DocumentCode :
3327136
Title :
Intelligent reconstruction method of MR images
Author :
Lee, Hyo Jong ; Lee, Suoo ; Potkin, Steven
Author_Institution :
Div. of Electron. & Inf., Chonbuk Nat. Univ., Jeonju, South Korea
fYear :
2004
fDate :
18-19 Nov. 2004
Firstpage :
365
Lastpage :
369
Abstract :
The magnetic resonance image is essential data to be processed in the neuro-imaging technique. Since the MR signal is obtained by oscillating magnetic fields in a special RF region, the MRI extraction procedure relies on complicated digital signal processing. The reconstruction of a 3D volume brain image from raw data is usually achieved by the trial-error phase angle correction method. In this paper, a straightforward heuristic method is developed to find correct phase angles, which can be used for extracting spatial information from the frequency encoded data. This intelligent method has been implemented into an automatic procedure in the reconstruction stage. It is found that the proposed method can save the neuro-imaging analysts a significant amount of time in the total analyzing procedure. Furthermore, the noise from a ghost image is also significantly reduced in the proposed method.
Keywords :
biomedical MRI; brain; heuristic programming; image denoising; image reconstruction; 3D volume brain image reconstruction; MR image intelligent reconstruction method; MRI extraction procedure; frequency encoded spatial information; ghost image noise reduction; heuristic method; magnetic resonance imaging; neuro-imaging technique; trial-error phase angle correction method; Data mining; Image reconstruction; Magnetic fields; Magnetic resonance; Magnetic resonance imaging; Neuroimaging; RF signals; Radio frequency; Reconstruction algorithms; Signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Signal Processing and Communication Systems, 2004. ISPACS 2004. Proceedings of 2004 International Symposium on
Print_ISBN :
0-7803-8639-6
Type :
conf
DOI :
10.1109/ISPACS.2004.1439077
Filename :
1439077
Link To Document :
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