Automated Brain Tumor Detection Using Convolutional Neural Networks on MRI Scans

This paper dives deep into how advanced machine learning methods can help find to brain tumors better, aiding doctors in diagnosing and planning treatment accurately. It talks about medical image like MRI scans, and explores various machine learning techniques from basic ones to more complex ones like deep learning. It discusses the literature review by focusing the method used to detect the brain tumor and their accuracies. Proposed method suggests the preprocessing of dataset collected from Kaggle platform and then apply DCCN to classify and detect four types of brain tumors. It also stresses how important it is for doctors to trust and understand these systems and talks about future research like sharing knowledge between different hospitals and combining different types of data. Overall, it's about making progress in finding brain tumors and helping patients better. The accuracy of suggested system is 97.24%.