Multi-resolution MRI Brain Image Segmentation Based on Morphological Pyramid and Fuzzy C-mean Clustering

Abstract

Image segmentation is a vital step in many imaging applications, such as medical images and computer vision. Image segmentation is considered as a challenging problem, so we need to develop an efficient, fast technique for medical image segmentation. In this paper, we propose a new system for a multi-resolution MRI brain image segmentation, which is based on a morphological pyramid with fuzzy C-mean (FCM) clustering. In the first stage, we use a wavelet multi-resolution to maintain spatial context between pixels. Secondly, we use the morphological pyramid to fuse the resulting multi-resolution images with the original image to increase sharpness and decrease noise in the processed image. Finally, we use FCM technique to segment the processed images. We compared our proposed system with some state of the art segmentation techniques on two different brain data sets. Experimental results showed that the proposed system improves the accuracy of the MRI brain image segmentation.