The History Of Wnt inhibitor

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Версія від 12:04, 8 червня 2017, створена Bronzeedge83 (обговореннявнесок) (Створена сторінка: The thalamus segmentation was performed by running a two-stage affine registration to standard space. The first stage is a 12 degree of freedom (DOF) registrati...)

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The thalamus segmentation was performed by running a two-stage affine registration to standard space. The first stage is a 12 degree of freedom (DOF) registration to the non linear MNI152 template, and the second one is a 12 DOF registration LMTK2 using a subcortical mask, to exclude voxels outside the subcortical regions. Pose (rotation and translation) is removed by minimising the sum-of-squares difference between the corresponding vertices of a subject's surface and the mean surface (target) (Patenaude, 2007). Vertex analysis was performed using first utils and thalamic shape change with increasing age was assessed on a per vertex basis. Regional changes in the vertices across all subjects were assessed using a global linear model with age as a continual regressor. The results were corrected for multiple comparisons using FDR (p?U0126 chemical structure was minimised by affine registration of the diffusion images to the non diffusion image, b0. The DTI data were then skull stripped using BET and scalar maps of fractional Romidepsin order anisotropy (FA), and mean diffusivity (MD), were generated by fitting a diffusion tensor model at each voxel using FMRIB's diffusion tool box (FDT). Cortical masks (frontal, parietal, temporal and occipital cortices) were obtained from the Harvard Oxford subcortical and MNI structural atlas in FSL, were thresholded to exclude white matter and were then binarized. The segmented thalami were used as thalamic masks. The DTI scalar maps were registered to standard space using a 2 step process as follows: 1. using FLIRT, each subject's b0 image was registered to its native 3D MPRAGE image, and 2. the 3D MPRAGE image was registered to the MNI_T1_1mm_brain using non-linear registration. The binarized thalamic and cortical masks were then propagated onto each individual's DTI scalar maps using the inverse of the above transformations. In order to exclude voxels that contained CSF along the medial border of the thalamus, the b0 images were segmented using FAST and a binarized cerebrospinal fluid (CSF) mask was used as an exclusion mask. Values for FA and MD were obtained for the whole thalami. Thalamo-cortical connections were assessed using connectivity based seed classification incorporating the distance correction tool in probtrackX (Behrens et al., 2003).