| ALGORITHM | TP | TN | FP | FN | Accuracy | Sensitivity | Specificity | PPV | NPV |
Input Image 1 | Legendre ROI | 46.933 | 49.217 | 3.066 | 0.782 | 96.151 | 0.9836 | 0.94135 | 0.93867 | 0.98435 |
Zernike ROI | 43.988 | 48.466 | 6.011 | 1.533 | 92.454 | 0.96631 | 0.88965 | 0.87977 | 0.96932 | |
Racah ROI | 47.430 | 49.344 | 2.569 | 0.655 | 96.775 | 0.98637 | 0.95051 | 0.94861 | 0.98689 | |
Legendre WS | 44.357 | 48.103 | 5.643 | 1.896 | 92.460 | 0.95899 | 0.89501 | 0.88714 | 0.96206 | |
Zernike WS | 20.652 | 40.134 | 29.347 | 9.865 | 60.787 | 0.67674 | 0.57762 | 0.41304 | 0.8027 | |
Racah WS | 39.489 | 46.467 | 10.510 | 3.533 | 85.956 | 0.91788 | 0.81553 | 0.78979 | 0.92934 | |
Input Image 2 | Legendre ROI | 45.844 | 48.967 | 4.156 | 1.032 | 94.811 | 0.97798 | 0.92177 | 0.91688 | 0.97935 |
Zernike ROI | 49.374 | 49.844 | 0.6254 | 0.155 | 99.219 | 0.99686 | 0.98761 | 0.98749 | 0.99689 | |
Racah ROI | 45.860 | 48.971 | 4.139 | 1.028 | 94.832 | 0.97807 | 0.92206 | 0.91721 | 0.97943 | |
Legendre WS | 46.428 | 48.827 | 3.571 | 1.172 | 95.255 | 0.97536 | 0.93184 | 0.92857 | 0.97654 | |
Zernike WS | 24.652 | 41.676 | 25.347 | 8.323 | 66.329 | 0.74759 | .062181 | 0.49305 | 0.83354 | |
Racah Watershed | 41.255 | 47.128 | 8.744 | 2.871 | 88.384 | 0.93493 | 0.84349 | 0.82511 | 0.94257 |