Study on the Application of MRF and Fuzzy Clustering as Well as the D-S Theory to Image Fusion Segmentation of the Human Brain

The features of the spatial information of Markov random field image was used in image segmentation. It can effectively remove the noise, so that more accurate segmentation results can be obtained. And more satisfactory segmentation results can be achieved with the application of Fuzzy Clustering Theory together with Two-Dimensional Histogram image segmentation methods, However, these two ways leads to different classification results while classifying the controversial pixels in images, so we can use the Dempster-Shafer evidence theory to fuse multi-source information, to assign the controversial points to the plausibility interval, and then divide them. This paper will adopt the above three theories to propose a new human brain image segmentation method. Experimental result shows that the segmentation result is more in line with human vision, and is of vital significance to accurate analysis and application of tissues.