Diabetic Retinopathy Web App

Webapp for classification of Diabetic Retinopathy from retinal images using flask and keras.

Diabetic Retinopathy

Diabetic retinopathy is an eye condition that can cause vision loss and blindness in people who have diabetes. It affects blood vessels in the retina.

No Diabetic Retinopathy	Severe Diabetic Retinopathy

Data Description

Dataset consists of retina images taken using fundus photography under a variety of imaging conditions.

A clinician has rated each image for the severity of diabetic retinopathy on a scale of 0 to 4:

0 - No DR

1 - Mild

2 - Moderate

3 - Severe

4 - Proliferative DR

About the Model used for prediction

Densely Connected Convolutional Networks or DenseNet

Dense Convolutional Network (DenseNet), which connects each layer to every other layer in a feed-forward fashion. Whereas traditional convolutional networks with L layers have L connections - one between each layer and its subsequent layer.

A more efficient model variant DenseNet-BC (DenseNet-Bottleneck-Compressed) networks are trained. Using the DenseNet-BC-121-32 model as the base model.

Advantages of DenseNet-BC are:

• Reduced number of parameters
• Similar or Better performance
• Better accuracy

Dense Net architecture as shown in the original paper which shows the connections from each layer to every other layer:

Requirements Insatallation

Using conda or virtualenv

virtualenv venv
source /bin/activate
python3 -m pip install -r requirements.txt

Direct (Not recommended)

python3 -m pip install -r requirements.txt

Run the Webapp by executing

python3 app.py

Refrences

• Diabetic Retinopathy Wikipedia
• Diabetic Retinopathy National Eye Institute
• Fundus Image Dataset from Kaggle
• Densely Connected Convolutional Networks (DenseNets)