DocumentCode :
2208373
Title :
Quality map thresholding for de-noising of complex-valued fMRI data and its application to ICA of fMRI
Author :
Rodriguez, Pedro A. ; Correa, Nicolle M. ; Adali, Tülay ; Calhoun, Vince D.
Author_Institution :
Dept. of CSEE, Univ. of Maryland, Baltimore County, Baltimore, MD, USA
fYear :
2009
fDate :
1-4 Sept. 2009
Firstpage :
1
Lastpage :
6
Abstract :
Although functional magnetic resonance imaging (fMRI) data are acquired as complex-valued images, traditionally most fMRI studies only use the magnitude of the data. FMRI analysis in the complex domain promises to provide more statistically significant information; however, the noisy nature of the phase poses a challenge for successful study of fMRI by complex-valued signal processing algorithms. In this paper, we introduce a physiologically motivated de-noising method that uses phase quality maps and demonstrate its effectiveness in successfully identifying and eliminating noisy areas in the fMRI data. Additionally, we show how the developed de-noising method improves the results of complex-valued independent component analysis of fMRI data, a very successful tool for blind source separation of biomedical data.
Keywords :
biomedical MRI; blind source separation; brain; haemodynamics; image denoising; independent component analysis; medical image processing; blind source separation; complex-valued fMRI; complex-valued signal processing; functional magnetic resonance imaging; image denoising; independent component analysis; phase quality maps; quality map thresholding; Algorithm design and analysis; Data analysis; Independent component analysis; Information analysis; Magnetic analysis; Magnetic noise; Magnetic resonance imaging; Noise reduction; Phase noise; Signal analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4947-7
Electronic_ISBN :
978-1-4244-4948-4
Type :
conf
DOI :
10.1109/MLSP.2009.5306263
Filename :
5306263
Link To Document :
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