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To resolve the difficult problem of soft tissue segmentation of MRI images of the segmentation of the multi target region of interest in the MRI images with complex targets and fuzzy boundary, this paper proposed a novel MRI image segmentation method, based on anisotropic diffusion and spatial fuzzy C-means clustering (SFCM). It preprocessed the images using the nonlinear and anisotropic diffusion, resolving the problem of weakening the image details while removing the noise. It designed space function combining with the neighborhood space, improving traditional FCM objective function. It used the spatial information of the image to achieve the accurate classification of every object in image was an effective solution to the isolated area correctly classified. After that, it obtained complete and continuous segmented regions. Finally, it utilized the fitting curve of histogram to initialize the classification number and the initial cluster centers, accelerating the algorithm iterative to the optimal solution, and also reducing the run time. The experiments show that the possibility of find a best solution is improved by introducing the method of MRI image segmentation method based on anisotropic diffusion and spatial FCM, so as to the processing of MRI images segmentation which has overlapped grayscale, discontinuous objects and fuzzy boundary. [ABSTRACT FROM AUTHOR]