Brain Tumor Detection Using Deep Learning

Abstract

Abstract: This paper explores the application of deep learning in detecting brain tumors through the comparison of ResNet50 and VGG19 classification models. The study also includes the comparison of Res-U-Net and U-Net models for tumor segmentation. The process involves feeding an input of Brain MRI scan into the classification model, which provides two outputs: detection of the tumor or confirmation of the patient's health. If a tumor is detected, the segmentation model locates it at a pixel level. The proposed approach has the potential to improve the accuracy and speed of brain tumor diagnosis, which could lead to more effective treatment.