Review on Brain Tumor Segmentation Methods using Convolution Neural Network for MRI Images

An efficient and timely detection of brain tumors will aid the better treatment selections and improves the survival rate of the patients. The segmentation processes of Magnetic resonance images (MRI) play a crucial role in detecting brain tumors. Since the large amounts of MRI images are generated during the cancer diagnosis, manual image segmentation will be a tedious job due to time constraints. An automatic image segmentation processes can alleviate the former limitation. There are various algorithms used to segment the images automatically, in which the deep learning technique is more efficiently used for large amount of images to find the size and location of a cancer. Enormous review papers have been published to give insight on MRI-based image segmentation. Our review is focused on Convolutional Neural Network (CNN) based deep learning algorithm, as it gives better accuracy in image recognition problems.