Removal of phase artifacts from fMRI data using a Stockwell transform filter improves brain activity detection.
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 significantly reducing image artifacts that overlap anatomical regions of interest. The major advantage of ST-filtering is that artifact frequencies may be removed within a narrow time-window, while preserving the frequency information at all other time points.
Goodyear
Bradley G
BG
Department of Radiology, Seaman Family MR Research Centre, University of Calgary and Foothills Medical Centre, Calgary, Alberta T2N 2T9, Canada. goodyear@ucalgary.ca
Zhu
Hongmei
H
Brown
Robert A
RA
Mitchell
J Ross
JR
D016477:Artifacts; D001931:Brain Mapping; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D014793:Visual Cortex / Q000033:anatomy & histology*