MRI Image Analysis for Brain Tumor Segmentation Using Convolutional Neural Network

Abstract

In medical imaging, the analysis of Brain Tumor Segmentation is one of the most challenging Problems. To reduce the death rate, the defects in the region of a Human Brain should be reported immediately. The segmentation of the abnormal region helps to monitor and plan the treatment. Isolating normal and abnormal tissues is a critical step in Segmentation. Magnetic Resonance Imaging (MRI) is a widely used, noninvasive modality for early diagnosis of Brain abnormalities. Several Deep Learning based methods have been applied to Brain Tumor Segmentation and achieved promising results. Deep Learning techniques such as the Convolutional Neural Network (CNN) are used to obtain the best results in Brain Tumor Segmentation. The building blocks of CNN algorithms are specifically designed for image segmentation tasks. Looking ahead, Deep Learning-based Brain Tumor Segmentation holds significant potential to revolutionize the diagnosis and treatment of Brain Tumors, paving the way for more accurate and personalized healthcare solutions.