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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 14, ISSUE 7, JULY 2025

Classification of Brain Tumours Using Deep Learning Techniques

Shalini Verma, Dr. Anita Pal

DOI: 10.17148/IJARCCE.2025.14741

Abstract: Brain tumours are potentially fatal anomalies in neural tissues that need to be identified quickly and properly classified in order to be treated. This study offers a deep learning and image processing framework for automated brain tumour detection. The study combines preprocessing, feature extraction, and classification into a single model by using convolutional neural networks (CNNs) to recognise and categorise different types of tumours from MRI scans. When compared to traditional machine learning techniques, experimental results show notable increases in accuracy. The suggested approach provides a dependable tool to help radiologists make clinical decisions more quickly, reduce human error, and aid in early diagnosis.

Keywords: Brain tumour, MRI, Deep Learning, CNN, Image Processing, Medical Diagnosis

How to Cite:

[1] Shalini Verma, Dr. Anita Pal, “Classification of Brain Tumours Using Deep Learning Techniques,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14741