Detection and classification of tumor in brain using visual geometry group

Now a day’s brain tumor detection is an important matter in computer aided diagnosis for medical applications. The classification process and plays vital role to the tumors. existing method concentrates on detection, features extraction classification. Though traditional Algorithms suffered from less accuracy takes more time execution. To enhance premature stage classification, main intension of this paper extract features, using VGG-16 Architecture. By we achieved maximum 99%, minimum loss, execution,F1 score, sensitivity etc., as compare CNN, execution collected data kaggle dataset, Brain MRI images 2065 patients, out which 1445 are cancerous 620 non cancerous.