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Abstract--In region of interest (ROI) based functional magnetic resonance imaging (fMRI) group analysis, errors in
 

Summary: +
Abstract--In region of interest (ROI) based functional
magnetic resonance imaging (fMRI) group analysis, errors in
delineation of an ROI or inclusion of non-active voxels within
an ROI can bias the statistical results. Addressing these
concerns, this paper presents a new fMRI processing method
that simultaneously refines ROI delineation and spatially
denoises fMRI activation statistics within the ROI. The
underlying assumption is that activation statistics within a small
neighborhood are spatially correlated, thereby exhibit similar
levels of influence on the overall ROI's response. Based on this
assumption, we first identify outlier voxels as those having
undue influence on an ROI's feature. Isolated outlier voxels at
region boundaries are then removed, thereby refining the ROI
delineation. The remaining outlier voxels are de-weighted based
on their influence relative to their neighbors to reduce the
effects of voxels deemed falsely active in later analysis. The
proposed method was tested on real fMRI data collected from 8
healthy subjects performing a bulb-squeezing motor task at
various frequencies. Using the proposed method, enhanced

  

Source: Abugharbieh, Rafeef - Department of Electrical and Computer Engineering, University of British Columbia

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences