DR_GCN brief info

diabetic retinopathy grading using lesion correlation learned by Graph Convolution Network

This is an implementation of Diabetic retinopathy grading based onLesion correlation graph Network takes Diabetic Retinopathy fundus images as input, output the grading result.

Whole model structure shows like this.

We combine the lesion correlation graph learned by Graph Convolution Network (GCN), combined with CNN fundus image features, and do the grading. Into 5 grades. SIFT extracted ROI vs SURF extracted ROI

lesion correlation graph constructed process

SURF features construct Nodes and their cooccurence construct edge information

experiment result

Deploying details

The DR_GCN model definition can be found in demo_dr_gcn.py SURF extraction and clustering process to get the Nodes and Edge information can be found in kmeans_feature_adj.py and surf_feature.py