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Deep Learning in Neuroimaging: A Comparative Analysis of Models for Brain Tumor Classification using MRI Images

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Comparative analysis reveals ResNet18 excels in brain tumor classification, suggesting its potential in neuroimaging.

ResNet18 achieved the highest classification accuracy of 93.50%, surpassing other models in brain tumor detection.
Among the models tested, ResNet18 showed improved generalization for various tumor classifications, aiding diagnostic processes.
A dataset of 6,056 labeled MRI images was employed to train and assess the performance of different deep learning models.
The findings suggest that deep learning models, particularly ResNet18, can significantly enhance the accuracy of automated neuro-oncological diagnosis.

Alok Tripathi (2025) studied this question.

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