Automated segmentation of multiple sclerosis lesions in multispectral MR imaging using fuzzy clustering

A method is presented for fully automated detection of Multiple Sclerosis ( MS) lesions in multispectral magnetic resonance (MR) imaging. Based on the Fuzzy C-Means (FCM) algorithm, the method starts with a segmentation of an MR image to extract an external CSF/lesions mask, preceded by a local image contrast enhancement procedure. This binary mask is then superimposed on t he corresponding data set yielding an image containing only CSF structures and lesions. The FCM is then reapplied to this masked image to obtain a mas k of lesions and some undesired substructures which are removed using anato mical knowledge. Any lesion size found to be less than an input bound is el iminated from consideration. Results are presented for test runs of the met hod on 10 patients. Finally, the potential of the method as well as its lim itations are discussed. (C) 2000 Elsevier Science Ltd. All rights reserved.