Brain Tumor detection from MRI scans using VGG- 19 networks

In the planning and quantitative assessment of brain tumors, determining the tumor extent is a critical challenge. MRI is a non-invasive technology that has emerged as a first-line diagnostic tool for brain tumors that does not require ionizing radiation. Gliomas are the most aggressive brain tumors, with a life expectancy of only a few months in the most advanced stages. Manual segmentation is a time-consuming procedure in clinical practice, and its success is greatly dependent on the operator's expertise. Hence, our paper aims to develop a system wherein it takes in the MRI scan images as input and classifies if the specific patient has Brain Tumor or not using the VGG-19 architecture of Convolutional Neural Networks.