Brain Tumor MRI Classification Using Hybrid Model

• Implementation and evaluation of NeuroVision, a ResNet-
18 + Transformer-encoder hybrid, for four-class brain tu-
mor MRI classification, using genuine ImageNet transfer
learning for the CNN backbone.
• A controlled, within-notebook comparison against a fine-
tuned ResNet-18-only baseline trained with identical data
splits, optimizer, and hyperparameters.
• Identification and correction of a shared-dataset
transform-aliasing defect in the data pipeline, with a
description of the corrected implementation.
• A positioning of the results against recent (2026) open-
access literature on CNN, wavelet-enhanced CNN, Vision
Transformer, and 3D volumetric methods for brain tumor
MRI analysis.