July 6, 2025Deleted Journal

Implementation of Deep Learning for Brain Tumor Classification from Magnetic Resonance Imaging

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This analysis employs deep learning techniques to improve brain tumor classification from MRI, highlighting the effectiveness of MobileNetV2.

MobileNetV2 model achieved the highest accuracy of 88.77% in classifying brain tumors.
Using 4600 MRI images, the study focused on identifying two classes: brain tumor and health.
The research utilized transfer learning with four models, including MobileNetV2 for improved outcomes.
Results suggest deep learning methods may offer advanced solutions for medical image classification.

Husna et al. (2025) studied this question.

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This analysis employs deep learning techniques to improve brain tumor classification from MRI, highlighting the effectiveness of MobileNetV2.