International Journal of Advanced Research in Computer and Communication Engineering

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

Downloads: | DOI: 10.17148/IJARCCE.2025.14741