Brain Tumor Detection and Classification from MRI Scans Using Deep Convolutional Neural Networks

DOI

10.2991/978-94-6239-713-2_3How to use a DOI?

Keywords

Explainable AI; convolutional neural networks; MRI images; deep learning; Grad CAM

Abstract

Detection of tumors in brain from Magnetic Resonance Imaging (MRI) plays a vital role in both planning and diagnosis for the treatment. Examining these MRI images manually takes a lot of time and it depends upon the experience of the observer. This drawback motivated the significance of automated detection systems. This project presented a deep learning framework with the help of convolutional neural networks (CNN) to detect the tumors accurately and in a precise manner. The system learns features from MRI scans and improve the performance. To improve the overall capability, a multi task based learning approach is introduced which performs both tumor segmentation and tumor detection in the same model. Addition to this, a module called Explainable AI using Grad CAM is integrated into the system which gives the visual representation in the form of heat maps as the output. This method helps to develop trust on the system and improves reliability of the entire model. Experimental results describe that this model has performed well as it proved the F1 score greater than 0.91, Dice score more than 0.89 and Area Under Curve (AUC) values near to 0.98. However, the proposed model requires some more work in order to be a real viable solution in real world application Overall, this proposed system proves high accuracy, efficiency, interpretability for the automatic tumor detection and classification.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Neelam Mary Vijaya Nirmala
AU  - Kommineni Prathima
AU  - Myla Vinaya Sri
AU  - Papani Sri Lakshmi
AU  - Pasam Aparna
PY  - 2026
DA  - 2026/06/25
TI  - Brain Tumor Detection and Classification from MRI Scans Using Deep Convolutional Neural Networks
BT  - Proceedings of the International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026)
PB  - Atlantis Press
SP  - 40
EP  - 50
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-713-2_3
DO  - 10.2991/978-94-6239-713-2_3
ID  - Nirmala2026
ER  -