Table 4.
Number of ROIs resulted in FP reduction using curvelet-based LBP (without sparse) & 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 | 203 | 13 | 273 | 257 | 16 | 315 | (203/216) = 0.94 | (16/315) = 0.05 |
| DDSM | 140 ∗ 4 = 560 | 465 | 95 | 1203 | 1095 | 108 | 240 | (465/560) = 0.83 | (108/240) = 0.45 | |
|
| ||||||||||
| Benign vs malignant | MIAS | 49 | 49 | 0 | 59 | 57 | 2 | 108 | (49/49) = 1.00 | (2/108) = 0.02 |
| DDSM | 46 ∗ 2 = 92 | 91 | 1 | 94 | 91 | 3 | 140 | (91/92) = 0.99 | (3/140) = 0.02 | |
|
| ||||||||||
| Normal vs malignant | MIAS | 49 ∗ 4 = 196 | 184 | 12 | 273 | 254 | 19 | 256 | (184/196) = 0.94 | (19/256) = 0.07 |
| DDSM | 46 ∗ 4 = 184 | 180 | 4 | 1203 | 1143 | 60 | 146 | (180/184) = 0.98 | (60/146) = 0.41 | |
| TMCH: Scanner1 | 107 ∗ 4 = 428 | 416 | 12 | 605 | 551 | 54 | 217 | (416/428) = 0.97 | (54/217) = 0.25 | |
| TMCH: Scanner2 | 65 ∗ 4 = 260 | 255 | 5 | 232 | 214 | 18 | 135 | (255/260) = 0.98 | (18/135) = 0.13 | |
∗Augmentation of image.