DEVELOPMENT OF A NEW DATA FUSION SYSTEM FOR SEGMENTATION OF MR IMAGES

Abstract

In this research paper, we propose an automatic segmentation method of multispectral magnetic resonance image (MRI) of the human brain using an information fusion approach through the framework of the possibility theory. The fusion process is summarized into three essential steps. First, a data is extracted from the various images and modeled in a common mathematical framework, in this step the fuzzy C-means (FCM) algorithm is chosen. The combination rule is used to combine this information in the second step. A final segmented image is the result of the last phase. Our experimental results using simulated brain MRI datasets show that the proposed approach overcome the impact of the noise and substantially improve the accuracy of image segmentation.