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Proceedings Paper

Improved method for correction of systematic bias introduced by the sub-voxel image registration process in functional magnetic resonance imaging (fMRI)
Author(s): Dee H. Wu; Jasjit Suri; Vincent Magnotta; Tomasz Przebinda; Victor DeBrunner
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Paper Abstract

During functional magnetic resonance imaging (fMRI) brain examinations, the signal extraction from a large number of images is used to evaluate changes in blood oxygenation levels by applying statistical methodology. Image registration is essential as it assists in providing accurate fractional positioning accomplished by using interpolation between sequentially acquired fMRI images. Unfortunately, current subvoxel registration methods found in standard software may produce significant bias in the variance estimator when interpolating with fractional, spatial voxel shifts. It was found that interpolation schemes, as currently applied during the registration of functional brain images, could introduce statistical bias, but there is a possible correction scheme. This bias was shown to result from the "weighted-averaging" process employed by conventional implementation of interpolation schemes. The most severe consequence of inaccurate variance estimators is the undesirable violation of the fundamental 'stationary' assumption required for many statistical methods and Gaussian random field analysis. Thus, this bias violates assumptions of the general linear model (GLM) and/or t-tests commonly used in fMRI studies. Using simulated data as well as actual human data in this, it was demonstrated that this artifact can significantly alter the magnitude and location of the resulting activation patterns/results. Further, the work detailed here introduces a bias correction scheme and evaluates the improved accuracy of its sample variance calculation and influence on fMRI results through comparison with traditional fMRI image registered data.

Paper Details

Date Published: 10 March 2006
PDF: 9 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61440U (10 March 2006); doi: 10.1117/12.655309
Show Author Affiliations
Dee H. Wu, Univ. of Oklahoma Health Sciences Ctr. (United States)
Jasjit Suri, Biomedical Technologies Inc. (United States)
Idaho State Univ. (United States)
Vincent Magnotta, Univ. of Iowa Medical Ctr. (United States)
Tomasz Przebinda, Univ. of Oklahoma (United States)
Victor DeBrunner, Univ. of Oklahoma (United States)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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