Meeting Abstract
Enhancing Automatic Classification of Hepatocellular Carcinoma Images through Image Masking, Tissue Changes, and Trabecular Features
Table 1
Experiment results.
| | Training data | Test data | Set of features | Sensitivity | Specificity |
| | Biopsy sample | Biopsy sample | 78 nuclei (unmasked) | 86.36% | 88.29% | | Surgery sample | Surgery sample | 78 nuclei (unmasked) | 88.21% | 87.99% | | Combination of biopsy and surgery sample | Biopsy sample | 78 nuclei (unmasked) | 84.73% | 91.87% | | 78 nuclei (masked) | 85.27% | 90.67% | | 72 nuclei (masked) + 21 new features | 88.18% | 91.87% | | Surgery sample | 78 nuclei (unmasked) | 88.95% | 87.62% | | 78 nuclei (masked) | 89.50% | 87.62% | | 72 nuclei (masked) + 21 new features | 91.34% | 89.68% |
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