Table 5.
Performance evaluation of existing state-of-the-art models and the proposed model.
| Study | Year | Model | Dataset | Image modalities | Number of classes | Number of images | Performance | XAI |
|---|---|---|---|---|---|---|---|---|
| Choudhury et al.50 | 2020 | CNN |
Brain tumor Kaggle dataset |
MRI | 2 | – |
Accuracy: 96.08% Precision: 94.87% Recall: 98.63% F1-score: 97.36% |
Not used |
| Saleh et al.22 | 2020 |
Pre-trained DL models |
Brain tumor Kaggle dataset |
MRI | 4 | 4480 |
Accuracy: 97.25-98.75% Precision: – Recall: – F1-score: 100% |
Not used |
| Bhanothu et al.51 | 2020 | Faster R-CNN |
Brain tumor Figshare dataset |
MRI | 3 | 2406 |
Accuracy: – Precision: 77.6% Recall: 80% F1-score: – |
Not used |
| Waghmare et al.52 | 2021 |
fine-tuned VGG-16 CNN |
Brain tumor Kaggle dataset |
MRI | 3 | 3664 |
Accuracy: 95.71% Precision: – Recall: 83.28% F1-score: – |
Not used |
| Díaz-Pernas et al.17 | 2021 | DCNN | BRATS 2013 | MRI | 3 | 3064 |
Accuracy: 97.3% Precision: – Recall: F1-score: |
Not used |
| Khairandish et al.53 | 2022 | CNN-SVM | BRATS 2015 | MRI | 2 | 230 |
Accuracy: 98.49% Precision: – Recall: – F1-score: – |
Not used |
| Mohan et al.54 | 2022 | DLBTDC-MRI |
BRATS2015 dataset |
MRI | 4 | 42,470 |
Accuracy: 98.145% Precision: 95.134% Recall: 97.348% F1-score: 96.25% |
Not used |
| Srinivas et al.55 | 2022 | VGG-16 |
Kaggle dataset |
MRI | 2 | 256 |
Accuracy: 96% Precision: 94% Recall: 100% F1-score: 98% |
Not used |
| Montaha et al.56 | 2022 | TD-CNN-LSTM |
BraTS 2018, BraTS 2019 and BraTS 2020 |
MRI | 2 | 978 |
Accuracy: 98.90% Precision: 98.95% Recall: 98.78% F1-score: 98.83% |
Not used |
| Hossain et al.24 | 2022 | ResNet50 |
TGCA-GBM dataset |
MRI and CT scans |
3 | 3064 |
Accuracy: 98.96% Precision: 98.67% Recall: 99.12% F1-score: 98.87% |
Not used |
| Vankdothu et. al.15 | 2022 | CNN-LSTM |
Brain tumor kaggle dataset |
MRI | 4 | 3264 |
Accuracy: 92% Precision: 96% Recall: 98.5% F1-score: – |
Not used |
| Rasheed et al.57 | 2023 | CNN |
Brain tumor Kaggle dataset |
MRI | 3 | 3064 |
Accuracy: 98.04% Precision: 98% Recall: 98% F1-score: 98% |
Not used |
| Abdusalomov et al.58 | 2023 | YOLOv7 |
Brain tumor Kaggle dataset |
MRI | 4 | 10,288 |
Accuracy: 99.5% Precision: 99.5% Recall: 99.3% F1-score: 99.4% |
Not used |
| Meena, Gaurav, et al.21 | 2024 | InceptionV3 | kaggle | – | 2 | 228 |
Accuracy: 98% Precision: – Recall: – F1-score: – |
Not used |
| BrTMHD-2023 | MRI | 2 | 1166 |
Accuracy: 98.97% Precision: 97% Recall: 97% F1-score: 97% |
Used | |||
| Proposed study | 2024 | ViT-GRU | Brain Tumor Kaggle Dataset | MRI | 2 | 256 |
Accuracy: 96.08% Precision: 97% Recall: 96% F1-score: 96% |
Not used |