Research Article
A Hybrid DE-RGSO-ELM for Brain Tumor Tissue Categorization in 3D Magnetic Resonance Images
Table 10
Accuracy results amongst various classifiers using 3D proposed feature extraction model.
| | Dataset | ELM | SVM | BPN | IELM-PSO | ELM-RGSO |
| | Real time data (70 cases) | 90.0% | 86.6% | 80.0% | 96.6% | 97.8% | | 86.6% | 83.3% | 76.6% | 93.3% | 94.6% | | 86.6% | 80.0% | 76.6% | 90.0% | 89.9% | | 83.3% | 80.0% | 76.6% | 86.6% | 88.67% | | 76.6% | 70.0% | 66.6% | 83.3% | 89.01% |
| | SPL and MBC sets (30 cases) | 92.8% | 90.0% | 85.7% | 97.14% | 97.63% | | 92.8% | 88.5% | 82.85% | 94.28% | 96.59% | | 91.4% | 90.0% | 88.5% | 94.28% | 96.00% | |
90.0% | 88.5% | 85.7% | 92.8% | 94.61% | | 90.0% | 82.85% | 78.5% | 91.4% | 93.89% |
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