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

Author

Dou, Weiber ; Ruan, Su ; Liao, Qingmiri ; Bloyet, Daniel ; Constans, Jean-marc

Author_Institution

Lab. GREYC, CNRS, Caen, France

Volume

1

fYear

2003

fDate

1-4 July 2003

Firstpage

681

Abstract

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.

Keywords

biomedical MRI; brain; feature extraction; fuzzy set theory; image classification; medical image processing; radiology; sensor fusion; tumours; data matching; fuzzy classification; fuzzy information fusion method; human brain; multispectral magnetic resonance images; proton density feature images; radiology; three dimension space; tissues; tumor area; Biomedical equipment; Data mining; Fuzzy sets; Humans; Image analysis; Image sequences; Magnetic resonance imaging; Medical services; Neoplasms; Radiology;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on

Print_ISBN

0-7803-7946-2

Type

conf

DOI

10.1109/ISSPA.2003.1224795

Filename

1224795