Brain Region Segmentation using CNN

Abstract

An important problem in medical image analysis is the segmentation of anatomical regions of interest. Once regions of interest are segmented, helps radiologists extract shape, appearance and other structural features that can be analyzed for disease diagnosis or treatment evaluation. Many segmentation techniques such as mean shift, region growing, water shed, graph cuts, fuzzy connectivity etc. are available for medical imaging especially for brain MRI. In our work, a fully automated system for brain region segmentation by using Human intelligence based deep learning technique is proposed. Deep learning technique is most popular state of the art method in recent applications. There are two stages pre-processing and segmentation via Convolutional Neural Network CNN.The MRI image with noise is used as an input image. MRI images are collected from publicly available database Open Access Series of Image Studies (OASIS). Three layers are used in this network, which is used to segment the brain region.