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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 9, SEPTEMBER 2025

AI-Powered Early Detection of Brain Tumours Using Medical Imaging

Subrahmanya, Nithish Pai B N, Priyanka Arjun

DOI: 10.17148/IJARCCE.2025.14906

Abstract: Brain tumours are often considered one of the most aggressive types of cancer. Historically, they were identified using conventional deep learning methods via MRI. Currently, studies are transitioning to advanced models that can analyse MRI scans to identify and classify tumours. Tumours are formed by abnormal cell growth in brain tissue and can be benign or malignant. Since treatment effectiveness and survival rates can be improved with early identification, this paper focuses on supervised learning approaches, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), to provide better and faster early detection.

Keywords: Brain tumour, Convolutional Neural Network, Recurrent Neural Network, Deep learning, Magnetic Resource Imaging (MRI), Artificial Intelligence, Medical Imaging, Early Detection, Tumour Classification.

How to Cite:

[1] Subrahmanya, Nithish Pai B N, Priyanka Arjun, “AI-Powered Early Detection of Brain Tumours Using Medical Imaging,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14906