Abstract: Brain tumors are among the most lethal and challenging diseases to diagnose and treat. Early detection and accurate classification are crucial for effective treatment planning and improving patient outcomes. This project focuses on developing a system for the detection and classification of brain tumors using Convolutional Neural Networks (CNNs). Utilizing MRI images, our model aims to differentiate between various types of brain tumors, offering a non-invasive and efficient diagnostic tool. The system is trained on a labeled dataset, and the CNN architecture is optimized for high accuracy in classification.

Keywords: Brain Tumor, MRI, CNN, Machine Learning, Image Classification, Medical Imaging.

| DOI: 10.17148/IARJSET.2024.11820