Quality Map Thresholding for De-noising of Complex-Valued fMRI Data and Its Application to ICA of fMRI

Authors:
Pedro A. Rodriguez;Nicolle M. Correa;Tom Eichele;Vince D. Calhoun;Tülay Adalı
Affiliations:
Department of CSEE, University of Maryland, Baltimore, USA 21250;Department of CSEE, University of Maryland, Baltimore, USA 21250;Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway;Department of ECE, The MIND Research Network and University of New Mexico, Albuquerque, USA 87131;Department of CSEE, University of Maryland, Baltimore, USA 21250
Venue:
Journal of Signal Processing Systems
Year:
2011

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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 to successfully identify and eliminate noisy areas in the fMRI data so they can be used in individual and group studies. 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.