Brain Tumour Detection on BraTS 2020 Using U-Net

Abstract

Main objective of this framework is to build a efficient deep learning model to detect the brain tumor. In this paper, the framework mainly focuses on the detection of brain tumor MRI images from the BraTS2020 dataset which is a part of the MICCAI BraTS2020 challenge, using U-Net architecture which is suitable for quick and accurate image classification and achieved a training accuracy of 98.485%. When compared to other architectures on BraTs2020 dataset, U-Net architecure with customization provides better results.