Research Article
Classification of SD-OCT Volumes Using Local Binary Patterns: Experimental Validation for DME Detection
Table 1
Summary of the state-of-the-art methods.
| Reference | Diseases | Data size | Preprocessing | Features | Representation | Classifier | Evaluation | Results | AMD | DME | Normal | Denoise | Flatten | Aligning | Cropping |
| [9] | ✓ | ✓ | ✓ | 45 | ✓ | ✓ | | ✓ | HOG | | Linear SVM | ACC | 86.7%, 100%, and 100% | [10] | ✓ | | ✓ | 384 | | | | | Texton | BoW, PCA | RF | AUC | 0.984 | [11] | ✓ | ✓ | ✓ | 326 | | ✓ | ✓ | | Edge, LBP | PCA | SVM-RBF | AUC | 0.93 | [12] | | ✓ | ✓ | 62 | ✓ | | | | LBP-LBP-TOP | PCA, BoW, and histogram | RF | SE, SP | 87.5%, 75% |
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