Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey

Highlights：

• The survey gives an overview of different diabetic retinopathy biomarkers and lesions and different tasks related to diagnosis. Also we have given an overview of datasets, which have been developed for research on diagnosis and commonly used performance metrics.

• Various bibliographic reference sources are used to explore the diverse applications of deep learning algorithms in the diabetic retinopathy diagnosis where most of which appeared recently.

• It covers deep learning based methods, which have been proposed for retinal blood vessels segmentation, OD detection and segmentation, detection of various lesions such as EXs, MAs, HMs and referable diabetic retinopathy.

• The review mentioned deep learning based methods in diabetic retinopathy and discussed their overall performance, gaps and future directions. Also it gives comparison with stat-of-the-art traditional methods based on hand-engineered features.

摘要

•This review gives a comprehensive view on stat-of-the-art deep learning based methods related to diabetic retinopathy diagnosis and will help researchers to conduct further research on this problem.•The survey gives an overview of different diabetic retinopathy biomarkers and lesions and different tasks related to diagnosis. Also we have given an overview of datasets, which have been developed for research on diagnosis and commonly used performance metrics.•Various bibliographic reference sources are used to explore the diverse applications of deep learning algorithms in the diabetic retinopathy diagnosis where most of which appeared recently.•It covers deep learning based methods, which have been proposed for retinal blood vessels segmentation, OD detection and segmentation, detection of various lesions such as EXs, MAs, HMs and referable diabetic retinopathy.•The review mentioned deep learning based methods in diabetic retinopathy and discussed their overall performance, gaps and future directions. Also it gives comparison with stat-of-the-art traditional methods based on hand-engineered features.