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Proceedings Paper

Optimizing wavelets for the analysis of fMRI data
Author(s): Manuela Feilner; Thierry Blu; Michael A. Unser
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Paper Abstract

Ruttiman et al. Have proposed to use the wavelet transform for the detection and localization of activation patterns in functional magnetic resonance imaging (fMRI). Their main idea was to apply a statistical test in the wavelet domain to detect the coefficients that are significantly different form zero. Here, we improve the original method in the case of non-stationary Gaussian noise by replacing the original z-test by a t-test that takes into account the variability of each wavelet coefficient separately. The application of a threshold that is proportional to the residual noise level. After the reconstruction by an inverse wavelet transform, further improves the localization of the activation pattern in the spatial domain.

Paper Details

Date Published: 4 December 2000
PDF: 12 pages
Proc. SPIE 4119, Wavelet Applications in Signal and Image Processing VIII, (4 December 2000); doi: 10.1117/12.408652
Show Author Affiliations
Manuela Feilner, Swiss Federal Institute of Technology Lausanne (Switzerland)
Thierry Blu, Swiss Federal Institute of Technology Lausanne (Switzerland)
Michael A. Unser, Swiss Federal Institute of Technology Lausanne (Switzerland)


Published in SPIE Proceedings Vol. 4119:
Wavelet Applications in Signal and Image Processing VIII
Akram Aldroubi; Andrew F. Laine; Michael A. Unser, Editor(s)

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