Removal of phase artifacts from fMRI data using a Stockwell transform filter improves brain activity detection

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Date

2004

Authors

Goodyear, Bradley G.
Zhu, Hongmei
Brown, Robert A.
Mitchell, Joseph

Journal Title

Journal ISSN

Volume Title

Publisher

Magnetic Resonance in Medicine

Abstract

A novel and automated technique is described for removing fMRI image artifacts resulting from motion outside of the imaging field of view. The technique is based on the Stockwell transform (ST), a mathematical operation that provides the frequency content at each time point within a time-varying signal. Using this technique, 1D Fourier transforms (FTs) are performed on raw image data to obtain phase profiles. The time series of phase magnitude for each and every point in the phase profile is then subjected to the ST to obtain a time-frequency spectrum. The temporal location of an artifact is identified based on the magnitude of a frequency component relative to the median magnitude of that frequency’s occurrence over all time points. After each artifact frequency is removed by replacing its magnitude with the median magnitude, an inverse ST is applied to regain the MR signal. Brain activity detection within fMRI datasets is improved by ignificantly reducing image artifacts that overlap anatomical regions of interest. The major advantage of ST-filtering is that artifact frequencies may be removed within a arrow time-window, while preserving the frequency information at all other time points.

Description

Keywords

fMRI, artifacts, filtering, Stockwell transform, Fourier transform, motion

Citation

Goodyear, B. G., Zhu, H. , Brown, R. A. and Mitchell, J. R. (2004), "Removal of phase artifacts from fMRI data using a Stockwell transform filter improves brain activity detection." Magn. Reson. Med., 51: 16-21. doi:10.1002/mrm.10681