Table 6 Comparison of results with already deployed technique
From: Automated detection of glaucoma using structural and non structural features
Technique | Specificity | Sensitivity | Accuracy |
|---|---|---|---|
Local dataset with 50 images | |||
CDR based detection | 0.91 | 0.93 | 92 |
Feature based detection | 0.91 | 0.86 | 90 |
Combined results | 0.88 | 1 | 92 |
Local dataset with 100 images | |||
CDR based detection | 0.98 | 0.92 | 97 |
Feature based detection | 0.90 | 0.88 | 89 |
Combined results | 0.87 | 1 | 91 |
Local dataset with 50 images | |||
Glaucoma detection using CDR and ISNT rule (Khan et al. 2013) | 0.85 | 0.73 | 82 |