Name
Title | ||
|---|---|---|
Automated segmentation of exudates, haemorrhages, microaneurysms using single convolutional neural network. |
Abstract | ||
|---|---|---|
•Automated segmentation of exudates, haemorrhages and micro-aneurysms.•A 10-layer convolutional neural network is employed.•Trained and tested on CLEOPATRA database.•149 images were used for training; another 149 images were used for testing.•Achieved a sensitivity of 0.8758 and 0.7158 for exudates and dark lesions respectively. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.ins.2017.08.050 | Information Sciences |
Keywords | Field | DocType |
Exudates,Microaneurysms,Haemorrhages,Convolutional neural network,Fundus image,Segmentation,Diabetic retinopathy | Diabetic retinopathy,Computer vision,Segmentation,Convolutional neural network,Fundus (eye),Artificial intelligence,Blindness,Mathematics | Journal |
Volume | Issue | ISSN |
420 | C | 0020-0255 |
Citations | PageRank | References |
28 | 1.21 | 21 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jen-Hong Tan | 1 | 745 | 32.04 |
| Hamido Fujita | 2 | 2644 | 185.03 |
| Sobha Sivaprasad | 3 | 72 | 3.17 |
| Sulatha V. Bhandary | 4 | 271 | 13.76 |
| A. Krishna Rao | 5 | 91 | 4.46 |
| Kuang Chua Chua | 6 | 201 | 9.36 |
| Rajendra Acharya U | 7 | 4666 | 296.34 |