Fusing fuzzy and probabilistic memberships for white matter lesion detection in MRI of the brain

Computerized tools for automated detection of white matter lesions of the brain in magnetic resonance imaging are very useful for neuroscience researchers to enhance the study of brain-related diseases and their causal associations with other risk factors. We introduce in this paper a fusion approach for identifying white matter lesions in elderly subjects with structural brain tissue changes. The detection methodology is based on image segmentation methods and probabilistic models for membership assignments and fusion. Experimental results on image data of patients show the effectiveness of the proposed approach in comparisons with other detection models.