Adelaide Research & Scholarship
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https://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 |
| DOI: | 10.1109/ICBBT.2010.5479018 |
| Published version: | http://dx.doi.org/10.1109/icbbt.2010.5479018 |
| Appears in Collections: | Aurora harvest 5 Electrical and Electronic Engineering publications |
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