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Two experiments were conducted to examine the effect of automatic image realignment on the performance of laparoscopic surgery.
Prior to distortion correction, the data were motion corrected by image realignment with the reference scan.
After slice-timing correction of the images, SPM2 [36]was used for image realignment, smoothing with a 3-D 9 mm isotropic Gaussian kernel, and normalization into the Montreal Neurological Institute averaged template based on structural MRIs from 152 brains.
Data pre-processing for functional volumes included image realignment, three-dimensional motion correction, linear de-trending, temporal frequency filtering with high pass filter, and spatial smoothing with a 4-mm Gaussian kernel (full width at half-maximum).
A 4th degree B-spline function without weighting and without warping was used for image realignment (head motion was less than 1-mm translations and 1°-rotations for all scans for all fMRI runs).
A fiducial target was placed to facilitate image realignment correcting for patient movement.
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SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/) was used to pre-process the images, including realignment, normalization, and smoothing.
All EPI volumes were aligned to the first volume acquired for each participant and a mean EPI image generated after realignment.
Image preprocessing involved realignment to correct for head motion between scans, normalization into standard Montreal Neurological Institute (MNI) stereotactic brain space, and smoothing with an isotropic 10 mm full-width-at-half-maximum Gaussian kernel.
Preprocessing of the image volumes included realignment of head motions, slice-time correction with reference to the middle slice acquired in time, normalization to the EPI-template based on the Montreal Neurological Institute MNII) reference brain (resampled voxel size 3 × 3 × 3 mm), and spatial smoothing with a Gaussian kernel (8 mm at full-width half-maximum).
In theory, NAC images should provide better realignment than AC images.
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