Table 9.
Methods | Accuracy | Sensitivity | Specificity | AUC |
---|---|---|---|---|
3D-FCN | 0.8975 | 0.8261 | 0.9295 | 0.9027 |
MRCNN | 0.9162 | 0.8487 | 0.9371 | 0.9173 |
3D-UNET | 0.9176 | 0.8516 | 0.9394 | 0.9259 |
PRN-HSN | 0.9286 | 0.8782 | 0.9430 | 0.9371 |
DCNN | 0.9170 | 0.8496 | 0.9388 | 0.9195 |
CLAHE-SVM | 0.9251 | 0.8672 | 0.9415 | 0.9328 |
Mask-RCNN | 0.9291 | 0.8806 | 0.9447 | 0.9396 |
proposed | 0.9390 | 0.8988 | 0.9476 | 0.9615 |