Enhanced Brain Tumour Detection and Classification through Sophisticated Machine Learning Approaches

Y. Sujitha, S. Rathnamahi, K. Sheshadri Ramana, N. Divya Sree, B. Sai Eswara Neha, P. Suniya Begum

2025

Abstract

If not treated, brain tumors pose a significant health risk. Detected and promptly treated. MRI examinations manual, but improved tumor detection Time-consuming and error-prone diagnosis prone. Deep learning will be used in this study. Methods, in particular Convolutional Neural Networks (CNNs), to boost precision and effectiveness in detecting brain tumors. The dataset of 7,023 MRI images is used in the research. From a variety of sources, such as Figshare, Br35H and SARTAJ. Preprocessing techniques like normalization, image resizing, and noise cancellation were used to improving the performance of a model. It was made a CNN model. Using TensorFlow and GPU training acceleration. Data-based additional techniques augmentation, adjusting the rate of learning, and making use of the Adam optimizer with a beta value made accuracy even better Callbacks such as Early Stopping and ReduceLR on Plateau were incorporated to prevent overfitting and ensure a stable training process. The machine learning model successfully divided brain tumors into four groups, achieving a remarkable accuracy of 99.54 percent. This demonstrates how effective deep learning in medical imaging and its potential as an accurate diagnostic instrument. The model makes use of important libraries like TensorFlow, Keras, Pandas and NumPy.

Paper Citation

in Harvard Style

Sujitha Y., Rathnamahi S., Ramana K., Sree N., Neha B. and Begum P. (2025). Enhanced Brain Tumour Detection and Classification through Sophisticated Machine Learning Approaches. 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 476-482. DOI: 10.5220/0013900200004919

in Bibtex Style

@conference{icrdicct`2525,
author={Y. Sujitha and S. Rathnamahi and K. Ramana and N. Sree and B. Neha and P. Begum},
title={Enhanced Brain Tumour Detection and Classification through Sophisticated Machine Learning Approaches},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={476-482},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013900200004919},
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 - Enhanced Brain Tumour Detection and Classification through Sophisticated Machine Learning Approaches
SN - 978-989-758-777-1
AU - Sujitha Y.
AU - Rathnamahi S.
AU - Ramana K.
AU - Sree N.
AU - Neha B.
AU - Begum P.
PY - 2025
SP - 476
EP - 482
DO - 10.5220/0013900200004919
PB - SciTePress