Name
Title | ||
|---|---|---|
Diagnosis of diabetic retinopathy based on holistic texture and local retinal features. |
Abstract | ||
|---|---|---|
•A new method to analyze eye fundus images for the automatic detection of diabetic retinopathy is proposed.•Two types of features were extracted including the holistic texture features and the local retinal features.•The performance of our system improved greatly when two local retinal features – microaneurysms and exudates – were incorporated into the analysis.•The diagnostic performance of the algorithm is very promising and similar to previous automatic systems and human expert analysis on the same dataset.•This framework has the potential to be used as an aiding tool for the diagnosis of diabetic retinopathy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.ins.2018.09.064 | Information Sciences |
Keywords | Field | DocType |
Diabetic retinopathy,Eye fundus image,Holistic texture features,Exudates,Micro-aneurysms | Diabetic retinopathy,Pattern recognition,Support vector machine,Fundus (eye),Artificial intelligence,Independent component analysis,Retinal,Modular design,Artificial neural network,Cross-validation,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
475 | 0020-0255 | 0 |
PageRank | References | Authors |
0.34 | 18 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luis Frazao | 1 | 0 | 0.68 |
| Nipon Theera-umpon | 2 | 184 | 30.59 |
| S. Auephanwiriyakul | 3 | 246 | 39.45 |