Segmentation of multiple sclerosis lesions based on D-S evidence theory
基于D-S证据理论的多发性硬化症病灶分割算法*

Multiple sclerosis (MS) is an inflammatory demyelinating disease that would damage central nervous system. There was a growing attention to the segmentation algorithms of MS lesions. This paper developed an automatic algorithm for MS lesions segmentation by utilizing the fusion T1 and T2-weighted MR brain images based on D-S evidence theory and FCM clustering algorithm. First, segmented T1 and T2-weighted MR brain images by a FCM clustering algorithm. Then fused the resultant images according to the joint mass of T1 and T2-weighted MR brain images to produce the segmentation of MS lesions. The testing experiments on MR brain images show that the proposed algorithm is able to improve the segmentation accuracy, which is important to assist the diagnosis of MS in clinic.