Sentence examples for realignment of functional from inspiring English sources

The sixtieth volume of the prior 3D-session was used as a reference for realignment of functional images to correct for head motion.

Preprocessing included slice timing for correcting differences in the timing of acquisition between slices, realignment of functional time series for correcting head motion, coregistration of functional and anatomical data, segmentation for extracting grey matter, spatial normalization to the Montreal Neurological Institute MNII) space, and spatial smoothing (Gaussian kernel, 6 mm FWHM).

The regressors modeling offsets and rest periods were therefore considered as covariates of no interest together with movement parameters derived from realignment of the functional volumes.

A more age-appropriate and functional realignment of psychiatric categories linked to dysfunctional anger is suggested.

T1-weighted structural images were coregistered to the mean image created by the realignment procedure and were used for normalization of functional images onto the Montreal Neurological Institute Atlas using normalization parameters derived from segmentation of the anatomical image.

Preprocessing of functional images included motion correction (realignment to the first volume), slice time correction (to the middle slice) and normalization to the standard EPI template of the Montreal Neurological Institute (MNI).

Pre-processing included realignment and adjustment for movement related effects, co-registration of functional and anatomical images, spatial normalization into standard stereotactic MNI space, and spatial smoothing using a 6 mm FWHM Gaussian kernel.

After realignment, the anatomical image was coregistered to the first volume of functional images.

Pre-processing of functional scans consisted of corrections for head motion (spatial realignment; trilinear interpolation) and scans were realigned to the first volume of the last functional scan (i.e., the volume closest to the anatomical scan).

For the univariate analyses, this involved image realignment to the first EPI image to correct for movement, segmentation, and spatial normalization of functional images to the MNI reference brain, and smoothing with an 10 mm isotropic Gaussian kernel.

Individual functional scans were preprocessed including the following steps: slice time correction, data realignment of all volumes to the first volume, co-registration and normalization into the MNI Montreal Neurological Institutee) stereotactical space as well as smoothing using an isotropic 8 mm full-width at half-maximum (FWHM) three- dimensional Gaussian kernel.