Name
Title | ||
|---|---|---|
Automatic differentiation of Glaucoma visual field from non-glaucoma visual filed using deep convolutional neural network. |
Abstract | ||
|---|---|---|
Our algorithm based on CNN has achieved higher accuracy compared to human ophthalmologists and traditional rules (AGIS and GSS2) in differentiation of glaucoma and non-glaucoma VFs. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12880-018-0273-5 | BMC Medical Imaging |
Keywords | Field | DocType |
Deep learning,Glaucoma,Visual field | Glaucoma,Pattern recognition,Convolutional neural network,Support vector machine,Artificial intelligence,Meridian (perimetry, visual field),Radiology,Deep learning,Artificial neural network,Random forest,Visual field,Medicine | Journal |
Volume | Issue | ISSN |
18 | 1 | 1471-2342 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
13 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fei Li | 1 | 0 | 0.34 |
| Zhe Wang | 2 | 199 | 19.26 |
| Guoxiang Qu | 3 | 0 | 1.01 |
| Diping Song | 4 | 2 | 2.08 |
| Ye Yuan | 5 | 0 | 0.34 |
| Yang Xu | 6 | 118 | 41.02 |
| Kai Gao | 7 | 78 | 39.46 |
| Guangwei Luo | 8 | 0 | 0.68 |
| Zegu Xiao | 9 | 0 | 0.34 |
| Dennis S. C. Lam | 10 | 0 | 0.68 |
| Hua Zhong | 11 | 100 | 13.13 |
| Yu Qiao | 12 | 2267 | 152.01 |
| Xiulan Zhang | 13 | 21 | 4.68 |