Tumor segmentation in brain MRI using a fuzzy approach with class center priors

This paper proposes a new fuzzy approach for automatic segmentation of normal and pathological brain MRI volumetric data sets. MRI is generally useful for brain tumor deduction because it provide more detailed information about its type, position, size. Brain tumor segmentation is the separation of different tumor tissues from normal brain tissue. In automatic brain segmentation MRI is a sophisticated tool for medical imaging. Fuzzy is used to segment all the tissues at the same time, and FCM algorithm is used to speed up tumor performances under and noisy and provide better accuracy and fast response. The result obtain from different segmentation by using fuzzy algorithm and comparing normal and pathological brain by automatic segmentation method.