Leveraging Capsule Networks for Robust Brain Tumor Classification and Detection in MRI Scans

Sandeep Shiraskar, Simon Vellandurai, Dominick Rizk

2025

Abstract

Brain tumors are life-threatening conditions where early detection and accurate classification are critical for timely and effective treatment. Misclassification or delayed identification of tumors can result in fatal consequences. Current deep learning techniques, predominantly based on Convolutional Neural Networks (CNNs), have demonstrated success in tumor detection but face limitations due to their inability to handle diverse and extensive datasets effectively. Moreover, CNNs suffer from information loss in pooling layers, leading to suboptimal performance in capturing global dependencies in MRI tumor images. To overcome these challenges, we propose the use of a modified Capsule Network to address the limitations of CNNs. Capsule Networks retain spatial hierarchies and dependencies, enabling improved performance in tumor detection and classification tasks. Our approach achieves near-perfect classification accuracy across four classes—pituitary, glioma, meningioma, and no tumor—using a diverse and augmented dataset. The dataset comprises publicly available MRI images from Figshare, Sartaj, and Br35 collections, providing a robust platform for evaluating model performance. Experimental results demonstrate that our method not only achieves superior accuracy compared to existing techniques but also maintains its performance across a broader range of data. These findings highlight the potential of Capsule Networks as a reliable and effective solution for brain tumor classification tasks, paving the way for advancements in medical imaging and diagnostic technologies.

Paper Citation

in Harvard Style

Shiraskar S., Vellandurai S. and Rizk D. (2025). Leveraging Capsule Networks for Robust Brain Tumor Classification and Detection in MRI Scans. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 1288-1296. DOI: 10.5220/0013323000003890

in Bibtex Style

@conference{icaart25,
author={Sandeep Shiraskar and Simon Vellandurai and Dominick Rizk},
title={Leveraging Capsule Networks for Robust Brain Tumor Classification and Detection in MRI Scans},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={1288-1296},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013323000003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Leveraging Capsule Networks for Robust Brain Tumor Classification and Detection in MRI Scans
SN - 978-989-758-737-5
AU - Shiraskar S.
AU - Vellandurai S.
AU - Rizk D.
PY - 2025
SP - 1288
EP - 1296
DO - 10.5220/0013323000003890
PB - SciTePress