DocumentCode :
472039
Title :
Threshold Optimization of Adaptive Template Filtering for MRI Based on Intelligent Optimization Algorithm
Author :
Guo, Lei ; Wu, Youxi ; Liu, Xuena ; Li, Ying ; Xu, Guizhi ; Yan, Weili
Author_Institution :
Joint Key Lab. of Electromagn. Field & Electr. Apparatus Reliability, Hebei Univ. of Technol., Tianjin
fYear :
2006
fDate :
Aug. 30 2006-Sept. 3 2006
Firstpage :
4763
Lastpage :
4766
Abstract :
Intelligent Optimization Algorithm (IOA) mainly includes Immune Algorithm (IA) and Genetic Algorithm (GA). One of the most important characteristics of MRI is the complicated changes of gray level. Traditional filtering algorithms are not fit for MRI. Adaptive Template Filtering Method (ATFM) is an appropriate denoising method for MRI. However, selecting threshold for ATFM is a complicated problem which directly affects the denoising result. Threshold selection has been based on experience. Thus, it was lack of solid theoretical foundation. In this paper, 2 kinds of IOA are proposed for threshold optimization respectively. As our experiment demonstrates, they can effectively solve the problem of threshold selection and perfect ATFM. Through algorithm analysis, the performance of IA surpasses the performance of GA. As a new kind of IOA, IA exhibits its great potential in image processing
Keywords :
adaptive filters; artificial immune systems; biomedical MRI; filtering theory; genetic algorithms; image denoising; medical image processing; MRI; adaptive template filtering method; denoising method; genetic algorithm; image processing; immune algorithm; intelligent optimization algorithm; threshold optimization; Adaptive filters; Algorithm design and analysis; Filtering algorithms; Genetic algorithms; Image analysis; Image processing; Magnetic resonance imaging; Noise reduction; Performance analysis; Solids;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
ISSN :
1557-170X
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2006.260331
Filename :
4462866
Link To Document :
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