Table 5.
Number of ROIs resulted in FP reduction using sparse curvelet coefficient-based LBP & ANN classification at training and validation stage.
| Class | Dataset used | Benign/malignant mass | Nonmass/benign mass | Total (#) images | TPR (true-positive rate) = TP/#lesions | FPPI (false-positive per image) = FP/# images | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| Previous stage | Selected (TP) | Lost (FN) | Previous stage | Selected (TN) | Lost (FP) | |||||
| Normal vs abnormal | MIAS | 108 ∗ 2 = 216 | 201 | 15 | 273 | 265 | 8 | 315 | (201/216) = 0.93 | (8/315) = 0.02 |
| DDSM | 140 ∗ 4 = 560 | 516 | 44 | 1203 | 1155 | 48 | 240 | (516/560) = 0.92 | (48/240) = 0.2 | |
|
| ||||||||||
| Benign vs malignant | MIAS | 49 | 48 | 1 | 59 | 59 | 1 | 108 | (48/49) = 0.98 | (1/108) = 0.01 |
| DDSM | 46 ∗ 2 = 92 | 89 | 3 | 94 | 89 | 5 | 140 | (89/92) = 0.97 | (5/140) = 0.03 | |
| Normal vs malignant | MIAS | 49 ∗ 4 = 196 | 192 | 4 | 273 | 259 | 14 | 256 | (192/196) = 0.98 | (14/256) = 0.05 |
| DDSM | 46 ∗ 4 = 184 | 182 | 2 | 1203 | 1167 | 36 | 146 | (182/184) = 0.99 | (36/146) = 0.25 | |
| TMCH: Scanner1 | 107 ∗ 4 = 428 | 424 | 4 | 605 | 593 | 12 | 217 | (424/428) = 0.99 | (12/217) = 0.05 | |
| TMCH: Scanner2 | 65 ∗ 4 = 260 | 260 | 0 | 232 | 232 | 0 | 135 | (260/260) = 1.00 | (0/135) = 0 | |
∗Augmentation of image.