Knowledge based fuzzy information fusion applied to classification of abnormal brain tissues from MRI

A fuzzy information fusion method is proposed in this paper. It can automatically classify abnormal tissues in human brain in a three dimension space from multispectral magnetic resonance images such as T1-weighted, T2-weighted and proton density feature images. It consists of four steps: data matching, information modelling, information fusion and fuzzy classification. Several fuzzy set definitions are proposed to describe the specific observation universal. The fuzzy information models of tumor area in human brain and the particular fuzzy relations that contribute to information fusion and classification are also established. Three MR image sequences of a patient are utilized as an example to show the method performances. The results are appreciated by experts in radiology.