Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 9 No 11 (2025): Volume 9, Issue 11, November 2025 | Pages: 399-407
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 26-11-2025
This research develops an automated system for brain tumor detection and classification using MRI images and Machine Learning in MATLAB. To address data limitations, we implement augmentation techniques to enhance dataset robustness. A novel hybrid model is designed, integrating convolutional neural networks for feature extraction with support vector machines for classification. The proposed approach is rigorously evaluated against existing methods using precision, recall, and F1-score metrics. Results demonstrate that our hybrid model achieves superior performance in both detection accuracy and classification reliability. This work provides a effective framework for computer-aided diagnosis, potentially assisting radiologists in clinical decision-making and improving patient outcomes through early and accurate tumor identification.
Brain Tumor Classification, MRI Analysis, Hybrid Model (CNNSVM), MATLAB Implementation, Computer-Aided Diagnosis
Harjot Kaur, Er. Manpreet Singh, & Prof. Dr. Jagdeep Kaur. (2025). Brain Tumor Detection and Classification Using MRI Images and Machine Learning in MATLAB A - Review. International Research Journal of Innovations in Engineering and Technology - IRJIET, 9(11), 399-407 Article DOI https://doi.org/10.47001/IRJIET/2025.911045
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