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 | 0.9890 | 0.9869 | 0.9826 | 0.9872 | 0.9867 | 0.9742 | 0.9912 |
FE1-UT | 0.9966 | 0.9964 | 0.9952 | 0.9966 | 0.9962 | 0.9928 | 0.9975 | |
UNET | MBOBHE | 0.9967 | 0.9956 | 0.9942 | 0.9956 | 0.9956 | 0.9913 | 0.9971 |
FE2-UT | 0.9449 | 0.9242 | 0.9006 | 0.9738 | 0.8794 | 0.8591 | 0.9358 | |
UNET | MPHE | 0.5544 | 0.2545 | 0.1873 | 1.0 | 0.1458 | 0.1458 | 0.5729 |
FE3-UT | 0.5544 | 0.2545 | 0.2038 | 1.0 | 0.1458 | 0.1458 | 0.5729 |