Improved method for correction of systematic bias introduced by the sub-voxel image registration process in functional magnetic resonance imaging (fMRI)

Dee H. Wu; Jasjit Suri; Vincent Magnotta; Tomasz Przebinda; Victor DeBrunner

doi:10.1117/12.655309

10 March 2006 Improved method for correction of systematic bias introduced by the sub-voxel image registration process in functional magnetic resonance imaging (fMRI)

Dee H. Wu, Jasjit Suri, Vincent Magnotta, Tomasz Przebinda, Victor DeBrunner

Author Affiliations +

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61440U (2006) https://doi.org/10.1117/12.655309
Event: Medical Imaging, 2006, San Diego, California, United States

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.

Citation Download Citation

Dee H. Wu, Jasjit Suri, Vincent Magnotta, Tomasz Przebinda, and Victor DeBrunner "Improved method for correction of systematic bias introduced by the sub-voxel image registration process in functional magnetic resonance imaging (fMRI)", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61440U (10 March 2006); https://doi.org/10.1117/12.655309

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available