Advances, Systems and Applications
From: Feature-enhanced fusion of U-NET-based improved brain tumor images segmentation
Model | Filter | Balanced Accuracy | F1 Score | Cohen's Kappa | Precision | Recall | Jaccard Index | ROC AUC |
---|---|---|---|---|---|---|---|---|
UNET | CLAHE | 0.9808 | 0.9735 | 0.9646 | 0.9735 | 0.9735 | 0.9483 | 0.9823 |
FE1-UT | 0.9864 | 0.9819 | 0.9758 | 0.9819 | 0.9818 | 0.9644 | 0.9879 | |
UNET | MBOBHE | 0.9828 | 0.977 | 0.9693 | 0.977 | 0.977 | 0.955 | 0.9846 |
FE2-UT | 0.9853 | 0.9798 | 0.9731 | 0.9798 | 0.9798 | 0.9604 | 0.986 | |
UNET | MPHE | 0.9842 | 0.978 | 0.9706 | 0.978 | 0.978 | 0.9569 | 0.9853 |
FE3-UT | 0.9842 | 0.9785 | 0.9713 | 0.9785 | 0.9785 | 0.9578 | 0.9856 |