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Multi-Modal Brain Tumor Diagnosis via Hybrid Vision Transformers and CNNs: A Deep Learning Approach

Authors :

Alireza Haghighatjoo¹ Fatemeh Noori² Peyman Afshari Bijarbaneh³ Seyed Amirhossein Mousavi⁴

1- دانشگاه آزاد اسلامی واحد مشهد 2- Genova University , italy 3- Genova University , italy 4- دانشگاه آزاد اسلامی واحد مشهد

Keywords :

Brain Tumor Segmentation،Deep Learning،Vision Transformer،3D ResNet،Medical Image Analysis

Abstract :

In this study, we propose a hybrid deep learning framework that integrates Convolutional Neural Networks (CNNs) with Vision Transformers (ViTs) for multimodal MRI-based brain tumor diagnosis. The model was trained and evaluated on public datasets, achieving higher accuracy and robustness compared to conventional CNN and ViT models. Our approach improved classification accuracy by 3–5% over recent state-of-the-art baselines. These findings suggest that hybrid architectures can effectively capture both local and global features, making them promising tools for reliable brain tumor diagnosis.

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