INRIAlign toolbox for fMRI realignment in SPM99
The INRIAlign toolbox enhances the standard SPM realignment routine
(see topic: spm_realign_ui in SPM99 documentation). In the latter,
rigid registration is achieved by minimization of the sum of squared
intensity differences (SSD) between two images. As noted by several SPM
users, SSD based registration may be biased by a variety of image
artifacts and also by activated areas. To get around this problem,
INRIAlign reduces the influence of large intensity differences by
weighting errors using a non-quadratic, slowly-increasing function (rho
function). This is basically the principle of an M-estimator.
When launching INRIAlign, the user may select a specific rho
function as well as an associated relative cut-off distance (which is
needed by most of the rho functions). By default, the rho function is
that of Geman-McClure while the relative cut-off distance is set to
Apart from this distinction, the method is very similar to
spm_realign and uses the same editable default parameters. Most of the
implementation has been directly adapted from the code written by J.
Author: Alexis Roche, INRIA
Sophia Antipolis, EPIDAURE Group, Now working at the CEA anatomo-fonctional
neuro-imaging unit, Frederic Joliot Hospital, Orsay, France
- L. Freire, A. Roche and J.-Fr. Mangin. What is the best
similarity measure for motion correction in fMRI? IEEE
Transactions in Medical Imaging 21, p. 470-484, 2002.
- L. Freire and J.-F. Mangin. Motion correction algorithms
may create spurious brain activations in the absence of subject motion.
Neuroimage 14(3), p. 709-722, september 2001.
- P.J. Rousseeuw and A.M. Leroy. Robust Regression and
Outlier Detection. Wiley Series in Probability and Mathematical
Last modified: Thu Oct 14 18:47:06 MEST 2004