Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/62253
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Type: Conference paper
Title: Fuzzy inference systems in MR image processing - A review
Author: Yin, X.
Ng, B.
Abbott, D.
Jia, W.
Ramamohanarao, K.
Citation: Proceedings of the International Conference on Bioinformatics and Biomedical Technology (ICBBT 2010): pp.19-22
Publisher: IEEE
Publisher Place: USA
Issue Date: 2010
ISBN: 9781424467761
Conference Name: International Conference on Bioinformatics and Biomedical Technology (2010 : Chengdu, China)
Statement of
Responsibility: 
x.x. Yin, B. W.-H. Ng, D. Abbott, W.Jia and K. Ramamohanarao
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: fuzzy inference systems; MR image; deformable models; affinity; active contouTS; gradient vector
Rights: ©2010 IEEE
RMID: 0020101470
DOI: 10.1109/ICBBT.2010.5479018
Appears in Collections:Electrical and Electronic Engineering publications

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