An Analysis of Segmenting and Classifying Tumor Regions in MRI Images using CNN
Brain tumor extraction from Magnetic Resonance Imaging (MRI) is an important task in medical image processing. It is one of the difficult and time consuming tasks because the structural variability among the tumor is entirely different from normal images. Manual segmentation requires expert knowledge and it has very less accuracy. So, we need intelligent machine learning technique for automatic detection of brain tumor through magnetic resonance images. These reasons motivate our exploration through machine learning solution that exploits flexible and high capacity of Deep Neural Network (DNN).The deep learning architectures are performing very accurately and they gradually outperform previous state of the art classical machine learning algorithms. MRI sequence consists of four intratumoral structures like edema, necrotic, non enhancing and enhancing regions. The purpose of this paper is to provide detailed examination of segmenting brain tumor and their regions using deep learning methods in MRI sequences.