Statistical analysis of functional MRI data in the wavelet domain

• Published in: IEEE transactions on medical imaging Vol. 17; no. 2; pp. 142 - 154
• Main Authors: Ruttimann, U.E., Unser, M., Rawlings, R.R., Rio, D., Ramsey, N.F., Mattay, V.S., Hommer, D.W., Frank, J.A., Weinberger, D.R.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.04.1998; Institute of Electrical and Electronics Engineers
• Subjects: Adult; Algorithms; Bandwidth; Biological and medical sciences; Brain - physiology; Echo-Planar Imaging - methods; Echo-Planar Imaging - statistics & numerical data; Fingers - physiology; Humans; Image Enhancement - methods; Image Processing, Computer-Assisted - methods; Image Processing, Computer-Assisted - statistics & numerical data; Investigative techniques, diagnostic techniques (general aspects); Linear Models; Magnetic resonance; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Magnetic Resonance Imaging - statistics & numerical data; Medical sciences; Motor Skills - physiology; Nervous system; Normal Distribution; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Sensitivity and Specificity; Signal detection; Signal to noise ratio; Statistical analysis; Statistical tests; Testing; Wavelet analysis; Wavelet coefficients; Wavelet domain; Wavelet transforms; Statistical analysis; Wavelet transformation; Statistical model; Central nervous system; Medical imagery; Nuclear magnetic resonance imaging; Multiresolution analysis; Image reconstruction; Brain (vertebrata)

The use of the wavelet transform is explored for the detection of differences between brain functional magnetic resonance images (fMRIs) acquired under two different experimental conditions. The method benefits from the fact that a smooth and spatially localized signal can be represented by a small...