Automated Detection and Prediction of Brain Tumor using ML

This research study focuses on developing an advanced machine learning system for the accurate classification of brain tumors using MRI scans. Traditional manual diagnosis consumes more time in deciding the type of brain tumor as there are very little changes in every type. Utilizing computer vision’s feature extraction techniques, including texture analysis and shape characterization, the proposed system aims to differentiate between various tumor types such as meningioma, glioma, pituitary, and non-tumor cases. The models used to validate the accuracy of the brain tumor classification system are Logistic Regression, Convolution Neural Network (CNN), and Visual Geometry Group(VGG), which are simple yet effective way to train and deploy in the radiology system to enhance diagnostic accuracy in neurooncology, and improve patient outcomes.