Deep Learning-Based Brain Tumor Classification Using CNNs on MRI Scans

Author(s)	Ms. Deborah Jestin
Country	India
Abstract	Brain tumors are a critical health issue requiring accurate and early diagnosis for effective treatment. Magnetic Resonance Imaging (MRI) provides detailed brain images that can be leveraged by deep learning techniques for tumor detection. In this paper, We propose a Convolutional Neural Network (CNN)-based approach for classifying brain MRI images into tumor and non-tumor categories. The model is trained on a publicly available dataset, achieving a validation accuracy of up to 99% and a testing accuracy of 100%. We also present visual insights using performance plots, a confusion matrix, and a Receiver Operating Characteristic (ROC) curve. Our findings demonstrate the potential of CNNs in assisting radiologists with efficient brain tumor diagnosis.
Keywords	Brain Tumor Classification, Convolutional Neural Network, Magnetic Resonance Imaging
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-09
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.41106
Short DOI	https://doi.org/g9fccn

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International Journal For Multidisciplinary Research