Abstract
This work provides a new method to estimate and remove baseline drifts in the fMRI signal. The baseline drift in each time series is described as a superposition of physical and physiological phenomena that occur at different scales. A fast algorithm, based on a wavelet representation of the data yields detrended time-series. Experiments with fMRI data demonstrate that our detrending technique can infer and remove drifts that cannot be adequately represented with low degree polynomials. Our detrending technique resulted in a noticeable improvement by reducing the number of false positive and the number of false negative.
This work was supported by a Whitaker Foundation Biomedical Engineering Research Grant.
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References
T.W. Anderson, The statistical analysis of time series, Wiley, 1971.
P.A. Bandettini, The temporal resolution of functional MRI, Functional MRI (C.T.W. Moonen and P.A. Bandettini, eds.), Springer-Verlag, 1999, pp. 205–220.
P.A. Bandettini, A. Jesmanowicz, E.C. Wong, and J.S. Hyde, Processing strategies for time-course data sets in functional MRI of the human brain, Magn. Reson. Med. 30 (1993), 161–173.
G.H. Glover, Deconvolution of impulse response in event-related bold fMRI, NeuroImage (1999), no. 9, 416–429.
P. Jezzard, Physiological noise: strategies for correction, Functional MRI (C.T.W. Moonen and P.A. Bandettini, eds.), Springer-Verlag, 1999, pp. 173–182.
V. Kiviniemi, J. Jauhiainen, O. Tervonen, E. Pääkkö, J. Oikarinen, V. Vainionpää, H. Rantala, and B. Biswal, Slow vasomotor fluctuation in fMRI of anesthetized child brain, Magn. Reson. Med. 44 (2000), 373–378.
F. Kruggel, D.Y von Cramon, and X. Descombes, Comparison of filtering methods for fMRI datasets, NeuroImage (1999), no. 10, 530–543.
M.J. Lowe and D.P. Russell, Treatment of baseline drifts in fMRI time series analysis, Journal of Computer Assisted Tomography 23(3) (1999), 463–473.
S. Mallat, A wavelet tour of signal processing, Academic Press, 1999.
M.J. Schlosser, N. Aoyagi, R.K. Fullbright, J.C. Gore, and G. McCarthy, Functional MRI studies of auditory comprehension, Human Brain Mapping 6 (1998), 1–13.
A.M. Smith, B.K. Lewis, U.E. Ruttimann, F.Q. Ye, T.M. Sinnwell, Y. Yang, J. H. Duyn, and J.A. Frank, Investigation of low frequency drift in fMRI signal, NeuroImage (1999), no. 9 (5), 526–533.
I. Vanzetta and A. Grinvald, Increased cortical oxidative metabolism due to sensory stimulation: implications for functional brain imaging, Science 286 (1999), 1555-8.
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Meyer, F.G., McCarthy, G. (2001). Estimation of Baseline Drifts in fMRI. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_25
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DOI: https://doi.org/10.1007/3-540-45729-1_25
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