in red. The first is mis-classified as glaucoma, the second is misclassified as maculopathy.

Citations

Guo et al. Prediction of different eye diseases based on fundus photography via deep transfer learning. Submitted.