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Proceedings Paper

fMRI activation detection in wavelet signal subspace
Author(s): Hamid Soltanian-Zadeh; Gholam-Ali Hossein-Zadeh; Babak A. Ardekani
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Paper 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.

Paper Details

Date Published: 24 April 2002
PDF: 11 pages
Proc. SPIE 4683, Medical Imaging 2002: Physiology and Function from Multidimensional Images, (24 April 2002); doi: 10.1117/12.463602
Show Author Affiliations
Hamid Soltanian-Zadeh, Univ. of Tehran and Henry Ford Health System (United States)
Gholam-Ali Hossein-Zadeh, Univ. of Tehran and Nathan S. Kline Institute for Psychiatric Research (Iran)
Babak A. Ardekani, Nathan S. Kline Institute for Psychiatric Research (United States)

Published in SPIE Proceedings Vol. 4683:
Medical Imaging 2002: Physiology and Function from Multidimensional Images
Anne V. Clough; Chin-Tu Chen, Editor(s)

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