Multi-scale based Network and Adaptive EfficientnetB7 with ASPP: Analysis of Novel Brain Tumor Segmentation and Classification

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Novel deep learning model improves segmentation and classification of brain tumors in MRI images, indicating enhanced diagnostic accuracy.

The proposed model achieves a classification accuracy of 98.2%, significantly outperforming conventional approaches.
The Multiscale Bilateral Awareness Network segments abnormal regions in MRI images, improving feature representation.
The Region Vision Transformer-based Adaptive EfficientNetB7 with Atrous Spatial Pyramid Pooling enhances classification reliability.
Hyperparameter optimization via the MRP-HOA algorithm leads to improved accuracy and robustness of the model.

Kulkarni et al. (2025) studied this question.

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Novel deep learning model improves segmentation and classification of brain tumors in MRI images, indicating enhanced diagnostic accuracy.