Fuzzy inference systems in MR image processing-a review

Author

Yin, X.X. ; Ng, B.W.-H. ; Abbott, D. ; Jia, W. ; Ramamohanarao, K.

Author_Institution

Sch. of Electr. & Electron. Eng., Univ. of Adelaide, Adelaide, SA, Australia

fYear

2010

fDate

16-18 April 2010

Firstpage

19

Lastpage

22

Abstract

Fuzzy inference systems are of great interest to provide a consistent mathematical framework for the representation of imprecision in relation to objects, relationships, knowledge and aims, and are viewed as powerful tools for reasoning and decision-making. In this paper, we survey several fuzzy approaches in magnetic resonances image processing, with an aim to develop and validate multidimensional segmentation and filtering methodology for future research. We also briefly review a number of advances of fuzzy set theory in the MR image processing application domain.

Keywords

biomedical MRI; decision support systems; filtering theory; fuzzy set theory; image segmentation; inference mechanisms; medical image processing; MR image processing; decision making; fuzzy inference systems; fuzzy set theory; image filtering; magnetic resonances images; multidimensional segmentation; reasoning; Decision making; Filtering; Fuzzy reasoning; Fuzzy systems; Image processing; Image segmentation; Magnetic domains; Magnetic resonance imaging; Magnetic separation; Multidimensional systems; MR image; active contours; affinity; deformable models; fuzzy inference systems; gradient vector;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedical Technology (ICBBT), 2010 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-6775-4

Type

conf

DOI

10.1109/ICBBT.2010.5479018

Filename

5479018