Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Fuzzy inference systems in MR image processing - A review|
|Citation:||Proceedings of the International Conference on Bioinformatics and Biomedical Technology (ICBBT 2010): pp.19-22|
|Conference Name:||International Conference on Bioinformatics and Biomedical Technology (2010 : Chengdu, China)|
|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|
|Appears in Collections:||Electrical and Electronic Engineering publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.