Paper
24 April 2002 fMRI activation detection in wavelet signal subspace
Hamid Soltanian-Zadeh, Gholam-Ali Hossein-Zadeh, Babak A. Ardekani
Author Affiliations +
Abstract
A new method is proposed for activation detection in event-related functional magnetic resonance imaging (fMRI). The method is based on nonparametric analysis of selected resolution levels (a subspace) in translation invariant wavelet transform (TIWT) domain. Using a priori knowledge about the activation signal and trends, we analyze their power in different resolution levels in TIWT domain and select an optimal set of resolution levels. A nonparametric randomization method is then applied in the wavelet domain for activation detection. This approach suppresses the effects of trends and enhances the detection sensitivity. In addition, since TIWT is insensitive to signal translations, the power analysis is robust with respect to signal shifts. Nonparametric randomization alleviates the need for assumptions about fMRI noise. The method has been applied to simulated and experimental fMRI datasets. Comparisons have been made between the results of the proposed method, a similar method in the time domain, and the cross-correlation method. The proposed method has shown superior sensitivity compared to the other methods.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hamid Soltanian-Zadeh, Gholam-Ali Hossein-Zadeh, and Babak A. Ardekani "fMRI activation detection in wavelet signal subspace", Proc. SPIE 4683, Medical Imaging 2002: Physiology and Function from Multidimensional Images, (24 April 2002); https://doi.org/10.1117/12.463602
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KEYWORDS
Functional magnetic resonance imaging

Wavelets

Statistical analysis

Signal detection

Wavelet transforms

Brain

Computer simulations

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