Table 1 The review on the previous research works.
From: Comprehensive brain tumour concealment utilizing peak valley filtering and deeplab segmentation
Citations | Research work perfomed | Approach followed | Performance metrics |
|---|---|---|---|
| Â | 3D Variational segmentation | Accuracy 89.4% | |
| Â | Graph cut (tumor and edema seg.) | Accuracy 87.8% | |
BTS | Review of deep learning methods | – | |
BTS | Review of AI techniques | − | |
BTSC | Deep learning with optimization techniques | Sensitivity93.1% specificity 95.6%, prediction error 5.5% | |
BTS | Review of deep learning applications | Dice score 0,89%,iou 0.82 | |
BTSC | Deep learning with optimization techniques | Sensitivity 94.3, specificity 96.2, prediction error 4.9% | |
BTSC | Hierarchical DNN | AUC 0.91% | |
BTSC | DL with optimization techniques | Dice similarity coefficient 0.90 | |
BTSC | DCNNs | Precision 94.1%,recall 93.7%, dice 0.92 similarity coefficient | |
Review of cancer detection methods | Review of ML and DL models | Specificity 95, sensitivity 94.6, F-score95.2 , precision 94.8 | |
BTSC | U-Net based segmentation | Accuracy 91.2 |
