Machine Learning Based Brain Tumor Detection and Classification Using MRI Scans with Convolutional Neural Networks

This research paper delves into the exploration of creating and implementing a sophisticated training model tailored for brain tumor classification. The model's backbone is Convolutional Neural Network (CNN) architecture, chosen for its proven efficiency in image classification tasks. The CNN is constructed to efficiently process and analyze brain tumor images. A carefully selected dataset of various brain tumor images is used for prolonged training in order to guarantee the accuracy and generalizability of the model. And the study goes beyond model development by seamlessly integrating the trained CNN into a user-friendly Flask web application. This integration enables clinicians and users to conveniently upload MRI scans in real-time and receive instant predictions regarding the presence of brain tumors. This work makes a substantial contribution to the fields of neuroimaging and healthcare diagnostics by bridging the gap between state-of-the-art deep learning technology and useful medical applications.