Table 5.
Comparison of Proposed study with Previous Works
| Parameter | Jasionowska et al.[32] | Guo et al.[5] | Minvathi et al.[33] | Proposed method |
|---|---|---|---|---|
| Database | DDSM | MIAS | MIAS/DDSM | MIAS/DDSM |
| Dataset | 34 AD ROIs, 258 non-AD ROIs. | 19 AD ROIs, 21 non-AD ROIs from MIAS. | 23 AD ROIs, 97 non-AD ROIs from DDSM. 19 AD ROIs, 152 non-AD ROIs from mini-MIAS. | 146 AD ROIs, 75 non-AD ROIs from DDSM. 39 AD ROIs (fixed size). 19 AD ROIs (ground truth) and 108 non-AD ROIs from MIAS. |
| Accuracy (%) | 83.50 | 72.50 | 89.69 | 95.34 (MIAS) 92.94 (DDSM) |
| Sensitivity (%) | 68.00 | N.S. | 94.38 | 92.30 (MIAS) 93.33 (DDSM) |
| Size of ROI (pixels) | Ground truth | 128 × 128 | 128 × 128 | Fixed size as well as variable size. |
| Features extracted | GLCM and statistic features | Fractal features | GLCM | GLCM, fractal-based features, Fourier power spectrum features. |
| Feature selection | Correlation-based feature selection | N.S. | Forward feature selection | Stepwise regression. |
| Classifier | SVM tuned with kernel parameters | SVM tuned with kernels parameters | SVM and Multi layer perceptrons | SVM tuned with kernel parameters. |
| Validation | Cross validation (fold not specified). | 4 cross validation. | 70/30 with leave one out cross validation | 3-fold cross validation With testing and training split into 2/3 and 1/3, respectively. |
| Clinical evaluation | No | No | No | Yes |
N.S. not specified in the paper