Research Article
Superlative Feature Selection Based Image Classification Using Deep Learning in Medical Imaging
| Article | Year | Model | Classification classes | Data size |
| [29] | 2020 | VGG-16 and VGG-19 | T1, T1CE, T2, and Flair | 75 low-grade gliomas and 210 high-grade gliomas | [30] | 2019 | VGG-19 | Glioma grades | 3064 images of 233 patients | [31] | 2019 | 2D CNN with genetic algorithm | (Meningioma, glioma, and pituitary) and (glioma grades) | 600 MRI images | [32] | 2019 | Customized CNN | Tumor or normal | 330 MRI images | [33] | 2019 | ResNet34 | Tumor or normal | 48 3D images | [34] | 2019 | Customized CNN | Glioblastoma, metastatic bronchogenic, and sarcoma | 66 MRI images | [35] | 2018 | VGG-16 | Classification of brain tumor type | 43 3D images |
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