Glioma Detection Using Deep and Transfer Learning

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This analysis demonstrates deep learning-based glioma classification using MRI scans, highlighting improvements over traditional methods.

Deep learning systems improved glioma detection accuracy, significantly outperforming traditional methods.
EfficientNetB2 demonstrated higher accuracy compared to MaxViT in distinguishing glioma grades using MRI images.
The established model analyzes a substantial dataset of 33,400 MRI images to support better diagnosis.
Integrating deep learning with MRI analysis could lead to more effective tools for clinicians in brain tumor detection.

Keerthi et al. (2025) studied this question.

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