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This study investigates the use of an ensemble of vision transformer (ViT) models for the automated classification of brain tumors from T1-weighted magnetic resonance imaging (MRI). The ensemble achieved an overall testing accuracy of 98.7% on a dataset of 3064 MRI slices, outperforming individual models. The findings suggest that ViT models could significantly aid radiologists in diagnosing brain tumors, enhancing decision-making processes.

Author

Linh Đào

Language

EN