MRI-Based Brain Tumor Detection and Classification Using Deep Learning

N. Malarvizhi, A. Divya, N. Sankar Ram, M. Saraswathi, Naveen Kumar R. J., M. Nalini

2025

Abstract

It is obvious that the detection and classification of brain tumors in the MRI scans is an important aspect of medical imaging and so is defected in diagnosis and treatment of medical issues. This work applies a Fully Convolutional Network (FCN) model towards automatic identification of brain tumors with MRI images from Kaggle dataset. The dataset is organized into training and testing folders which have subfolders that represent categories of tumors such as glioma, meningioma, pituitary tumors, and ‘no tumor’ for normal cases. This lets the FCN learn to not only detect the presence of a tumor, but also which specific type it is. The model is trained to process MRI images on a pixel-by-pixel basis, allowing for precise segmentation and classification of abnormal regions. In the event that the model detects a tumor, it will determine the tumor type based on the set of features that the model has learned for each category in the dataset. The model operates in a sequence of two stages: first, it classifies an MRI scan to be tumor-positive or tumor-negative; second, if the model detects the presence of a tumor, it classifies the tumor into one of the set categories. The model performs binary classification as well as multi-class classification. The proposed system will help to assist radiologists by providing a tool that is automated and reliable for brain tumor detection and classification, which, without doubt, simplifies the diagnostics process and improves the outcome.

Paper Citation

in Harvard Style

Malarvizhi N., Divya A., Ram N., Saraswathi M., J. N. and Nalini M. (2025). MRI-Based Brain Tumor Detection and Classification Using Deep Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 86-91. DOI: 10.5220/0013923200004919

in Bibtex Style

@conference{icrdicct`2525,
author={N. Malarvizhi and A. Divya and N. Ram and M. Saraswathi and Naveen J. and M. Nalini},
title={MRI-Based Brain Tumor Detection and Classification Using Deep Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={86-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013923200004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - MRI-Based Brain Tumor Detection and Classification Using Deep Learning
SN - 978-989-758-777-1
AU - Malarvizhi N.
AU - Divya A.
AU - Ram N.
AU - Saraswathi M.
AU - J. N.
AU - Nalini M.
PY - 2025
SP - 86
EP - 91
DO - 10.5220/0013923200004919
PB - SciTePress